This document provides a seminar report on Ambient Intelligence (AmI). It discusses the history and vision of AmI, which envisions electronic environments that are sensitive and responsive to people. Key concepts of AmI include systems being embedded, context-aware, personalized, adaptive and anticipatory. Achieving AmI requires technologies like sensors, networks and human-computer interfaces. AmI also has social and political influences as technology becomes more ubiquitous. The document outlines how AmI relates to areas like networks, sensors and artificial intelligence and discusses the 5Ws and 3Ps principles of AmI design and implementation.
Ambient intelligence (AmI) refers to digital environments that are aware of a person's presence and context and can respond accordingly. Key aspects of AmI include systems and technologies that are embedded, context-aware, personalized, adaptive, and anticipatory. AmI aims to improve people's quality of life while also benefiting the environment through more efficient energy usage and waste reduction. Some applications of AmI include smart homes, health monitoring, transportation, education, emergency services, and production facilities. However, challenges remain regarding issues like limited sensor battery life, modeling multiple users, self-testing software, and privacy/security concerns.
Ambient intelligence is an emerging discipline that brings intelligence to our everyday environments and makes those environments sensitive to us. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence.
Ambient Intelligence seminar report made by Shifali JindalShifaliJindal
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to human presence. Key technologies that enable AmI include ubiquitous computing, ubiquitous communication, and intelligent user interfaces. As devices become smaller, more connected and integrated into our environment, the technology disappears into our surroundings until only the user interface remains. AmI has applications in smart homes, healthcare, public transportation, and education by embedding intelligence and sensors into environments to automatically adapt to and assist users. Realizing the full vision of AmI will require overcoming challenges around privacy, security, and developing natural human-computer interaction.
This document provides an overview of ambient intelligence (AmI). It defines AmI as a paradigm that replaces conventional input/output devices with sensors and processors, enabling objects to communicate and interact with users naturally. The document outlines a generic AmI architecture consisting of sensors, actuators, middleware, and AI reasoning. Examples of AmI systems for personalized sports training and elderly assisted living are described. The promises of AmI include more convenient access to data and helpful behaviors from AI, but dangers include threats to privacy from increased data collection. The future of AmI may include greater social and emotional intelligence and scaling to support multiple users.
Ambient intelligence aims to create technology that is invisible, embedded in our environments, and responds easily to human presence and needs. It uses sensors, RFID, biometrics and other technologies to create personalized, intelligent home or automotive environments. For example, a home could automatically adjust lights and temperature based on occupants' preferences and activities. Challenges include the cost to install and maintain such systems as well as potential privacy issues, but proponents argue ambient intelligence could improve quality of life by saving time and increasing safety, security and entertainment.
Ambient Intelligence (AmI) refers to a vision of the future information society where intelligent interfaces enable people and devices to interact with each other and with the environment. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence. Because these contributing fields have experienced tremendous growth in the last few years, AmI research has strengthened and expanded. Because AmI research is maturing, the resulting technologies promise to revolutionaries daily human life by making people's surroundings edible and adaptive.
Ambient intelligence (AmI) aims to change how people interact with technology by making their surroundings more adaptive through the use of networked sensors and intelligent software. Key AmI technologies include various sensors like RFID and microphones that can detect people's presence and activities. AmI systems also rely on reasoning abilities to interpret sensor data and predict/recognize contexts and activities, and acting abilities to tie the digital and physical worlds together through devices like robots. Example applications of AmI include smart homes that use sensors and intelligent appliances to provide security, convenience and assisted living features to homeowners. Overall, AmI promises to revolutionize daily life but also faces ongoing challenges in user preferences, interactions, and reliance on wireless sensors and infrastructure.
Ambient intelligence (AmI) refers to digital environments that are aware of a person's presence and context and can respond accordingly. Key aspects of AmI include systems and technologies that are embedded, context-aware, personalized, adaptive, and anticipatory. AmI aims to improve people's quality of life while also benefiting the environment through more efficient energy usage and waste reduction. Some applications of AmI include smart homes, health monitoring, transportation, education, emergency services, and production facilities. However, challenges remain regarding issues like limited sensor battery life, modeling multiple users, self-testing software, and privacy/security concerns.
Ambient intelligence is an emerging discipline that brings intelligence to our everyday environments and makes those environments sensitive to us. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence.
Ambient Intelligence seminar report made by Shifali JindalShifaliJindal
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to human presence. Key technologies that enable AmI include ubiquitous computing, ubiquitous communication, and intelligent user interfaces. As devices become smaller, more connected and integrated into our environment, the technology disappears into our surroundings until only the user interface remains. AmI has applications in smart homes, healthcare, public transportation, and education by embedding intelligence and sensors into environments to automatically adapt to and assist users. Realizing the full vision of AmI will require overcoming challenges around privacy, security, and developing natural human-computer interaction.
This document provides an overview of ambient intelligence (AmI). It defines AmI as a paradigm that replaces conventional input/output devices with sensors and processors, enabling objects to communicate and interact with users naturally. The document outlines a generic AmI architecture consisting of sensors, actuators, middleware, and AI reasoning. Examples of AmI systems for personalized sports training and elderly assisted living are described. The promises of AmI include more convenient access to data and helpful behaviors from AI, but dangers include threats to privacy from increased data collection. The future of AmI may include greater social and emotional intelligence and scaling to support multiple users.
Ambient intelligence aims to create technology that is invisible, embedded in our environments, and responds easily to human presence and needs. It uses sensors, RFID, biometrics and other technologies to create personalized, intelligent home or automotive environments. For example, a home could automatically adjust lights and temperature based on occupants' preferences and activities. Challenges include the cost to install and maintain such systems as well as potential privacy issues, but proponents argue ambient intelligence could improve quality of life by saving time and increasing safety, security and entertainment.
Ambient Intelligence (AmI) refers to a vision of the future information society where intelligent interfaces enable people and devices to interact with each other and with the environment. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence. Because these contributing fields have experienced tremendous growth in the last few years, AmI research has strengthened and expanded. Because AmI research is maturing, the resulting technologies promise to revolutionaries daily human life by making people's surroundings edible and adaptive.
Ambient intelligence (AmI) aims to change how people interact with technology by making their surroundings more adaptive through the use of networked sensors and intelligent software. Key AmI technologies include various sensors like RFID and microphones that can detect people's presence and activities. AmI systems also rely on reasoning abilities to interpret sensor data and predict/recognize contexts and activities, and acting abilities to tie the digital and physical worlds together through devices like robots. Example applications of AmI include smart homes that use sensors and intelligent appliances to provide security, convenience and assisted living features to homeowners. Overall, AmI promises to revolutionize daily life but also faces ongoing challenges in user preferences, interactions, and reliance on wireless sensors and infrastructure.
This document discusses ambient intelligence, which brings intelligence to everyday environments through hidden interfaces that recognize users and adapt to their needs. It describes key characteristics of being human-centric, embedded, context-aware, personalized and adaptive. The technologies that enable ambient intelligence are ubiquitous computing, ubiquitous communication and intelligent user interfaces. Applications include smart homes, healthcare, education and public transport. Research challenges include modeling multiple users, designing self-repairing software, and ensuring security and privacy.
Ambient intelligence (AmI) refers to digital environments that are sensitive and responsive to human presence. AmI is based on ubiquitous computing, communication, and intelligent user interfaces. It aims to empower users through context-aware and adaptive technologies. Key challenges include privacy and security as AmI systems collect extensive user data and monitor environments. Potential applications include smart homes, healthcare, transportation, education, emergency response, and industry.
Ambient Intelligence made by Shifali JindalShifaliJindal
Ambient intelligence is an emerging discipline that brings intelligence to everyday environments through hidden interfaces that recognize users and adapt to their needs. It is built on technologies like ubiquitous computing, communication and intelligent user interfaces. The key steps involve sensing a user's environment and activities, reasoning to interpret context and predict needs, and acting by automating systems or providing notifications. Applications include smart homes, healthcare, transportation, education and more. Challenges remain around privacy, interoperability, reliability and resource constraints.
This document proposes a Virtual Smart Phone (VSP) system that allows users to interact with digital devices and communicate with others through touch and gesture-based interactions on their palm, replacing the need for a physical mobile phone. The VSP turns a user's hand into a mobile phone through which they can make calls, receive calls, capture images/video, and transfer data to other users or devices over networks like GSM or the internet. The goal is to free interactions from physical device dependencies and connect the physical world to the virtual world. Potential applications include health monitoring, accessing product information, getting news/weather updates, connecting devices virtually, and using in education systems.
The document discusses the Internet of Things (IoT). It defines IoT as physical objects embedded with sensors that can collect and exchange data over the internet. It describes how IoT works through technologies like RFID, sensors, and wireless connections. It also outlines some applications of IoT like smart homes, manufacturing, healthcare, and more. Finally, it discusses technological challenges and criticisms of IoT, such as issues with privacy, security, and political manipulation.
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to human presence. AmI aims to make our everyday environments intelligent and responsive to our immediate needs through networks of hidden computing devices. AmI was first proposed in 1988 and is based on ubiquitous computing, ubiquitous communication, and intelligent user interfaces. Key technologies that enable AmI include sensing human presence and activities, reasoning about user behaviors and needs, and acting through intelligent devices to affect the environment. While AmI offers benefits like customizing environments and increasing human control, ongoing challenges include privacy, security, and designing self-testing software.
Augmented reality The future of computingAbhishek Abhi
This is a PPT on Developing Augmented Reality this field is rapidly developing around the world. this ppt describes the entire meaning of the word augmented reality and what it is made up off and the working of this devices.
Haptic technology provides tactile feedback through devices that allow users to touch and feel virtual objects. It works by applying forces, vibrations or motions to the user through input/output devices like data gloves. This gives users the sense of touch when interacting with computer-generated environments. Common haptic devices include Phantom, which provides 3D touch feedback of virtual objects, and Cyber Grasp, which fits over the hand and provides force feedback to each finger. Haptics have applications in virtual reality, medicine, video games, mobile devices, arts and robotics. The future may see holographic interaction and remote surgery using haptics.
“The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network
Today Home Automation is one of the growing requirement in the society. This paper presents the implementation of Home Automation using Raspberry Pi. The Raspberry Pi is a basic embedded system and being a low cost single-board computer used to reduce the complexity of systems in real time applications. This application mainly serves as an efficient base to control various home appliance like Fan, Tube light, Refrigerator through mobile based application. The application is designed to provide a facility to user to access control of many appliances used in homes.
-Integrating information with real world.
-The s/w program processes the video stream data captured by the camera and tracks the location of colored markers using simple computer vision techniques.
The document discusses the introduction to Internet of Things (IoT). It defines IoT and describes its characteristics, physical and logical design, enabling technologies, and deployment levels. The physical design covers IoT devices, protocols, and communication layers. The logical design includes functional blocks, communication models, and APIs. Enabling technologies include wireless sensor networks, cloud computing, big data analysis, communication protocols, and embedded systems. IoT deployment levels range from single node local systems to multi-node systems with local coordination and cloud-based storage, analysis and applications.
The document discusses the Internet of Things (IoT). It defines IoT as the network of physical objects embedded with electronics, software, and sensors that enables the collection and exchange of data. Key components that drive IoT include sensors that detect information, connectivity that allows communication over the internet, and people and processes that analyze and take action based on the data. Some advantages of IoT are more efficient resource utilization, minimized human effort through automation, and time savings. The document outlines current and potential future applications of IoT but also notes there are challenges to widespread adoption.
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from embedded systems and extreme programming to biometrics, quantum computing, and more.
2. Some examples include elastic quotas, electronic ink, gesture recognition, graphics processing units, grid computing, and honeypots.
3. The broad range of topics provide many options for students or professionals to explore emerging technologies and issues in computing.
Internet of Things (Iot) Based Smart Environment and its Applicationsijtsrd
In day to day world the internet of things is one of the emerging technologies. Through wired and wireless medium IOT connects various object which helps the human to interact with objects in both digital as well as physical world. Due to increase of population the services are very challenging for the providers. To overcome those challenges the IOT has developed with many applications. IOT contain the sensor which connects to Bluetooth, Wi-Fi, RFID and also it covers wide area with many technologies like GSM, 3G and GPRS. The IOT devices collect many useful information from various devices and flow the data between many devices. The flow of information can be done without human'“to-human or human'“to-computer interaction. Due to IOT the world will become smart so it is called as smart home, smart cities, smart building and also some applications. Many sectors are connected to RFID technologies like banking, agriculture, education, domestic appliances monitoring, Surveillances, government '“ e services, government '“ e services, traffic surveillance, meteorology and security and emergency. This devices also consist of heat, light, security system with less cost. The online capable devices figure was 31% in 2016. It increased up to 8.4 billion in 2017. The IOT devices will be increased more than 30 billion in the year of 2020. The value of IOT will reach nearly up to $7.1 trillion. In 2019 Enterprise internet of things (EIOT) devices increases up to 9.1 billion. In this paper IOT based smart environment is discussed with its issue. It is used for transport, vehicle parking, waste management, reduce traffic, increase the better communication with road side objects like hospital, school and also with other objects. Devi Kala Rathinam. D | Sherin. J | Santhiya Grace. A"Internet of Things (Iot) Based Smart Environment and its Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd15709.pdf http://www.ijtsrd.com/engineering/computer-engineering/15709/internet-of-things-iot-based-smart-environment-and-its-applications/devi-kala-rathinam-d
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from elastic quotas to 3D internet.
2. Some examples include extreme programming, face recognition technology, honeypots, IP spoofing, digital light processing, and cloud computing.
3. The topics cover a wide range of areas including networking, security, hardware, software, interfaces, and applications.
The document discusses Internet of Things (IoT). It defines IoT as the network of physical objects embedded with sensors, software and connectivity that allows them to collect and exchange data. The document outlines the history of IoT and how it works by connecting physical objects through various technologies like RFID, sensors and wireless networks. It provides examples of applications of IoT in various domains like healthcare, transportation, manufacturing etc. It also discusses the current status and future prospects of IoT along with technological challenges and criticisms around privacy, security and control issues.
The document discusses light-based Wi-Fi (Li-Fi) which uses visible light communication and LED lamps to transmit data wirelessly. It notes that Li-Fi has significantly higher capacity than radio-based Wi-Fi as the light spectrum is much larger. It also describes how Li-Fi has advantages over Wi-Fi such as better security since light cannot pass through walls to intercept signals. The document outlines some of the key components used in a Li-Fi system like LED lamps that can transmit data by varying in intensity and a photodetector that receives the signals.
The document discusses the Internet of Things (IoT). IoT is a concept that considers objects in the environment that can connect wirelessly and interact with each other to create new applications and services. The goal of IoT is to enable anything to connect anytime and anywhere using any network. Key IoT technologies include communication protocols, hardware, software, data platforms, and machine learning. Sensors, connectivity, and integrating data with people and processes enable smart systems and IoT.
Fog computing is a distributed computing paradigm that processes data closer to IoT devices rather than sending all data to centralized cloud servers. This helps address issues like high latency, bandwidth constraints, and scalability challenges. Fog computing deploys compute and storage resources between end devices and cloud data centers. It can perform tasks like data aggregation, analytics, and decision making near devices to enable low-latency applications. Coordinating fog and cloud resources requires addressing challenges regarding resource management, load balancing, APIs, security, and fault tolerance.
This document provides a list of over 200 seminar topics related to computer science, electronics, IT, mechanical engineering, electrical engineering, civil engineering, applied electronics, chemical engineering, biomedical engineering, and MBA projects. The topics are divided into categories such as computer science projects, electronics projects, IT projects, and so on. Each topic includes a brief 1-2 sentence description. Contact information is provided at the bottom for requesting full reports on any of the topics.
The document discusses night vision technology and night vision devices (NVDs). It covers what night vision is, the different types including biological and technical approaches, how NVDs work using image intensification or thermal imaging, the generations of devices, and their applications in military, security, and civilian use. Key points include that NVDs allow vision in low-light conditions, common components like image intensifier tubes, and that thermal imaging detects infrared light emitted as heat without needing ambient light.
This document discusses ambient intelligence, which brings intelligence to everyday environments through hidden interfaces that recognize users and adapt to their needs. It describes key characteristics of being human-centric, embedded, context-aware, personalized and adaptive. The technologies that enable ambient intelligence are ubiquitous computing, ubiquitous communication and intelligent user interfaces. Applications include smart homes, healthcare, education and public transport. Research challenges include modeling multiple users, designing self-repairing software, and ensuring security and privacy.
Ambient intelligence (AmI) refers to digital environments that are sensitive and responsive to human presence. AmI is based on ubiquitous computing, communication, and intelligent user interfaces. It aims to empower users through context-aware and adaptive technologies. Key challenges include privacy and security as AmI systems collect extensive user data and monitor environments. Potential applications include smart homes, healthcare, transportation, education, emergency response, and industry.
Ambient Intelligence made by Shifali JindalShifaliJindal
Ambient intelligence is an emerging discipline that brings intelligence to everyday environments through hidden interfaces that recognize users and adapt to their needs. It is built on technologies like ubiquitous computing, communication and intelligent user interfaces. The key steps involve sensing a user's environment and activities, reasoning to interpret context and predict needs, and acting by automating systems or providing notifications. Applications include smart homes, healthcare, transportation, education and more. Challenges remain around privacy, interoperability, reliability and resource constraints.
This document proposes a Virtual Smart Phone (VSP) system that allows users to interact with digital devices and communicate with others through touch and gesture-based interactions on their palm, replacing the need for a physical mobile phone. The VSP turns a user's hand into a mobile phone through which they can make calls, receive calls, capture images/video, and transfer data to other users or devices over networks like GSM or the internet. The goal is to free interactions from physical device dependencies and connect the physical world to the virtual world. Potential applications include health monitoring, accessing product information, getting news/weather updates, connecting devices virtually, and using in education systems.
The document discusses the Internet of Things (IoT). It defines IoT as physical objects embedded with sensors that can collect and exchange data over the internet. It describes how IoT works through technologies like RFID, sensors, and wireless connections. It also outlines some applications of IoT like smart homes, manufacturing, healthcare, and more. Finally, it discusses technological challenges and criticisms of IoT, such as issues with privacy, security, and political manipulation.
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to human presence. AmI aims to make our everyday environments intelligent and responsive to our immediate needs through networks of hidden computing devices. AmI was first proposed in 1988 and is based on ubiquitous computing, ubiquitous communication, and intelligent user interfaces. Key technologies that enable AmI include sensing human presence and activities, reasoning about user behaviors and needs, and acting through intelligent devices to affect the environment. While AmI offers benefits like customizing environments and increasing human control, ongoing challenges include privacy, security, and designing self-testing software.
Augmented reality The future of computingAbhishek Abhi
This is a PPT on Developing Augmented Reality this field is rapidly developing around the world. this ppt describes the entire meaning of the word augmented reality and what it is made up off and the working of this devices.
Haptic technology provides tactile feedback through devices that allow users to touch and feel virtual objects. It works by applying forces, vibrations or motions to the user through input/output devices like data gloves. This gives users the sense of touch when interacting with computer-generated environments. Common haptic devices include Phantom, which provides 3D touch feedback of virtual objects, and Cyber Grasp, which fits over the hand and provides force feedback to each finger. Haptics have applications in virtual reality, medicine, video games, mobile devices, arts and robotics. The future may see holographic interaction and remote surgery using haptics.
“The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network
Today Home Automation is one of the growing requirement in the society. This paper presents the implementation of Home Automation using Raspberry Pi. The Raspberry Pi is a basic embedded system and being a low cost single-board computer used to reduce the complexity of systems in real time applications. This application mainly serves as an efficient base to control various home appliance like Fan, Tube light, Refrigerator through mobile based application. The application is designed to provide a facility to user to access control of many appliances used in homes.
-Integrating information with real world.
-The s/w program processes the video stream data captured by the camera and tracks the location of colored markers using simple computer vision techniques.
The document discusses the introduction to Internet of Things (IoT). It defines IoT and describes its characteristics, physical and logical design, enabling technologies, and deployment levels. The physical design covers IoT devices, protocols, and communication layers. The logical design includes functional blocks, communication models, and APIs. Enabling technologies include wireless sensor networks, cloud computing, big data analysis, communication protocols, and embedded systems. IoT deployment levels range from single node local systems to multi-node systems with local coordination and cloud-based storage, analysis and applications.
The document discusses the Internet of Things (IoT). It defines IoT as the network of physical objects embedded with electronics, software, and sensors that enables the collection and exchange of data. Key components that drive IoT include sensors that detect information, connectivity that allows communication over the internet, and people and processes that analyze and take action based on the data. Some advantages of IoT are more efficient resource utilization, minimized human effort through automation, and time savings. The document outlines current and potential future applications of IoT but also notes there are challenges to widespread adoption.
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from embedded systems and extreme programming to biometrics, quantum computing, and more.
2. Some examples include elastic quotas, electronic ink, gesture recognition, graphics processing units, grid computing, and honeypots.
3. The broad range of topics provide many options for students or professionals to explore emerging technologies and issues in computing.
Internet of Things (Iot) Based Smart Environment and its Applicationsijtsrd
In day to day world the internet of things is one of the emerging technologies. Through wired and wireless medium IOT connects various object which helps the human to interact with objects in both digital as well as physical world. Due to increase of population the services are very challenging for the providers. To overcome those challenges the IOT has developed with many applications. IOT contain the sensor which connects to Bluetooth, Wi-Fi, RFID and also it covers wide area with many technologies like GSM, 3G and GPRS. The IOT devices collect many useful information from various devices and flow the data between many devices. The flow of information can be done without human'“to-human or human'“to-computer interaction. Due to IOT the world will become smart so it is called as smart home, smart cities, smart building and also some applications. Many sectors are connected to RFID technologies like banking, agriculture, education, domestic appliances monitoring, Surveillances, government '“ e services, government '“ e services, traffic surveillance, meteorology and security and emergency. This devices also consist of heat, light, security system with less cost. The online capable devices figure was 31% in 2016. It increased up to 8.4 billion in 2017. The IOT devices will be increased more than 30 billion in the year of 2020. The value of IOT will reach nearly up to $7.1 trillion. In 2019 Enterprise internet of things (EIOT) devices increases up to 9.1 billion. In this paper IOT based smart environment is discussed with its issue. It is used for transport, vehicle parking, waste management, reduce traffic, increase the better communication with road side objects like hospital, school and also with other objects. Devi Kala Rathinam. D | Sherin. J | Santhiya Grace. A"Internet of Things (Iot) Based Smart Environment and its Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd15709.pdf http://www.ijtsrd.com/engineering/computer-engineering/15709/internet-of-things-iot-based-smart-environment-and-its-applications/devi-kala-rathinam-d
1. The document lists over 100 potential seminar topics in computer science and information technology, ranging from elastic quotas to 3D internet.
2. Some examples include extreme programming, face recognition technology, honeypots, IP spoofing, digital light processing, and cloud computing.
3. The topics cover a wide range of areas including networking, security, hardware, software, interfaces, and applications.
The document discusses Internet of Things (IoT). It defines IoT as the network of physical objects embedded with sensors, software and connectivity that allows them to collect and exchange data. The document outlines the history of IoT and how it works by connecting physical objects through various technologies like RFID, sensors and wireless networks. It provides examples of applications of IoT in various domains like healthcare, transportation, manufacturing etc. It also discusses the current status and future prospects of IoT along with technological challenges and criticisms around privacy, security and control issues.
The document discusses light-based Wi-Fi (Li-Fi) which uses visible light communication and LED lamps to transmit data wirelessly. It notes that Li-Fi has significantly higher capacity than radio-based Wi-Fi as the light spectrum is much larger. It also describes how Li-Fi has advantages over Wi-Fi such as better security since light cannot pass through walls to intercept signals. The document outlines some of the key components used in a Li-Fi system like LED lamps that can transmit data by varying in intensity and a photodetector that receives the signals.
The document discusses the Internet of Things (IoT). IoT is a concept that considers objects in the environment that can connect wirelessly and interact with each other to create new applications and services. The goal of IoT is to enable anything to connect anytime and anywhere using any network. Key IoT technologies include communication protocols, hardware, software, data platforms, and machine learning. Sensors, connectivity, and integrating data with people and processes enable smart systems and IoT.
Fog computing is a distributed computing paradigm that processes data closer to IoT devices rather than sending all data to centralized cloud servers. This helps address issues like high latency, bandwidth constraints, and scalability challenges. Fog computing deploys compute and storage resources between end devices and cloud data centers. It can perform tasks like data aggregation, analytics, and decision making near devices to enable low-latency applications. Coordinating fog and cloud resources requires addressing challenges regarding resource management, load balancing, APIs, security, and fault tolerance.
This document provides a list of over 200 seminar topics related to computer science, electronics, IT, mechanical engineering, electrical engineering, civil engineering, applied electronics, chemical engineering, biomedical engineering, and MBA projects. The topics are divided into categories such as computer science projects, electronics projects, IT projects, and so on. Each topic includes a brief 1-2 sentence description. Contact information is provided at the bottom for requesting full reports on any of the topics.
The document discusses night vision technology and night vision devices (NVDs). It covers what night vision is, the different types including biological and technical approaches, how NVDs work using image intensification or thermal imaging, the generations of devices, and their applications in military, security, and civilian use. Key points include that NVDs allow vision in low-light conditions, common components like image intensifier tubes, and that thermal imaging detects infrared light emitted as heat without needing ambient light.
This document summarizes a seminar on using mobile apps to teach mathematics at the primary level. It describes grouping students into levels based on their math skills and exposing them to interactive apps on a mobile phone to help them learn counting, number recognition, and the four basic operations. The approach uses a trial and error method with immediate feedback to help slow learners. Observations found this approach helped students learn at their own pace and engaged them in learning. The conclusion is that interactive technology can make learning fun and help students learn skills like number sense that prepare them for further education.
Night vision devices use image intensification or thermal imaging to produce images in low-light conditions. Image intensification amplifies existing light using a photocathode and microchannel plate to produce an image, while thermal imaging detects infrared radiation emitted or reflected from objects. There are multiple generations of night vision devices with improvements in resolution, gain, and range. Night vision technology has military, law enforcement, hunting, and other applications for seeing in darkness.
The document discusses the Sailfish OS mobile operating system. It provides details on its origins from the Maemo and Meego OS projects from Nokia. It describes Sailfish OS as a Linux-based operating system developed by Jolla for use on mobile devices. It also lists many phones and tablets that run Sailfish OS officially or through unofficial ports, and details the OS's version history and key features.
An automotive night vision system uses a thermographic camera to increase a driver's perception and seeing distance in darkness or poor weather beyond the reach of the vehicle's headlights. Such systems are offered as optional equipment on certain premium vehicles. The first introduction was in 2000 on Cadillac Deville.
CRAXweb: Automatic Exploit Generation for Web ApplicationsAung Thu Rha Hein
This is my first seminar presentation. The presentation is based on the core paper: CRAXweb: Automatic Web Application Testing and Attack Generation. If you are interested in this research area, other research methods of this research can be found at reference sections.
Night vision technology in Cars(Automotive),types of night vision technology,Mercedes Night vision technology compared with BMW's night vision technology,active night vision assist,passive night vision assist,thermographic image sensor
The document discusses XML Encryption, which is a W3C standard for encrypting XML documents and data. It can encrypt entire documents, parts of documents, or external objects. XML Encryption uses symmetric or asymmetric encryption and supports algorithms like AES and Triple DES. It provides elements for specifying the encryption method, key information, and encrypted data or references to encrypted resources. The key information does not directly include the encryption key but provides ways to locate it through names, encryption, or key agreement protocols.
This document discusses cross-site scripting (XSS) attacks. It defines XSS as an attack where malicious scripts are injected into otherwise trusted websites. The document outlines three types of XSS attacks and provides examples of real-world XSS worms. It explains how to exploit stored, reflected, and DOM-based XSS vulnerabilities. Finally, it recommends ways to prevent XSS, including input and output filtering, encoding output, and using mitigations like HttpOnly cookies and content security policies.
E ink is an electronic paper display invented in 1996 at MIT. It uses microcapsules containing charged black and white pigment particles that are moved to the top or bottom of the capsule by electric fields to display text and images. E ink displays are used in e-readers and other devices because they are bi-stable, require no power to maintain a display, and can be read in direct sunlight. The document discusses the history, working mechanism, applications, advantages like low power consumption, and future uses of e ink technology.
The E-Ball concept pc is a sphere shaped pc which is the smallest design among all the laptops and desktops.
This concept PC will measure 160mm in diameter and it was designed for Microsoft Windows OS.
This computer has all the features like a traditional computer, like, mouse, dvd, large screen display, mother-board, hard
drive, web came ,modem, LAN& WAN slots etc.
The document provides information about e-ink technology, including its history, working principle, variants, applications, advantages, and future scope. E-ink technology uses electrically charged pigments in microcapsules that can be moved around using an electric field to create an electronic paper display. It is used in applications such as e-readers, watches, phones, and other devices to create low-power, sunlight readable displays.
This document discusses nanorobotics, which involves engineering robots at the nanoscale level. Nanorobots could potentially travel inside the human body to detect information, find defects, or deliver drugs. Theoretical discussions of nanorobotics date back to Richard Feynman and R. Freitas. Potential applications of nanorobots include cleaning arteries to treat atherosclerosis, detecting pathogens in blood cells, tooth repair in dentistry, and assisting in cancer treatment. Both advantages and disadvantages of using organic nanobots for medical applications are presented.
Sailfish OS is a Linux-based operating system developed by Jolla for mobile devices. It is based on the Linux kernel and Mer Core middleware. The OS combines the Linux kernel with Jolla's proprietary UI and supports running Android applications through a compatibility layer. Sailfish OS 2.0 is currently in development with a focus on improved Android compatibility, new Intel architecture support, and enhanced privacy and personalization features. The OS uses open source technologies like Qt and aims to eventually be fully open source.
seminar report on night vision technologyAmit Satyam
This document summarizes the history and technology behind night vision devices. It describes how early generations used multiple image intensifier tubes to amplify light, while later generations employed microchannel plates and gallium arsenide photocathodes to improve light sensitivity and gain. The document outlines the key technological advances between each generation, from Generation 0 devices that used infrared illumination to Generation 4's filmless and gated technology offering improved resolution and reduced noise in varying light conditions.
The document is a seminar report submitted in partial fulfillment of a Bachelor of Engineering degree in Industrial Engineering and Management from Bangalore Institute of Technology in 2016. The report discusses night vision systems in automobiles and aims to highlight advancements that can convert monochromatic night vision displays to colorized displays to better assist drivers. It provides background on night vision technology, the components of automotive night vision systems including infrared projectors, night vision cameras, image intensifiers, and infrared sensors. It also discusses advancements like pedestrian detection systems, Intelligent Vision for Automobiles at Night (IVAN), and true color night vision using liquid crystal filter intensified cameras.
The document discusses night vision systems in automobiles. It describes two types of night vision systems: active illumination and thermal imaging. Active illumination uses infrared technology to detect pedestrians up to four times farther than headlights, while thermal imaging uses heat sensing to see in complete darkness. Night vision systems have advantages like reducing accidents and providing a greater viewing range, though they also have disadvantages such as higher costs. Major automakers like Audi, BMW, and Mercedes-Benz have incorporated night vision systems into some of their vehicles.
This document summarizes trends in ubiquitous multimedia computing. It discusses concepts like ubiquitous computing, ambient intelligence, and the internet of things. It outlines trends in areas like m-health, ubiquitous multimedia services, context awareness, and security issues. It also summarizes two European ICT projects focused on elderly care and alarm handling. Finally, it discusses the speaker's experiences with ubiquitous multimedia projects and their plans to apply that experience to solutions for e-health, e-learning, and e-management.
These are the slides of the tutorial presented at the 17th International Conference on Business Process Management (BPM 2019), Wien, Austria, 2--6 September 2019.
Talk given by Francesco Leotta, Andrea Marrella and Massimo Mecella
Cite them as:
Leotta F., Marrella A., Mecella M. (2019) IoT for BPMers. Challenges, Case Studies and Successful Applications. In: Hildebrandt T., van Dongen B., Röglinger M., Mendling J. (eds) Business Process Management. BPM 2019. Lecture Notes in Computer Science, vol 11675. Springer, Cham.
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to human presence. AmI aims to support users by having devices work together to automatically meet users' needs through context awareness and personalized interactions. Key technologies that enable AmI include ubiquitous computing, ubiquitous communication, and intelligent user interfaces to create a seamless experience between users and their digitally augmented surroundings. While AmI offers benefits like increased convenience, control, and efficiency, open challenges remain regarding privacy, security, complexity of modeling multiple users, and ensuring reliability of networked devices.
The idea is to create a social network of sensors in which various sensors integrated to intel Galileo will send the data to the user.
Nowadays using various social networking sites like Facebook, twitter, google+ has become too main stream.
Now the idea is to integrate our home status to these social networking sites that is, creating a “Galileo link”.
Home status will be comprised of various readings taken by the sensors like IR sensor, LDR, temperature sensor.
Sensors send data to intel Galileo then Galileo acts as a client and sends that data to the social networking site.
For example in Facebook an account is created and that account is registered on Facebook developer. As soon as the account is registered on Facebook developer it creates an access token.
Access token is then included in python script running in the Galileo device.
Hence our data can be seen in our news feed and we just have to add the registered account as our friend
- The ELLIOT project aims to develop an experiential platform for users and citizens to co-create and experiment with Internet of Things (IoT) applications and services using a living lab approach.
- The platform will implement Knowledge-Social-Business (KSB) experience models to explore socially-enabled IoT technologies and their impact.
- Three living labs will test the platform in logistics, well-being, and environmental sectors to validate the models and co-creation techniques.
Presentation at the Workshop on Expectations for AAL and enhanced living environments in 2025/2030, by Francisco Florez-Revuelta, Susanna Spinsante, and Nuno Garcia, all members of the Cost Action IC1303 - AAPELE - Algorithms, Architectures and Platforms for Enhanced Living Environments
Human Computer Interaction: Trends and ChallengesIRJET Journal
The document provides an overview of human-computer interaction (HCI), including definitions, recent advances, trends and challenges. HCI is the study of how humans interact with computers and how to design interfaces for successful human-computer interaction. It is an interdisciplinary field that incorporates areas like computer science, psychology, anthropology, sociology and ergonomics. The document discusses applications of HCI in education, healthcare and everyday life. Advances in technology have led to new interaction methods like wearables, virtual reality and ubiquitous computing.
Ubiquitous computing will surround users
with a comfortable and convenient information environment and a smart
space that merges physical and computational infrastructures into an integrated
habitat. This habitat will feature a proliferation of hundreds or thousands of
computing devices and sensors that will provide new functionality, offer specialized
services, and boost productivity
and interaction among the devices and
the
users.
This document discusses enabling technologies and architectures for an Internet of Things (IoT) system to support smart cities. It provides an overview of services that could be enabled by an urban IoT, including improved management of transportation, lighting, public spaces, cultural heritage sites, waste collection and more. The document also presents the Padova Smart City project, which deployed an IoT network in Padua, Italy to collect various data for city administration and provide services to citizens.
This document provides an outline and introduction for a discussion on the Future Internet. It discusses how the Internet has become integral to modern life but was originally designed in a different technological era. It questions if the TCP/IP stack still adequately meets today's needs. The scope of a Future Internet is debated as either a new network or a broader converged infrastructure. Key topics covered include substrate resources and integration with software, software-defined networking, information and mobility challenges, and ensuring simplicity, sustainability and evolvability.
The Five forces that shape StrategyRivalry among existing cocarmanl5wisc
The Five forces that shape Strategy
Rivalry among existing competitors
Threat of new entrants
Bargaining power of supplies
Bargaining power of buyers
Threat of substitute products or services
Emerging and Converging
Technologies
Chapter 12 examines ethical aspects of three key
emerging/converging technologies:
ambient intelligence (AmI),
nanocomputing,
autonomous machines (AMs).
This chapter also examines issues in the emerg-
ing field of machine ethics, and it describes a
“dynamic” ethical framework for addressing chal-
lenges likely to arise from emerging technologies.
Converging Technologies and
Technological Convergence
Before examining specific emerging and
converging technologies, we first consider
what is meant by the concept of
“technological convergence.”
Howard Rheingold (1992) notes that
technological convergence occurs when
unrelated technologies or technological paths
intersect or “converge unexpectedly” to create an
entirely new field.
Technological Convergence
(Continued)
We should note that convergence in the context of
cybertechnology is by no means new or even recent,
but it has been ongoing since this technology’s
inception.
For example, in Chapter 1 we saw that early network
technologies resulted from the convergence of
computing and communications technologies in the
late 1960s and early 1970s.
Howard Rheingold notes that virtual-reality (VR)
technology (examined in Chapter 11) resulted from
the convergence of video technology and computer
hardware in the 1980s.
Converging Technologies and
Pervasive Computing
Currently, cybertechnology is converging with
non-cybertechnologies at an unprecedented
pace.
For example, cyber-specific technologies are
converging with non-cybertechnologies, such as
biotechnology and nanotechnology.
Cybertechnology is also becoming pervasive and
ubiquitous as computing devices now permeate
both our public and private spaces (in connection
with ambient-intelligence-related technologies).
1. Ambient Intelligence (AmI)
Ambient Intelligence (AmI) is typically defined as a
technology that
enables people to live and work in environments
that respond to them in “intelligent ways” (Aarts
and Marzano, 2003; Brey, 2005; and Weber et al.,
2005).
Review the example in the textbook of the
(hypothetical) “intelligent home,” which incoprpoates
key aspects of (and is made possible by) AmI.
Also review Scenario 1-1 in the textbook, which
illustrates an instance of the Internet of Tings (IoT)
and which is made possible, in large part, by AmI.
AmI (Continued)
AmI has benefited from, and has been made
possible by, developments in the field of arti-
ficial intelligence (AI), described in Chap. 11.
AmI has also benefited from the convergence
of three key technological components, which
underlie it:
1) pervasive computing,
2) ubiquitous communication, ...
The document summarizes the ELLIOT project, which aims to develop an experiential Internet of Things platform involving users. The project will study the impact of IoT through open innovation and living labs. It will explore user co-creation techniques, and experiment with three use cases in logistics, well-being, and environment across three European living labs. The results will be disseminated through the living labs networks and multipliers to support wider adoption of IoT.
This document discusses the application of cloud computing in smart cities. It first defines cloud computing and smart cities. Cloud computing provides on-demand access to shared computing resources, while smart cities aim to create sustainable economic development and high quality of life through technology and infrastructure. The document argues that cloud computing is a key pillar and important for achieving the goals of smart cities, as it provides the necessary infrastructure. It then outlines Dubai's vision for smart cities and discusses some of the research questions that will be explored, such as the benefits of cloud computing and security concerns.
The document summarizes the ARTEMIS Spring Event 2013 in Brussels. It discusses the role of ARTEMIS in representing industry and funding collaborative research projects. Projects may receive between 2.5-59 million Euros and involve partners from 8-56 countries. Key topics discussed include smart systems, embedded systems, Internet of Things, eHealth and more. Success stories were highlighted from projects in areas like phone connectivity. Presentations were given on initiatives like Arrowhead and CESAR for safety-critical systems. The event emphasized the importance of communication, collaboration and building a sustainable innovation ecosystem through ARTEMIS funding.
IRJET- Internet of Things Technologies for Future of Smart Cities: Artificial...IRJET Journal
This document discusses the role of Internet of Things (IoT) technologies in enabling smart cities. It describes how IoT allows objects to be connected to the internet and exchange data. This data can then be analyzed to improve services and efficiency in areas like transportation, waste management, and environmental monitoring. The document also outlines some challenges to the large-scale adoption of IoT in cities, such as security, lack of standards, and ensuring real-time solutions. It argues that combining IoT with artificial intelligence can help address issues like analyzing large volumes of data and automatically adjusting systems in response.
Cross-features & normative assets of Smart cities & Industry 4.0Mokhtar Ben Henda
The document discusses emerging technologies related to smart cities and Industry 4.0. It presents conceptual frameworks that outline the generation of intelligent systems, from the intelligent web to smart cities, factories, and society. Key concepts discussed include the evolution of the web, industry revolutions, and smart city generations. Artificial intelligence pedigrees such as algorithms and the Internet of Things are described as enabling intelligence across systems. Standards and standardization bodies for smart cities and Industry 4.0 are also summarized.
Intervención Olavi Luotonen. Comisión europea. Scientific Officer, New Infrastucture Paradigms and Experimental Facilities en las Primeras Jornadas de Centros de Conocimiento. Citilab Cornellà #citilab #joceco
The ELLIOT project aims to develop an experiential Internet of Things platform involving users and citizens. It will define knowledge, social, and business experience models for IoT. An experiential platform will implement these models to explore socially-enabled IoT applications and services. Three use cases will test the platform in logistics, well-being, and environmental sectors. The goal is to increase adoption of IoT in Europe through open innovation and a living lab approach.
The document discusses smart cities, defining them as cities that use information and communication technologies to be more efficient, manage resources better, and improve citizens' quality of life. It describes key factors in smart city development like new technologies, open innovation, and technical architecture. It also outlines examples of smart city initiatives and applications around the world and how 5G can further enable smart cities.
Keynote presented at the Arab ICT 2024 conference in Bahrein from 27 to 28 of February, 2024, with title "Engineering Education in the time of the Internet of Things:
Ethics and Sustainability" showing technical and Industry 4.0 activities to be considered under the filter of the Ethical activity of engineering, Sustainability and Circular Economy, and showing information about ECoVEM project and IEEE/IEEE EdSoc - Bahrain Society of Engineers
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seminar report on ambient intelligent
1. AAmmbbiieenntt IInntteelllliiggeennccee ((AAmmII))
SEMINAR REPORT
2015-2016
In partial fulfillment of Third year
In
COMPUTER SCIENCE
SUBMITTED BY
ANKITA
SRIVASTAVA
DEPARTMENT OF COMPUTER SCIENCE
VIVEKANANDA COLLEGE OF TECHNOLOGY AND
MANAGEMENT
2. VIVEKANANDA COLLEGE OF TECHNOLOGY
AND MANAGEMENT
DEPARTMENT OF COMPUTER SCIENCE
CCEERRTTIIFFIICCAATTEE
This is to certify that the seminar report entitled “AAmmbbiieenntt IInntteelllliiggeennccee ((AAmmII))”” is being
submitted by AAnnkkiittaa SSrriivvaassttaavvaa in partial fulfillment of Third Year in Computer
Science is a bonafide record of the seminar presented by her.
Mr. Ranjeet Rai Prof. Mr. Lalit Mohan Gupta
Lecturer HOD
Dept. of Computer Science Dept. of Computer Science
3. AACCKKNNOOWWLLEEDDGGEEMMEENNTT
First of all let me thank our HOD Prof: Mr. Lalit Mohan Gupta , Dept. of
Computer Science, VCTM who provided with the necessary facilities and advice. I am
also thankful to Mr. Ranjeet Rai , Lecturer, Dept of Computer Science, VCTM for
his valuable suggestions and support for the completion of this seminar. With great
pleasure I remember Miss. Aayushi Saxena, Lecturer, Dept. of Computer
Science,VCTM for her sincere guidance. Also I am thankful to all of my teaching and
non-teaching staff in the department and my friends for extending their warm kindness
and help.
I would like to thank my parents without their blessings and support I would not
have been able to accomplish my goal. I also extend my thanks to all my well wishers.
Finally, I thank the almighty for giving the guidance and blessings.
4. ABSTRACT
Philips Research introduced Ambient Intelligence(AmI) in the year 1998. In 2001,
AmI was taken up by The European Commission’s Information Society Technologies
Advisory Group (ISTAG). In computing, AmI refers to electronic environments that are
sensitive and responsive to the presence of people. Ambient intelligence is a vision on the
future of consumer electronics, telecommunications and computing for the time frame
2010–2020.
The development of ambient intelligence applications that effectively adapt to the
needs of the users and environments requires the presence of planning mechanisms for
goal-oriented behavior. A planning system for AmI applications is based on the
hierarchical task network (HTN) approach and is called distributed hierarchical task
network (D-HTN). D-HTN is able to find courses of actions to address given goals.
The application areas of AmI include health-related applications, public
transportation sector, education services etc. This seminar aims to give an insight into
ambient intelligence technology and a planner for AmI applications.
Keywords: Ambient intelligence, context awareness, sensors, planning, multiagents
5. CONTENTS
Se.no
1
Title
Introduction to AmI
Page no.
1
2 History 2
3 AmI
3.1 Vision 3
3.2 Semantics 4
3.3 Key concepts 4
3.4 Key Technologies 5
4 Social and political aspects of AmI 6
5 Relation between AmI and other Computer Science areas 7
6 5Ws and 3Ps of AmI 9
7 Architecture of AmI system 11
8 Components of AmI system 12
9 AmI System - Planning
9.1 Features of AmI systems 15
9.2 Why planning needed for AmI
Applications?
15
9.3 Planning and D-HTN planner 16
9.4 D-HTN algorithms 18
10 Application areas 20
11 Challenges 21
12 Conclusion 23
13 References 24
6. Dept. of Computer Science, Vivekananda College Of Technology And Management
~ 1 ~
1. Introduction
Ambient Intelligence (AmI) is a new paradigm in Information Technology that has
potential for great impact in the future. The vision of AmI is that the people will be
surrounded by intelligent objects that can sense the context and respond according to the
desire of the people. AmI is a multidisciplinary topic, since it combines the features of many
of the areas in Computer Science.
In the last five years, we have seen significant advances in three promising technology
areas: virtual environments, in which 3D displays and interaction devices immerse the user in
a synthesized world, mobile communication and sensors, in which increasingly small and
inexpensive terminals and wireless networking allow users to roam the real world without
being limited to stationary machines. The merging of these areas allows the emergence of a
new vision: the Ambient Intelligence (AmI).
AmI refers to a digital environment that proactively, but sensibly, supports people in
their everyday lives. It will make the feeling that the people live with technology. It is aligned
with the concept of ‘disappearing computer’, since the AmI environment make the
technology invisible. As the devices grow smaller, more connected and more integrated into
our environment, the technology disappears into our surroundings.
“The most profound technologies are those that disappear. They weave themselves into the
fabric of everyday life until they are indistinguishable fromit.” M. Weiser
The basic idea behind AmI is that by enriching an environment with technology
(mainly sensors and devices interconnected through a network), a system can be built to take
decisions to benefit the users of that environment based on real-time information gathered
and historical data accumulated.
An important aspect of AmI has to do with interaction. On one side there is a
motivation to reduce the human-computer interaction as the system is supposed to use its
intelligence to infer situations and user needs from the recorded activities, as if a passive
human assistant was observing activities unfold with the expectation to help when (and only
if) required. On the other side, a diversity of users may need or voluntarily seek direct
interaction with the system to indicate preferences and needs. The entire environment around
us, homes and offices, cars and cities, will collectively develop a pervasive network of
intelligent devices that will cooperatively gather, process and transport information.
7. Dept. of Computer Science, Vivekananda College Of Technology And Management
~ 2 ~
2. History
In 1998, the board of management of Philips commissioned a series of presentations
and internal workshops, organized by Eli Zelkha and Brian Epstein of Palo Alto Ventures
(who coined the name 'Ambient Intelligence') to investigate different scenarios that would
transform the high-volume consumer electronic industry from the current “fragmented with
features” world into a world in 2020 where user-friendly devices support ubiquitous
information, communication and entertainment. In the years after, these developments grew
more mature. In 1999, Philips joined the Oxygen alliance, an international consortium of
industrial partners within the context of the MIT Oxygen project, aimed at developing
technology for the computer of the 21st century. In 2000, plans were made to construct a
feasibility and usability facility dedicated to Ambient Intelligence. This HomeLab officially
opened on 24 April 2002.
Along with the development of the vision at Philips, a number of parallel initiatives
started to explore ambient intelligence in more detail. In 2001, the concept of Ambient
Intelligence (AmI) was taken up by European Commission’s Information Society
Technologies Advisory Group (ISTAG). The term Ambient Intelligence is defined by ISTAG
as "the convergence of ubiquitous computing, ubiquitous communication, and interfaces
adapting to the user". Following the advice of the ISTAG, the European Commission used
the vision for the launch of their sixth framework (FP5) in Information, Society and
Technology (IST), with a subsidiary budget of 3.7 billion euros. EU FP6: driving vision in a
3.7BEuro 5 year ICT (Information and Communication Technologies) research program
(2002-2006). EU FP7 (9.1 BEuro for ICT): acknowledged (mainstreamed) but more
focused, systemic and transformational (2007-2012)
The European Commission played a crucial role in the further development of the
AmI vision. As a result of many initiatives the AmI vision gained traction. Fraunhofer
Society started several activities in a variety of domains including multimedia, Microsystems
design and augmented spaces. MIT started an AmI research group at their Media Lab.
Several more research projects started in a variety of countries such as USA, Canada, Spain,
France and the Netherlands. In 2004, the first European symposium on AmI (EUSAI) was
held and many other conferences have been held that address special topics in AmI.
8. Dept. of Computer Science, Vivekananda College Of Technology And Management
~ 3 ~
3. AmI: Vision, semantics, key concepts and key technologies
3.1 Vision
Ambient Intelligence (AmI) will radically change how people interact with
technology. In AmI, people will be surrounded by a multitude of interconnected embedded
systems. These devices will be able to locate and recognize objects and people, as well as
people’s intentions.
The vision of AmI is characterized by two key features: intelligence and embedding.
The feature of “intelligence” refers to the fact that the digital environment is able to analyze
the context, adapt itself to the people and objects that reside in it, learn from their behavior,
and eventually recognize as well as express emotion. The feature of “embedding” means that
miniaturized devices will increasingly become part of the invisible background of peoples’
activities, and that social interaction and functionality will move to the foreground.
it.”
According to the AmI vision,” people will not just use technology: they will live with
Hence, AmI is :-
vision for our environment
‘smart electronic environment that is sensitive and responsive to the presence of
people’
‘Electronics embedded in every-day objects; natural interaction; context aware;
Personalized ; adaptive; responsive; pro-active.’
Enhancing productivity, healthcare, well-being, expressiveness, creativity.
9. Dept. of Computer Science, Vivekananda College Of Technology And Management
~ 4 ~
3.2 Semantics
Ambient Intelligence refers to electronic environments that are sensitive and
responsive to the presence of people
The term ambient refers to the environment and reflects the need for typical
requirements such as distribution, ubiquity, and transparency.
Distribution refers to noncentral systems control and computation.
Ubiquity means the embedding is present everywhere.
Transparency indicates that the surrounding systems are invisible and
unobtrusive.
The term Intelligence means the digital surroundings exhibit specific forms of social
interaction. In other words, an environment must recognize the people that live in it, adapt
itself to them, learn from their behavior, and possibly show emotion. In short, the
environment should be intelligent.
3.3 Key Concepts
AmI provides ‘Smarter’ living. ie. AmI is a technology for people. To refine the
notion of ambient intelligence, Marzano and Emile Aarts formulated the following five key
concepts of AmI:
Embedded. Many networked devices are integrated into the environment.
Context aware. The system can recognize you and your situational context.
Personalized. The system can tailor itself to meet your needs.
s
Adaptive. It can change in response to you.
Anticipatory. The system anticipates your desires without conscious
mediation.
The first two elements relate to the integration of hardware devices into the
environment, and refer to embedded systems in general. Embedded systems play an
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important role in the realization of ambient intelligence because they account for the
embedding of electronic devices into people’s surroundings.
The three other key elements of ambient intelligence concern the adjustment of
electronic systems in response to users. These system adjustments occur on different time
scales. Personalization refers to those occurring on a short time scale (for example, installing
personalized settings). Adaptation involves adjustments to changing user behaviors detected
by monitoring the user over longer periods of time. Ultimately, when the system gets to know
the user so well that it can detect behavioral patterns, adjustments are possible over a very
long period of time.
3.4 Key Technologies
The benefit of an AmI system is measured by how much can give to people while
minimizing explicit interaction. The aim is to enrich specific places (a room, a building, a car,
a street) with computing facilities which can react to people’s needs and provide assistance.
In order for AmI to become a reality a number of key technologies are required:
Unobtrusive hardware (Miniaturisation, Nanotechnology, smart devices,
sensors etc.)
Seamless mobile/fixed communication and computing infrastructure
(interoperability, wired and wireless networks, service-oriented architecture,
semantic web etc.)
Dynamic and massively distributed device networks, which are easy to control
and program (e.g. service discovery, auto-configuration, end-user
programmable devices and systems etc.).
Human-centric computer interfaces (intelligent agents, multimodal interaction,
context awareness etc.)
Dependable and secure systems and devices (self-testing and self repairing
software, privacy ensuring technology etc.)
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4. The social and political aspects of ambient intelligence
Ambient intelligence is more than just a question of embedding technology into objects.
It involves human culture in its broadest sense: universal desires; complex social
relationships; diverse value systems; individual likes and dislikes; the sustainability of
economic and natural ecosystems; and codes of ethics, conduct, and communication, both in
civil society and in business. This is also what makes ambient intelligence markedly different
from other concepts such as pervasive computing and ubiquitous computing
In AmI, technology lives with the people, hence AmI has both social and political
influences. The current phase of AmI/pervasive computing, in which computers are already
being embedded in many devices, has begun to affect our everyday lives in ways we do not
even notice.
ISTAG identified a series of necessary characteristics that will permit the eventual
societal acceptance of AmI.
AmI should:
facilitate human contact.
be orientated towards community and cultural enhancement.
help to build knowledge and skills for work, better quality of work, citizenship and
consumer choice.
inspire trust and confidence.
be consistent with long term sustainability - personal, societal and environmental -
and with life-long learning.
be made easy to live with and controllable by ordinary people.
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5. Relationbetween AmI and other Computer Science areas
Fig 1
Networks, Sensors, Human Computer Interfaces (HCI), Pervasive Ubiquitous
Computing and Artificial Intelligence (AI) are all relevant and interrelated but none of them
conceptually covers the full scope of AmI. Ambient Intelligence puts together all these
resources to provide flexible and intelligent services to users acting in their environments.
Ambient intelligence involves the convergence of several computing areas. It is a
multi-disciplinary approach which aims to enhance the way environments and people interact
with each other. The ultimate goal of the area is to make the places we live and work in more
beneficial to us.
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6. 5Ws and 3Ps of AmI
Of Importance for AmI are the “5Ws” (Who, Where, What, When and Why) principle
of design:
Who: the identification of a user of the system and the role that user plays within the system
in relation to other users. This can be extended to identifying important elements like pets,
robots and objects of interest within the environment.
Where: the tracking of the location where a user or an object is geographically located at
each moment during the system operation. This can demand a mix of technologies, for
example technology that may work well indoors may be useless outdoors and vice -versa.
When: the association of activities with time is required to build a realistic picture of a
system’s dynamic. For example, users, pets and robots living in a house will change location
often change location and knowing when those changes happened and for how long they
lasted are fundamental to the understanding of how an environment is evolving.
What: the recognition of activities and tasks users are performing is fundamental in order to
provide appropriate help if required. The multiplicity of possible scenarios that can follow an
action makes this very difficult. Spatial and temporal awareness help to achieve task
awareness.
Why: the capability to infer and understand intentions and goals behind activities is one of
the hardest challenges in the area but a fundamental one which allows the system to
anticipate needs and serve users in a sensible way
There seems to be a growing consensus that achieving sustainability requires a good
balance between three factors, sometimes referred to as the three P’s: people, planet, and
profit.
People: Humans exploit everything around them to improve their lives and expand the ir
powers. They want to acquire everything with minimum effort and maximum comfort. This
desire, to have devices that amplify human powers without hindering or cluttering their lives
is what drives the increasing miniaturization of devices. Many devices have already made the
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transition from big static objects to small objects that people can carry around on their bodies.
Clocks are now wristwatches, and more recently phones and audio systems have reached the
stage of becoming worn on the body. This instinct to find greater comfort, power, knowledge,
and freedom has been the main driving force behind technological innovation.
Ambient intelligence intends to improve the quality of people’s lives. Not everything
that’s possible with technology is actually desirable. Therefore, it’s crucial that people make
the right choices with ambient intelligence. This is only possible if people agree on what
quality of life and what sort of world they would like to see develop.
Planet: AmI has a great contribution to the planet. AmI provides better care for the
environment. Numerous novel ecological developments are possible by integrating smart
electronics into the environment. They aid in checking pollution and checking uncontrolled
dumping of waste products. There are also techniques for determining energy wastage and
reduce needless consumption.
Profit: Ambient Intelligence describes a new economy called “experience economy”. It is
positioned as the fourth major wave following the classic economies of commodity, goods,
and service. People are willing to spend money for getting better experience. Recollection of
a personal event might just bring back that good old feeling.
Virtual worlds in an ambient-intelligent environment might support such events.
There are many other applications, such as ambient lighting, ambient sounds and poetic
interfaces which all could bring good feel to people. A salient property of an experience is
that it can feel real, whether it has been generated by a real or a virtual cause; what counts is
the belly feeling.
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7. Architecture of AmI system
Fig 2
Sensors bring data to the system. The data collected is transmitted by the network and
pre-processed by the middleware, which collates and harmonizes data from different devices.
In order to make decision-making easier and more beneficial to the occupants of the
environment the system will have a higher level layer of reasoning which will accomplish
diagnosis and advise or assist humans with responsibility for intervention.
Elements that may be included in the high level ‘Decision Making’ process are a
‘Knowledge Repository’ where the events are collected and an ‘AI Reasoner’ which will
apply for example spatial-temporal reasoning to take decisions. For example, a decision
could be to perform some action in the environment and this is enabled via ‘Actuators’.
Knowledge discovery and machine learning techniques learn from the acquired information in
order to update the AI Reasoner in the light of experience of the
system.
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8. Components of AmI system
AmI system is comprised of three main components: ubiquitous computing,
ubiquitous communication, and user adaptive interfaces.
Ubiquitous computing means any computing device, while moving with you, can
build incrementally dynamic models of its various environments and configure its services
accordingly. The devices will be able to either "remember" past environments they operated
in, or proactively build up services in new environments. Ubiquitous computing" refers to
omnipresent computers that serve people in their everyday lives at home and at work,
functioning invisibly and unobtrusively in the background and freeing people to a large
extent from tedious routine tasks. This includes pen-based technology, hand-held or portable
devices, large-scale interactive screens, wireless networking infrastructure, and voice or
vision technology.
Ubiquitous communication: Ubiquitous computing is the introduction and
expansion of wireless network technology, which enables flexible communication between
interlinked devices that can be stationed in various locations or can even be portable.
Wireless LAN (W-LAN) applications per standard IEEE 802.11b offer high-speed
transfer rates of 11 Kbits/s and can be extended over entire office buildings and
production areas by using several access points. While W-LAN is considerably cheaper than a
traditional stationary LAN, it is often still too costly to be included in small individual devices
Bluetooth technology is used in today's handheld applications like cellular phones or
personal digital assistants (PDAs) per standard IEEE 802.15 to allow wireless connection
within a personal area network (W-PAN). While the cost of Bluetooth equipment is
significantly lower than the cost of W-LAN, the transmission range of up to 10 meters and
the data transfer rate of less than 720 Kbit/s are inferior. New Bluetooth versions are
currently under development that attempt to eliminate the latter drawback. V1.2 allows rates
of up to 3 Mbit/s, V2.0 of up to 12 Mbit/s
High rate W-PANs per standard IEEE 802.15 TG3, launched in 2003, use higher
power devices (8 dBm) than regular Bluetooth equipment (0 dBm) to transmit data at a rate
of up to 55 Mbit/s and over a range of up to 55 m. This technology is, therefore, an attractive
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alternative to W-LAN, especially considering the comparatively lower cost.
Low power W-PANs per standard IEEE 802.15 TG4 are particularly useful for handheld
devices since energy consumption for data transmission purposes, and costs, are extremely
low. The range of operation of up to 75 m is higher than current Bluetooth applications, but
the data transfer rate of 250 Kbit/s is lower.
Wireless body area networks (BANs) interlink various wearable devices, such as
wireless data glasses, earpieces, microphones, and sensors, and can connect them to outside
networks. BANs are often used for medical applications but also in work-related fields, for
example, to provide production operators with instructions that are adapted to the respective
work situation. BANs usually consist of a central network unit, which connects the devices
and which can provide an interface to further networks outside the BAN, for example, via
Bluetooth. Advantages of BANs versus W-PANs are the short range and the resulting lower
risk of tapping and interference, as well as low frequency operation, which leads to lower
system complexity. Technologies used for wireless BANs include magnetic, capacitive, low-
power far-field and infrared connections, while non-wireless BANs use wires or conductive
fabrics.
Radio frequency identification (RFID) encompasses wireless identification through radio
transmission. RFID systems comprise a read/write station and active (with own power
source) or passive (power supplied by the read/write station) transponders (transmitter /
responder), and can be used in a variety of applications. Traditional examples include
protection against theft, access control, and billing. The range of possible applications is
much greater: RFID systems can be used for material tracking in manufacturing and logistics,
for cash register applications in stores as an alternative to barcode scanning, or for localizing
items or persons.
Network administration is facilitated by minimizing the effort required for setting up
networks. The introduction of mobile ad hoc networks (MANETs) is an important step in this
direction. A MANET uses the wireless technologies described in the list above but is more
flexible than conventional networks, since the routers are included in the mobile nodes
instead of being fixed and have the ability to configure themselves. This provides the network
with great flexibility due to its ability to adapt automatically to a changing network
environment.
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User adaptive interfaces
User adaptive interfaces, the third integral part of AmI, are also referred to as
"Intelligent social user interfaces" (ISUIs). These interfaces go beyond the traditional
keyboard and mouse to improve human interaction with technology by making it more
intuitive, efficient, and secure. They allow the computer to know and sense far more about a
person, the situation the person is in, the environment, and related objects than traditional
interfaces can.
ISUIs encompass interfaces that create a perceptive computer environment rather than
one that relies solely on active and comprehensive user input. ISUIs can be grouped into five
categories:
Visual recognition (e.g. face, 3D gesture, and location) and output
Sound recognition (e.g. speech, melody) and output
Scent recognition and output
Tactile recognition and output
Other sensor technologies
The key to an ISUI is the ease of use, in this case the ability to personalize and
adapt automatically to particular user behavior patterns (profiling) and different situations
(context awareness) by means of intelligent algorithms. In many cases, different ISUIs, such
as voice recognition and touch screen, are combined to form multi-modal interfaces. ISUIs
make network usage more secure as the interfaces can identify users automatically by, for
example, face or voice recognition instead of requesting a password.
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9. AmI system - Planning
9.1 Features of AmI Systems
AmI system is composed of numerous agents. Agents are smart devices, which are
fixed or mobile devices. Agents form part of AmI system either permanently or temporarily.
For example a person comes with a mobile phone into a room equipped with AmI system.
The cell phone, when properly connected to the network of other devices, is temporarily part
of the system. After the person leaves the room is disconnected.
Features of AmI system are:-
• Feature 1: Some agents could take no responsibility in building the plan because of their
limitations in processing and communication. This pushes toward the centralized
planning process.
• Feature 2: The skills to perceive the environment and to perform the actions are
distributed over the agents. This pulls toward the distributed planning process.
9.2 Why Planning needed for AmI applications?
The development of ambient intelligence (AmI) applications that effectively adapt to
the needs of the users and environments requires the presence of planning mechanisms for
goal-oriented behavior. An AmI system that plans is able to find a course of action that, when
executed, achieves a desired effect. The planning system builds plans according to the
capabilities of available devices that perform actions to satisfy the user’s need.
A planning system for AmI applications proposed by Francesco Amigoni, Associate
Member, IEEE and Nicola Gatti, Member, IEEE, is based on the hierarchical task network
(HTN) approach and it is called distributed hierarchical task network (D-HTN). D-HTN
planner can support both the features of AmI systems; i.e centralized as well as distributed
features.
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9.3 Planning and D-HTN planner
A planning algorithm has three inputs:
– a description of the world,
– a description of the goal,and
– a description of the capabilities in form of possible actions that can be
performed.
The planning algorithm’s output is a sequence of actions such that, when they are executed in
a domain satisfying the initial state description, the goal will be achieved. AmI system need a
centralized planner that manages distributed capabilities. A distributed HTN approach
appears appropriate for AmI applications because it naturally supports heterogeneous agents
and knowledge exchange among them.
D-HTN planners are based on the concept of task network that is represented as
[(n1:1 ),(n2:2 ),……(nm: m), ]
where
i are tasks, either primitive (that can be directly executed by an agent) or
nonprimitive (that must be further decomposed);
ni are labels to distinguish different occurrences of the same task;
is a Boolean formula representing the constraints on the tasks, such as variable
bindings constraints [e.g.,v=v’], ordering constraints [e.g., (n<n’), with the meaning
that n must be executed before n’], and state constraints [e.g.,(n,l,n’) , with the
meaning that l must be true immediately after n, immediately before n’, and in all
states between n and n’ ].
A task network can be represented by a graph. For example, the task network:
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Fig 3
The intended meaning of this graph is that, in order to request a good g1 by e-mail, we
first have to create the RequestText t1 and look for the EmailAddress a1 of a supplier of g1,
and then we have to SendEmail with content t1 to a1.
Functions of Agents and Planner in D-HTN planner:-
• AGENT:
– Each agent keeps a local data structure called plan library, which stores all the
decompositions it knows.
– The decompositions in the plan library of an agent have been defined by the
designer during the installation of the agent and are peculiar for each agent
• PLANNER:
– generate a plan, the other agents are only requested to communicate
decompositions .
By means of a communication mechanism based on message passing,
– the planner can ask the currently connected agents to send their available
decompositions for a given task
– the agents can send to the planner the requested decompositions.
D-HTN planning starts with an initial task network D representing the problem (the
goal) and with a set M of methods or decompositions. Each decomposition is a pair
m=(t,d),where t is a non-primitive task and d is a task network; m says that a way to achieve
is to perform the tasks in . Then, D-HTN planning proceeds by finding a non-primitive task
from the current task network D and a method m=(t’,d’), in M such that t’
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unifies with t and by replacing t with d’ in D. When only primitive tasks are left in D, a
plan for the original problem can be found. A plan is a sequence of ground primitive
tasks .This pure HTN planning process can be refined to make it more efficient by
introducing backtracking, critic functions, and other technicalities.
Each decomposition has associated three numerical indexes that are associated to:-
– Performance -measures the expected effectiveness of the decomposition
– Cost- measures the expected resource consumption for performing the tasks in
the decomposition
– Probability of success - measures the expected likeliness that no error occurs
9.4 D-HTN Algorithms
D-HTN is composed of a set of distributed algorithms that are executed concurrently
by the planner and by the agents. Algorithm 1 presents an overview of the D-HTN algorithm
executed by the planning agent. The main data structure to represent the plan that is being
formed is a task network D. D is initialized with the initial task to be solved (i.e., the goal to
be reached). The D-HTN planner produces a final plan D composed only of primitive tasks
that can be executed by the agents. M(t) denotes the decomposition set.
Algorithm 1 D-HTN algorithm for the planner
1: D = initial task
2: while D contains non-primitive tasks do
a) choose a non-primitive task t from D
b) populate M(t), by requesting the currently connected agents to send
the decompositions m = (t’, d’) such that t’ unifies with t and by
collecting these decompositions
c) choose a decomposition m = (t’,d’) from M(t)
d) if t is primitive for the agent a proposing m then
bind a to t and remove t from the non-primitive tasks
3:end while
e) end if
f) replace t with d’ in D
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Algorithm 2 D-HTN algorithm for the agents
1: while the agent is active do
a) wait for a message from the planner
b) if the message is a request of decompositions for a non-primitive task t
then
send to the planner the decompositions m = (t’, d’) in the
plan library such that t’ unifies with t
c) end if
2: end while
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10. Application areas
Ambient Intelligence possesses applications in many areas. Some of them are listed below:-
• Health-related applications. Hospitals can increase the efficiency of their services by
monitoring patients’ health and progress by performing automatic analysis of activities in
their rooms. They can also increase safety by, for example, only allowing authorized
personnel and patients to have access to specific areas and devices.
• Public transportation sector. Public transport can benefit from extra technology including
satellite services, GPS-based spatial location, vehicle identification, image processing and
other technologies to make transport more fluent and hence more efficient and safe.
• Education services. Education-related institutions may use technology to track students
progression on their tasks, frequency of attendance to specific places and health related issues
like advising on their diet regarding their habits and the class of intakes they opted for.
• Emergency services. Safety-related services like fire brigades can improve the reaction to a
hazard by locating the place more efficiently and also by preparing the way to reach the place
in connection with street services. The prison service can also quickly locate a place where a
hazard is occurring or is likely to occur and prepare better access to it for security personnel.
• Production-oriented places. Production-centred places like factories can self-organize
according to the production/demand ratio of the goods produced. This will demand careful
correlation between the collection of data through sensors within the different sections of the
production line and the pool of demands via a diagnostic system which can advice the people
in charge of the system at a decision-making level.
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11. Challenges
Fig 4
The fast penetration of wireless communications has put into evidence the user’s need
to get easily connected anywhere and anytime at an affordable price. On the one hand,
wireless communications clearly proved that the most a technology provides simple access
means, added to freedom of movement and increased security, the most the user is willing to
accept it.
On the other hand, the most a technology is complex and costly, the less the user is
prone to accept it, in spite of possibly large potential advantages, which are generally not
reachable by the average user not interested in spending time and energies in acquiring the
underlying technology fundamentals. As a consequence, the successful systems of the future
will adhere to the paradigm of ”disappearing technologies”, both valid for communications
and computing, and will provide improved ease-of use at the expense of an increased, but
invisible to the user, complexity of the underlying systems and networks necessary to
transport and process the information in the different multimedia forms and usage contexts.
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Ambient Intelligence faces a lot of challenges. Among these are the social implications
of AmI environments, the different potentials of AmI to enrich our lives, aspects of privacy
and trust, characteristics of different AmI interactions, how much intelligence people are
willing to accept, the different dimensions of the term ambient, the design of future
interaction spaces and intelligent artifacts, factors of user experience for implicit interaction,
existing and emerging AmI application areas and scenarios, the connection of AmI concepts
to physical spaces where it happens etc.
• Challenges in Interaction technology
Develop ambient interaction concepts that are truly intelligent, simple,and
intuitive.
Integrate multi-modality with context awareness and intuitive feedback
mechanisms.
Integrate smart media access into surroundings (audio, video, and light).
Develop interaction concepts for novel AmI technologies (photonic textiles, e-
paper, polymer lighting)
• Challenges in Innovation
Build an eco-system that uses co-creation as a model for open innovation.
Involve multiple parties in the user centered design cycle at large.
Concentrate on well-defined business domains (i.e., hospitality, fashion,
furniture, well-being, city beautification).
Develop new business models for AmI innovation
• Challenges in Involvement
Reach out to ordinary people so as to let them participate in the AmI effort.
Involve ordinary people in the user centered design cycle at large.
Let people experience the AmI future and live in it yourselves.
Make AmI part of education.
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12. Conclusion
Ambient Intelligence (AmI) is growing fast as a multi-disciplinary topic of interest
which can allow many areas of research to have a significant beneficial influence into our
society. AmI is a vision on the future of consumer electronics, telecommunications and
computing for the time frame 2010–2020.
Ambient Intelligence envisions a world where people are surrounded by intelligent
and intuitive interfaces embedded in the everyday objects & physical environments around
them. These interfaces recognize and respond to the presence and behaviors of an individual
in a personalized and relevant way.
The new paradigm of ambient intelligence can bring about a revolution in the design,
appearance, and use of electronics in ordinary life. It could support and facilitate simple and
recurrent tasks, but it could also lead to a culture very different from today’s. This new
culture could develop through the expansion of the use media into a world in which physical
and virtual experiences merge to support personal expression, business productivity , and
personal lifestyles.
Technology will not be the limiting factor in realizing ambient intelligence. The
ingredients to let the computer disappear are already available, but the true success of the
paradigm will depend on the ability to develop concepts that allow natural interaction with
digital environments.
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13. References
1. www.comsis.org/pdf.php?id=nst-4604
2. https://en.wikipedia.org/wiki/Ambient_intelligence
3. www.sciencedirect.com/science/article/pii/S157411920900025X
4. www.slideshare.net/nikhilpatteri/ambient-intelligence-28697238
5. Scholarly articles for ambient intelligence technologies
applications and opportunities
6. www.neurovr.org/emerging/book5/01_AMI_Alcaniz.pd
7. www.collegelib.com/t-ambient-intelligence-seminar-report-
abstract.html
8. www.research.microsoft.com/enus/um/people/liuj/publications/ami.p
df
9. AmbientIntelligence:European Conference,AmI2008,Nuremberg,
Germany ...
10.https://books.google.co.in/books?isbn=3642251676