This document discusses a seminar presentation on smart sensors. It provides an introduction to smart sensors, defining them as sensors with integrated electronics that can perform logic functions, two-way communication, and make decisions. It discusses the usefulness of silicon technology in smart sensors and their general architecture. The architecture typically includes elements like a sensing element, amplifier, analog-to-digital converter, memory, and processor. In conclusions, smart sensors provide benefits like reduced costs, remote diagnostics, enhanced applications, improved reliability, and better signal-to-noise ratios compared to traditional sensors.
The document discusses intelligent sensors. It defines intelligent sensors as devices that combine sensing elements with integrated signal processing and microprocessors to enable self-calibration, compensation for drift, computation, and decision-making. Intelligent sensors are described as being able to adapt to changing conditions, sense non-physical quantities, and integrate sensing and computation on a single chip. Applications mentioned include use in intelligent robots, smart fabrics, and advanced driver assistance systems like adaptive cruise control. A specific example of an intelligent tire sensor that detects sidewall forces is provided.
intelligent sensors and sensor networksSurinder Kaur
The document discusses intelligent sensors and sensor networks. It describes using neural networks for decision making and learning in intelligent sensors. Specifically, it discusses using spiking neural networks for human localization based on sensor data from laser range finders and other sensors. It also examines using neural networks like radial basis function networks and multilayer perceptrons for material classification based on sensor readings. Finally, it proposes a universal sensor interface chip that can provide local intelligence to develop various intelligent sensor applications.
This document discusses smart sensors, including their architecture, operation, evolution, and applications. It describes the key components of a smart sensor such as sensing elements, data acquisition systems, programming devices, and communication interfaces. Examples of industrial applications like accelerometers and medical uses for food safety monitoring are also provided. The document traces the evolution of sensors from early generations with little electronics to later smart sensors with integrated computing capabilities.
Sensors detect physical parameters and convert them into electrical signals. Sensors are made of silicon and can measure attributes like temperature, pressure, and speed. Smart sensors contain both sensors and microprocessors, allowing them to process data, communicate, and make decisions. Smart sensors are classified based on the sensor type, technology, components, and network connectivity. They have advantages like reliability, performance, and scalability but also disadvantages like complexity, cost, and needing external calibration.
This document discusses smart sensors and their applications. It notes that smart sensors have minimum interconnecting cables, high reliability, high performance, and are easy to design, use and maintain in small rugged packaging. They also allow for self calibration, communication, computation, and multi-sensing. Some applications mentioned include home security, smart home devices like light bulbs and thermostats, as well as medical sensors like electrocardiogram and blood flow sensors. Wired smart sensors are noted to have higher complexity and cost compared to wireless due to requiring predefined functions and external processors for calibration.
Smart sensors have integrated electronics that allow them to perform logic functions, two-way communication, and make decisions in addition to sensing. A sensor only responds with a low-level output signal, while a smart sensor can amplify and process that signal. Smart sensors typically have components like sensing elements, amplifiers, ADCs, memory, and a processor that allow them to self-calibrate, perform computations, communicate signals, and integrate multiple sensors on a single device. Silicon is a common material used to fabricate miniaturized smart sensors for applications like infrared detection, acceleration measurement, and multisensing integrated chips.
This document discusses a seminar presentation on smart sensors. It provides an introduction to smart sensors, defining them as sensors with integrated electronics that can perform logic functions, two-way communication, and make decisions. It discusses the usefulness of silicon technology in smart sensors and their general architecture. The architecture typically includes elements like a sensing element, amplifier, analog-to-digital converter, memory, and processor. In conclusions, smart sensors provide benefits like reduced costs, remote diagnostics, enhanced applications, improved reliability, and better signal-to-noise ratios compared to traditional sensors.
The document discusses intelligent sensors. It defines intelligent sensors as devices that combine sensing elements with integrated signal processing and microprocessors to enable self-calibration, compensation for drift, computation, and decision-making. Intelligent sensors are described as being able to adapt to changing conditions, sense non-physical quantities, and integrate sensing and computation on a single chip. Applications mentioned include use in intelligent robots, smart fabrics, and advanced driver assistance systems like adaptive cruise control. A specific example of an intelligent tire sensor that detects sidewall forces is provided.
intelligent sensors and sensor networksSurinder Kaur
The document discusses intelligent sensors and sensor networks. It describes using neural networks for decision making and learning in intelligent sensors. Specifically, it discusses using spiking neural networks for human localization based on sensor data from laser range finders and other sensors. It also examines using neural networks like radial basis function networks and multilayer perceptrons for material classification based on sensor readings. Finally, it proposes a universal sensor interface chip that can provide local intelligence to develop various intelligent sensor applications.
This document discusses smart sensors, including their architecture, operation, evolution, and applications. It describes the key components of a smart sensor such as sensing elements, data acquisition systems, programming devices, and communication interfaces. Examples of industrial applications like accelerometers and medical uses for food safety monitoring are also provided. The document traces the evolution of sensors from early generations with little electronics to later smart sensors with integrated computing capabilities.
Sensors detect physical parameters and convert them into electrical signals. Sensors are made of silicon and can measure attributes like temperature, pressure, and speed. Smart sensors contain both sensors and microprocessors, allowing them to process data, communicate, and make decisions. Smart sensors are classified based on the sensor type, technology, components, and network connectivity. They have advantages like reliability, performance, and scalability but also disadvantages like complexity, cost, and needing external calibration.
This document discusses smart sensors and their applications. It notes that smart sensors have minimum interconnecting cables, high reliability, high performance, and are easy to design, use and maintain in small rugged packaging. They also allow for self calibration, communication, computation, and multi-sensing. Some applications mentioned include home security, smart home devices like light bulbs and thermostats, as well as medical sensors like electrocardiogram and blood flow sensors. Wired smart sensors are noted to have higher complexity and cost compared to wireless due to requiring predefined functions and external processors for calibration.
Smart sensors have integrated electronics that allow them to perform logic functions, two-way communication, and make decisions in addition to sensing. A sensor only responds with a low-level output signal, while a smart sensor can amplify and process that signal. Smart sensors typically have components like sensing elements, amplifiers, ADCs, memory, and a processor that allow them to self-calibrate, perform computations, communicate signals, and integrate multiple sensors on a single device. Silicon is a common material used to fabricate miniaturized smart sensors for applications like infrared detection, acceleration measurement, and multisensing integrated chips.
This document discusses smart sensors and the Internet of Things (IoT). It begins with introducing the group members and then outlines topics to be covered such as definitions of smart sensors, their evolution, examples of smart sensors used in IoT applications, and the benefits of a world connected by smart sensors and IoT. Specific types of smart sensors are explained in more detail such as temperature, proximity, pressure, gas, accelerometer, level, motion detection, optical, and gyroscope sensors. Applications of smart sensors for smart cities, utilities, and environmental monitoring are presented. Both pros and cons of smart sensors are listed.
Introduction to IoT
Components of the IoT
IoT Related Statistics
IoT Applications & Use Case Scenarios
Stakeholders of the IoT Applications
Future Directions
Conclusions
Smart IR temperature sensors integrate sensors and circuits to process environmental information without human interference. The new smart sensors are the smallest available, allowing remote control and monitoring from a computer. They work by measuring infrared radiation between 0.7-14 microns, which corresponds to object temperatures. Digital electronics and software provide fast response, remote setup and calibration, and additional functionality. As an example, a smart IR sensor can control a space heater based on the actual temperature of the area being heated rather than just the heater itself, improving safety and efficiency.
This document discusses smart sensors and intelligent sensors. It defines smart sensors as sensors combined with interfacing circuits that allow two-way communication and decision making. Intelligent sensors are an evolution of smart sensors that add data processing, reconfigurability, and the ability to aggregate data from other sensors. The document outlines the architecture and generations of smart sensors from early devices with just sensor elements to current ones with memory, digital intelligence, and integrated analog-to-digital conversion. It provides examples of smart sensor applications and discusses their advantages of being more reliable and scalable while also having higher complexity and cost compared to simple sensors.
The document discusses smart sensors, providing details on their architecture, fabrication, advantages, disadvantages and applications. Some key points:
- Smart sensors integrate a sensor, analog/digital converter, processor and communication interface on a single chip, allowing them to process and communicate sensor data.
- The basic architecture includes a sensing element, amplifier, ADC, memory, processor and communication components. Fabrication uses techniques like micro-machining and bonding.
- Advantages are reduced system load and faster operation. Applications include industrial monitoring, automotive controls, biomedical devices, and smart dust networks of tiny sensors. Disadvantages include higher initial costs and issues with mixing old and new devices.
T-Mobile IoT: The Network Built for Software.
Best in Class Radio
Distributed & Virtualized Core
Advanced Connectivity
Operation System
Connectivity Management (Local and Global)
Device and Data Management
Application Services Layer
IoT Solutions
Packaged Solutions - Off-the-Shelf
Custom Solutions
Industry Focused - Built for Purpose
IoT Innovation
Emerging Tech - Edge, Private Node
Developer Platform
Innovation Hubs - Curiosity Lab, 5G Innovation Lab, Automotive Lab
The document summarizes the key points from a technical seminar on sensor technology presented by Sharenya. It discusses sensor design features and trends in sensor technology, focusing on miniaturization and the increasing use of multi-sensor and wireless systems. The main advantages of sensors are listed as high accuracy, resolution, reliability and energy efficiency. Examples of sensor uses include detection of light, motion, temperature, pressure as well as vehicle speed and environmental molecules.
Smart Sensors: Analyzing Efficiency of Smart Sensors in Public DomainDr. Amarjeet Singh
The paper gives the brief idea of smart sensors,
structure and its application. Smart sensor as compare to
other sensors can sensor anything with the special computing
devices connected with each other in sensor network. These
smart sensors first convert the digital signals to analog signals
and then communicate the message to the device. Now a days
smart sensors are used almost everywhere around us but very
few people know its working and future applications. So here
is a small review on smart sensors. This paper will help you
gain knowledge and its applications in daily life.
Introduction to smart sensors & its’ applicationPranay Mondal
Smart sensors are sensors combined with interfacing electronic circuits that can perform logic functions, two-way communication, and make decisions. They convert physical, biological, or chemical inputs into digital outputs. Smart sensors have evolved from first generation devices with little electronics to now being fully integrated systems-on-chip with sensing, processing, communication and power management. They are used widely in industrial applications like structural health monitoring and geological mapping due to advantages like minimum interconnects, high reliability, and scalability.
Sensors are devices that measure physical quantities and convert them into signals that can be read by observers or instruments. They are used in many applications from cars and machines to medicine and more. Sensors come in different types including optical sensors, which detect light, and biosensors, which are used in biomedical applications and detect biological components. The resolution of a sensor refers to the smallest change it can detect in the measured quantity.
This document describes an IOT based weather reporting system that uses temperature, humidity, and rain sensors to monitor weather conditions and provide live reporting over the internet. The system uses an Arduino Uno microcontroller connected to DHT11 and rain drop sensors to constantly measure temperature, humidity, and rainfall. The sensor data is transmitted to an online server via WiFi. Users can access the weather data by visiting a website. The system provides automated, real-time weather monitoring and reporting with high accuracy at a low cost.
The document discusses sensors, defining them as devices that measure physical quantities and convert them into signals. It describes qualities of good sensors such as sensitivity and lack of influence on the measured property. Additionally, it covers common sensor types, errors, and measurement definitions like sensitivity, deviation, and resolution.
The document discusses sensors used in aircraft autopilot systems. An automatic flight control system uses various sensors to monitor speed, height, position, doors, obstacles, fuel and maneuvers. A computer receives data from these sensors, compares it to pre-designed values, and provides control signals to engines, flaps, and rudders to enable smooth autonomous flight. Sensors provide input to computers, which are the system's brains, and mechanics provide the outputs to control aircraft systems.
The project uses a PIR motion sensor to detect motion and trigger a camera. An Arduino microcontroller coordinates and controls the system, activating the camera when the PIR sensor detects motion.
A smart sensor is a device that integrates a sensor and processing unit into a single package. It can perform functions like data conversion, communication, decision making, and logical operations. Smart sensors have applications in industries, automotives, biomedicine, defense, and more. They allow for faster, more accurate, and more intelligent sensing compared to traditional sensors.
This document describes a project to develop an industrial data acquisition system using ARM architecture. The system uses various sensors interfaced with an LPC2129 microcontroller to monitor temperature, CO2, light, and color. The sensor data is transmitted wirelessly using Zigbee to a monitoring node. The system allows remote monitoring of industrial environments for improved efficiency and safety. It provides a low-cost solution for continuous, real-time sensor data collection and monitoring. Future work involves integrating the system with the Internet of Things for intelligent sensor monitoring and control.
This two CD set contains PLC training simulations including: (1) hardware I/O and BCD simulations, (2) a motorized garage door simulation, and (3) an automated filling system simulation. It also includes simulations for: (4) an intersection traffic light control, (5) a batch mixing system, (6) binary coded decimal, and (7) dual compressor control. Further simulations are for: (8) a 4 floor elevator, and (9) a bottle line. More details on the simulations included on both CDs can be found at the provided URL.
This document provides guidance on selecting and installing surge protection devices (SPDs) for process control systems to protect sensitive electronics from electrical surges. It discusses SPD placement for different applications including hazardous areas, analog and digital I/O, high current signals up to 6A, 4-20mA loops, interposing relays, RTDs, HART communication, and RS232/RS485. SPDs should be installed at both ends of cable runs connecting PLCs, field instruments, and I/O to provide adequate protection from surges traveling on cables.
PLC and HMI Programming; and Other Examples of Work Performed by Jeff FingerJeffrey Finger
Jeff Finger has experience programming programmable logic controllers (PLCs) and human-machine interfaces (HMIs). He has performed various automation tasks including developing HMI screens, writing and troubleshooting PLC ladder logic, integrating different control systems, and more. Jeff is skilled at industrial automation work involving PLCs, HMIs, and other control systems.
This document discusses smart sensors and the Internet of Things (IoT). It begins with introducing the group members and then outlines topics to be covered such as definitions of smart sensors, their evolution, examples of smart sensors used in IoT applications, and the benefits of a world connected by smart sensors and IoT. Specific types of smart sensors are explained in more detail such as temperature, proximity, pressure, gas, accelerometer, level, motion detection, optical, and gyroscope sensors. Applications of smart sensors for smart cities, utilities, and environmental monitoring are presented. Both pros and cons of smart sensors are listed.
Introduction to IoT
Components of the IoT
IoT Related Statistics
IoT Applications & Use Case Scenarios
Stakeholders of the IoT Applications
Future Directions
Conclusions
Smart IR temperature sensors integrate sensors and circuits to process environmental information without human interference. The new smart sensors are the smallest available, allowing remote control and monitoring from a computer. They work by measuring infrared radiation between 0.7-14 microns, which corresponds to object temperatures. Digital electronics and software provide fast response, remote setup and calibration, and additional functionality. As an example, a smart IR sensor can control a space heater based on the actual temperature of the area being heated rather than just the heater itself, improving safety and efficiency.
This document discusses smart sensors and intelligent sensors. It defines smart sensors as sensors combined with interfacing circuits that allow two-way communication and decision making. Intelligent sensors are an evolution of smart sensors that add data processing, reconfigurability, and the ability to aggregate data from other sensors. The document outlines the architecture and generations of smart sensors from early devices with just sensor elements to current ones with memory, digital intelligence, and integrated analog-to-digital conversion. It provides examples of smart sensor applications and discusses their advantages of being more reliable and scalable while also having higher complexity and cost compared to simple sensors.
The document discusses smart sensors, providing details on their architecture, fabrication, advantages, disadvantages and applications. Some key points:
- Smart sensors integrate a sensor, analog/digital converter, processor and communication interface on a single chip, allowing them to process and communicate sensor data.
- The basic architecture includes a sensing element, amplifier, ADC, memory, processor and communication components. Fabrication uses techniques like micro-machining and bonding.
- Advantages are reduced system load and faster operation. Applications include industrial monitoring, automotive controls, biomedical devices, and smart dust networks of tiny sensors. Disadvantages include higher initial costs and issues with mixing old and new devices.
T-Mobile IoT: The Network Built for Software.
Best in Class Radio
Distributed & Virtualized Core
Advanced Connectivity
Operation System
Connectivity Management (Local and Global)
Device and Data Management
Application Services Layer
IoT Solutions
Packaged Solutions - Off-the-Shelf
Custom Solutions
Industry Focused - Built for Purpose
IoT Innovation
Emerging Tech - Edge, Private Node
Developer Platform
Innovation Hubs - Curiosity Lab, 5G Innovation Lab, Automotive Lab
The document summarizes the key points from a technical seminar on sensor technology presented by Sharenya. It discusses sensor design features and trends in sensor technology, focusing on miniaturization and the increasing use of multi-sensor and wireless systems. The main advantages of sensors are listed as high accuracy, resolution, reliability and energy efficiency. Examples of sensor uses include detection of light, motion, temperature, pressure as well as vehicle speed and environmental molecules.
Smart Sensors: Analyzing Efficiency of Smart Sensors in Public DomainDr. Amarjeet Singh
The paper gives the brief idea of smart sensors,
structure and its application. Smart sensor as compare to
other sensors can sensor anything with the special computing
devices connected with each other in sensor network. These
smart sensors first convert the digital signals to analog signals
and then communicate the message to the device. Now a days
smart sensors are used almost everywhere around us but very
few people know its working and future applications. So here
is a small review on smart sensors. This paper will help you
gain knowledge and its applications in daily life.
Introduction to smart sensors & its’ applicationPranay Mondal
Smart sensors are sensors combined with interfacing electronic circuits that can perform logic functions, two-way communication, and make decisions. They convert physical, biological, or chemical inputs into digital outputs. Smart sensors have evolved from first generation devices with little electronics to now being fully integrated systems-on-chip with sensing, processing, communication and power management. They are used widely in industrial applications like structural health monitoring and geological mapping due to advantages like minimum interconnects, high reliability, and scalability.
Sensors are devices that measure physical quantities and convert them into signals that can be read by observers or instruments. They are used in many applications from cars and machines to medicine and more. Sensors come in different types including optical sensors, which detect light, and biosensors, which are used in biomedical applications and detect biological components. The resolution of a sensor refers to the smallest change it can detect in the measured quantity.
This document describes an IOT based weather reporting system that uses temperature, humidity, and rain sensors to monitor weather conditions and provide live reporting over the internet. The system uses an Arduino Uno microcontroller connected to DHT11 and rain drop sensors to constantly measure temperature, humidity, and rainfall. The sensor data is transmitted to an online server via WiFi. Users can access the weather data by visiting a website. The system provides automated, real-time weather monitoring and reporting with high accuracy at a low cost.
The document discusses sensors, defining them as devices that measure physical quantities and convert them into signals. It describes qualities of good sensors such as sensitivity and lack of influence on the measured property. Additionally, it covers common sensor types, errors, and measurement definitions like sensitivity, deviation, and resolution.
The document discusses sensors used in aircraft autopilot systems. An automatic flight control system uses various sensors to monitor speed, height, position, doors, obstacles, fuel and maneuvers. A computer receives data from these sensors, compares it to pre-designed values, and provides control signals to engines, flaps, and rudders to enable smooth autonomous flight. Sensors provide input to computers, which are the system's brains, and mechanics provide the outputs to control aircraft systems.
The project uses a PIR motion sensor to detect motion and trigger a camera. An Arduino microcontroller coordinates and controls the system, activating the camera when the PIR sensor detects motion.
A smart sensor is a device that integrates a sensor and processing unit into a single package. It can perform functions like data conversion, communication, decision making, and logical operations. Smart sensors have applications in industries, automotives, biomedicine, defense, and more. They allow for faster, more accurate, and more intelligent sensing compared to traditional sensors.
This document describes a project to develop an industrial data acquisition system using ARM architecture. The system uses various sensors interfaced with an LPC2129 microcontroller to monitor temperature, CO2, light, and color. The sensor data is transmitted wirelessly using Zigbee to a monitoring node. The system allows remote monitoring of industrial environments for improved efficiency and safety. It provides a low-cost solution for continuous, real-time sensor data collection and monitoring. Future work involves integrating the system with the Internet of Things for intelligent sensor monitoring and control.
This two CD set contains PLC training simulations including: (1) hardware I/O and BCD simulations, (2) a motorized garage door simulation, and (3) an automated filling system simulation. It also includes simulations for: (4) an intersection traffic light control, (5) a batch mixing system, (6) binary coded decimal, and (7) dual compressor control. Further simulations are for: (8) a 4 floor elevator, and (9) a bottle line. More details on the simulations included on both CDs can be found at the provided URL.
This document provides guidance on selecting and installing surge protection devices (SPDs) for process control systems to protect sensitive electronics from electrical surges. It discusses SPD placement for different applications including hazardous areas, analog and digital I/O, high current signals up to 6A, 4-20mA loops, interposing relays, RTDs, HART communication, and RS232/RS485. SPDs should be installed at both ends of cable runs connecting PLCs, field instruments, and I/O to provide adequate protection from surges traveling on cables.
PLC and HMI Programming; and Other Examples of Work Performed by Jeff FingerJeffrey Finger
Jeff Finger has experience programming programmable logic controllers (PLCs) and human-machine interfaces (HMIs). He has performed various automation tasks including developing HMI screens, writing and troubleshooting PLC ladder logic, integrating different control systems, and more. Jeff is skilled at industrial automation work involving PLCs, HMIs, and other control systems.
Apple's Smart Sensor Technologies -- market research report (sample)MEMS Journal, Inc.
This comprehensive 204-page report covers the latest and emerging sensors, microsystems, and MEMS technologies which Apple is developing and using for its products including the iPhone and the Watch. To order the full version, please go here: https://fs8.formsite.com/medved44/form33/index.html
This document is a certificate of release or discharge from active duty in the U.S. Navy for an individual named Scott Allan Lambertus. It provides key identifying information such as their name, social security number, rank, dates of service, and record of military assignments. The certificate indicates they served honorably from 2012 to 2018 as an E-4 in the Navy, with their last duty assignment being with Fighter Squadron 151 aboard the USS Nimitz.
Done by Group : Diamond
School Name : Umm Hakeem Independent Secondary School for Girls.
Smart Sensors Module : Gives knowledge about smart sensors and the PVDF films through activities, experiments and projects which depend on smart sensors.
the product Idea is : The smart blind glasses have an infrared sensor , it will be used by blind people which will allow them to walk freely like any other normal person, or let’s say that they are going to walk like they actually can see.
Maxon operation & application of maxon’s new epos controllerElectromate
The EPOS P is a programmable motion controller that functions similarly to a PLC. It has the same functionality as the EPOS 24/5 motion controller and additional CAN master capabilities. Programming follows the IEC 61131-3 standard like PLCs. The EPOS P has 1MB of memory for programming motion profiles and storing variables, and can process up to 10,000 lines of code in under 4ms, making it suitable for controlling motion and automation applications.
"Building HMI with Visual Basic Technologies - 1998". Though they are old slides but still worth having a look especially for those who are new to HMI and SCADA technologies.
This document discusses industrial automation applications of pneumatics and PLC systems. It lists the main industrial fields that utilize these technologies, including automotive, cement, food, pharmaceutical, infrastructure, machine, and chemical industries. It also outlines the typical automation applications involved, such as engineering design, assembly, installation, PLC programming, and visualization. Several example applications and client references are provided, including pneumatic test benches for automotive companies and machine modernization projects for various industrial manufacturers.
Bluetooth based smart sensor devices 2Vijay Kribpz
This document discusses Bluetooth-based smart sensor devices. It begins with an abstract and introduction to Bluetooth technology, defining it as a short-range wireless standard. It then covers Bluetooth operations, topologies of piconets and scatternets, and how Bluetooth works. The document discusses using sensors with Bluetooth, including examples like pressure sensors. It describes building Bluetooth-based wireless sensor networks and addressing Bluetooth security. It outlines characteristics and applications of Bluetooth technology, as well as advantages and disadvantages. The conclusion envisions future expansion of Bluetooth applications.
PROFINET - The backbone of IIoT.
IOT, IIOT, Industrie 4.0 are becoming popular topics of conversation, but what do they mean and where does PROFINET fit into the equation? This presentation will try to explain this and provide a clearer idea of the benefits of using PROFINET as part of an overall move towards these concepts, collectively known as the 4th Industrial Revolution.
BIOGRAPHY
Peter Thomas is a Process Control and Automation Engineer with Control Specialists Ltd. He is Chairman of the PROFIBUS & PROFINET International Training Centre (PITC) Workgroup and is a member of the PROFIBUS UK Steering Committee.
This document discusses Bluetooth technology and its use in smart sensor networks. It begins with an introduction of Bluetooth and its specifications. It then explains the two main Bluetooth topologies - piconet and scatternet. Next, it describes how Bluetooth can be used to create wireless sensor networks and the roles of smart sensor nodes and the gateway. It outlines the hardware and software considerations for implementing a Bluetooth smart sensor network and the process the gateway uses to communicate with smart sensor nodes. In conclusion, it briefly discusses applications of sensor networks and factors that influence sensor network design.
Projet de fin d'etude :Control d’acces par empreintes digitaleAbdo07
Projet de fin d'etude :Control d’acces par empreintes digitale
Réalisé par : AABIDA Abderrahime _NAJMA Soufiane _ AIT BBA Mohamed
Encadré par : M.ROUFI
Année Universitaire : 2014-2015
Université Cadi Ayyad
Faculté des sciences Semlalia
Marrakech
The document discusses the electrical interface of sensors, dividing it into power (operating voltage) and output signal type. It describes discrete outputs like PNP and NPN transistors that function like a switch, and analog outputs that can represent measurement or position as a varying voltage, current, or digital pulse width. Discrete sensors are generally preferred over 2-wire AC/DC types. The document provides examples of analog applications and reviews the key aspects of a sensor's electrical interface.
Wireless sensor networks use multiple sensor nodes that communicate wirelessly to monitor environments. Each node contains sensors to capture phenomena, processing capabilities, and wireless communication. Common sensor types include temperature, pressure, optical, acoustic, and chemical sensors. Challenges for wireless sensor networks include limited energy, decentralized operation, and security. Example applications are structural health monitoring, traffic control, and precision agriculture.
The document describes a PC-based oscilloscope that can display input waveforms on a computer screen. It includes a block diagram of the circuit which conditions input signals below 1 kHz and converts them to digital format for interfacing with a PC. Software written in Turbo C acquires and displays the data. The PC-based oscilloscope costs less than traditional models, can store multiple waveforms, and allows viewing on multiple PCs over a network. However, it has limitations such as low input frequency and voltage range and lacks multi-channel capability.
The document introduces the Cy-Net3 mesh networking technology and its USB/Ethernet Gateway module. Cy-Net3 uses ad hoc mesh networking to allow self-forming and self-healing low power networks. The Gateway module allows Cy-Net3 networks to connect to Ethernet and USB devices and supports various applications including automated meter reading, home automation, and industrial telemetry.
Review Schneider Electric’s innovative and efficient upstream oil and gas offer and how to optimize remote assets. Benefit from industry expertise and live demonstrations that highlight reducing total cost of ownership and turning data into reliable information to drive business.
This document provides an overview of RTX, a Danish company that specializes in wireless technologies and IoT product integration. The agenda includes an introduction to RTX, discussions on product design and wireless technologies for IoT, and examples of IoT projects. RTX has expertise in areas like Bluetooth, DECT, Wi-Fi, LoRa and LTE for IoT. They provide full-service solutions including hardware, software, certification and supply chain management to integrate wireless technologies into IoT products and systems.
Design and Implementation of Secured Wireless Communication Using Raspberry PiIRJET Journal
This document describes the design and implementation of a secured wireless communication system using a Raspberry Pi. The system uses a master-slave architecture with wireless communication between sensor nodes and a master controller. Various sensors measure parameters like temperature, light intensity, voltage and current. The sensor data is sent wirelessly to the master controller and then to a Raspberry Pi, which acts as a wireless web server. The Raspberry Pi allows remote monitoring of the sensor data through a smart phone using GPRS technology. The system aims to provide a low-cost and portable solution for industrial wireless monitoring applications.
The document discusses the integration of expert systems with SCADA for power grid management. It describes two key expert system applications: (1) An Intelligent Alarm Processor (IAP) that analyzes faults and provides quick diagnoses; and (2) A Power System Restoration (PSR) system that generates switching sequences and advice for restoring power during emergencies. The expert systems can reduce operator cognitive load, provide faster response to events, minimize errors, and help avoid critical situations.
This document introduces LoRa-BLE modules and TTN-compatible carrier-grade LoRaWAN gateways from 144Lab. It summarizes the key features of the InsightSiP LoRa-BLE module, including that it uses an InsightSiP design with SX1261 and nRF52832 chips. It also summarizes the key features of 144Lab's Samaritaine.01 gateway, including that it uses the LoRa-BLE module and can be powered by two AA batteries for long-term operation. Finally, it thanks the audience for their attention.
The document describes a smart LED display board project submitted for a degree. It uses a GSM module to receive SMS messages which are then displayed on the LED board. The system includes an AT89S51 microcontroller, GSM module, LED display, power supply, and software. Users can send display messages via SMS from any location which are received by the GSM module and shown in scrolling text on the LED board. The design aims to provide a flexible SMS-driven display system for places like colleges, universities, and other public areas.
The document provides information about DeviceNet and Smart Distributed Systems (SDS), two industrial communication protocols based on CAN bus. DeviceNet was developed by Rockwell and uses a trunk/drop topology to connect devices like sensors to controllers. It supports up to 64 nodes at speeds up to 500kbps. SDS was developed by Honeywell for connecting intelligent sensors and actuators and supports up to 125 nodes at speeds up to 1Mbps. The document compares aspects of the two protocols such as maximum bit rates, number of supported nodes, and default node numbers.
The document discusses data loggers used in Indian Railways. It provides an overview of RDSO which tests railway equipment. It then discusses the signal testing laboratory and its facilities. A key point is that data loggers monitor relay activities to generate reports on the signaling system. The document describes how data is collected via sensors and sent to the data logger. It outlines the types of data loggers and their applications in Indian Railways. Areas for improvement are also noted such as measuring train load and track failures to prevent accidents.
This document outlines the thesis project of Satya Prakash Rout, a student pursuing an M.Tech in Applied Optics. The project involves emulating different Dynamic Bandwidth Allocation algorithms to monitor the performance of a 10G-EPON network implementing Triple Play. Specific aspects that will be studied include implementing Triple Play with a new scheduling algorithm called TD-Sense, generating different traffic models, comparing the performance of DBA-Gated, DBA-Linear and DBA-Max algorithms, and potential future work involving long-reach PONs and green networking techniques. The document concludes by acknowledging the contributions of the student's guide, advisors and classmates to the successful completion of the project.
A consolidated description of ten recent innovations in RTD signal conditioning for industrial process measurement and control. Items include incorporation of ASIC processors, improved calibration, and more.
IRJET - Software-Defined Radio using ‘Redpitaya’IRJET Journal
The document describes a project using a Redpitaya software-defined radio platform and RTL-SDR dongle to demonstrate a basic wireless communication system to students. A magnetic loop antenna is used to transmit a 3kHz signal modulated to 30MHz from the Redpitaya, which is then received by an RTL-SDR dongle and displayed through software on a laptop to help students understand fundamental wireless communication concepts. The project aims to provide students with hands-on experience of how signals are modulated, transmitted, and received in a software-defined radio system to improve their understanding of wireless communications.
IRJET- Power Line Carrier CommunicationIRJET Journal
This document describes power line carrier communication (PLCC), which uses power lines as a communication medium. It discusses using PLCC to transmit electricity billing data from individual homes to the electricity company without site visits. Key components of the system include a real-time clock, energy meter, microcontroller, LCD display, and FSK transmitter and receiver. Data transmission is done by modulating a signal onto the power line using FSK modulation. The system is intended to reduce the burden on electricity companies by allowing remote transmission of billing data without the need for site visits.
This document describes a wireless fuel level sensor system using radio frequency. The system consists of a transmission section and receiver section connected by an RF module. The transmission section uses liquid level probes connected to a microcontroller to detect the fuel level and encode the data. The encoded data is transmitted via an RF transmitter. The receiver section receives the data via an RF receiver, decodes it using a decoder, and sends it to another microcontroller connected to an LCD to display the fuel level. The system provides automated and wireless fuel level detection with low power consumption.
This document provides an overview of 5G technologies and discusses key areas of research and development. It begins by looking back at early 5G research from 2003 and the maturation of 4G standards. It then explores several candidate 5G technologies including massive MIMO, device-to-device communication, and network function virtualization. The document also discusses efforts towards developing 5G by various groups and the challenges of developing a comprehensive 5G vision given the early stage of research. Energy efficiency and a potential 90% reduction in network energy consumption by 2020 is highlighted as an important focus area.
This document provides an overview of 5G technologies and discusses key areas of research and development. It begins by looking back 10 years at early 5G research and standardization efforts. It then discusses the maturing of 4G standards and examples of 4G deployments in China. The document outlines various 5G research initiatives and candidate technologies under exploration for 5G. It emphasizes that the vision for 5G is still emerging and will be defined through ongoing research exploring technical approaches piece by piece. The document also discusses efforts to make communication networks more energy efficient and "green" as data usage grows dramatically.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3Data Hops
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Issues:
Cost
Size, weight
Power use
Self-testing, self-calibration
Wired/wireless communication
Stand-alone components are far away from ideal characteristics desired for measurements.
Cost: Only a few cents extra for a BT chip
Power usage: 10% of a BT chip
Low End Extension (LEE) of Bluetooth is the technology to solve a simple mismatch. There are several small devices that could add value by having wireless radio connection to mobile terminal but cannot bear the power consumption and cost associated to Bluetooth. However, the mobile terminals will have Bluetooth as the short-range wireless solution. Bluetooth LEE tackles the mismatch by introducing minor additions to the Bluetooth chip in the mobile terminals that allows designs that will produce major saving in power consumption and cost in the chips embedded into small devices. Examples of the small devices include wireless sensors, toys, wireless pens etc
Instead of replacing the existing wired connections with the wireless as targeted by Bluetooth, the BluLite targets to provide new connections between the Bluetooth enabled mobile phones and the devices that cannot bare the additional price and/or power consumption of the Bluetooth radio but could benefit from the connectivity. Further, the target use scenarios require some processing in the device connected to the mobile phone and there is not necessary line-of-sight connection. Thus, IRDA and RFID solutions do not meet the requirements. The following categorization highlights the BluLite use cases.
IrDa fails to meet the link distance, the power consumption and the pointing criteria. Furthermore, the current co-existence of IrDa and Bluetooth is not a cost- and size-efficient solution for mobile terminals.
ZigBee would result in a considerable cost and size penalty to the mobile terminals since it results in yet another radio alongside Bluetooth. It’s as complex as Bluetooth and the power-efficient protocols are limited to home and industrial automation use.
RFID is difficult to benchmark due to the plurality of RFID technologies. The RFID technologies that feature the essence of the technology, passive tag, would either fail in link distance, voice support and in cost increase in mobile terminal.
Bluetooth technology is limited by its peak and average power consumption, cost, piconet topology, and connection set-up times. The consensus is that Bluetooth technology cannot be scaled down to the appropriate power and cost levels for small peripherals just by applying advanced implementation techniques. Rather, the specification needs to be changed in some areas to account for the mismatch in design requirements of small peripherals and mobile terminals.
The MIMOSA sensor architecture is defined to be modular, freely scalable and has open interfaces for third parties through open Simple Sensor Interface (SSI) protocol. Plug-in type implementation of sensors using SSI is the key to modularity. Using SSI system will detect what sensors are available regardless their location in terminal, in RFID tag, or in sensor radio node. This modular architecture is shown here. The Sensor API on the host device will keep a list of available sensors and provide functions for accessing the sensors, be they local (connected directly to the host device) or remote (RFID or BT LEE connected).
NanoIP, which stands for the nano Internet Protocol, is a concept that was created to bring Internet-like networking services to embedded and sensor devices, without the overhead of TCP/IP. NanoIP was designed with minimal overheads, wireless networking, and local addressing in mind.
The protocol actually consists of two transport techniques, nanoUDP, which is an unreliable simple transport, and nanoTCP, which provides retransmissions and flow control. A socket-compatible API is provided which makes the use of the protocols very similar to that of IP protocols. The only difference is in addressing and the port range. NanoIP makes use of the MAC address of underlying network technology rather than IP addresses, which are not needed for local networks. The port range is 8-bits, 256 ports each for source and destination. In addition to nanoIP itself, a range of compact application protocols have been developed, such as nHTTP and nPing.