1. The document discusses how AI and IoT can be used together in various industries like manufacturing, agriculture, transportation and healthcare.
2. In manufacturing, AI and IoT are used for predictive maintenance and quality control to reduce downtime and increase operational efficiency. Sensors in IoT devices collect data that AI analyzes to detect maintenance issues.
3. In agriculture, smart sensors monitor crop fields and automate irrigation, while AI and data analysis provide insights into crop health. AI is also used in autonomous vehicles, using sensors to navigate roads and share information.
4. In healthcare, AI and IoT are applied to remote patient monitoring, improving diagnostics, reducing wait times and tracking medical equipment.
The document discusses various real world applications of Internet of Things (IoT) technology. It describes how IoT is used in industrial settings to improve processes and productivity through automated equipment monitoring and predictive maintenance. It also discusses consumer IoT applications for personal devices and smart home appliances. Additional sections cover IoT applications in retail supply chain management, banking security and fraud detection, healthcare remote patient monitoring, transportation fleet management, agriculture environmental monitoring, energy use monitoring, smart cities infrastructure, and military command and control systems.
The document discusses Internet of Things (IoT). It defines IoT as a network of connected devices that can collect, process, and transmit data without human intervention using wireless communication. It explains how IoT works by devices gathering data and sending it over the internet for processing, then receiving instructions to improve performance. Advantages include efficiency, cost savings, and new business opportunities, while disadvantages include privacy, security, and complexity issues. The document outlines various applications and sensors used in IoT, as well as challenges such as security, regulation, compatibility and bandwidth limitations.
Models applied in IoT solutions, Semantic models for data models, Application of semantic models,
information models, information models to structure data, relationships between data categories
The document discusses Internet of Things (IoT) and provides an overview. It defines IoT as a network of physical objects embedded with sensors, software and network connectivity that enables the collection and exchange of data. IoT allows objects to be sensed and controlled remotely across existing network infrastructure, creating opportunities to directly integrate physical systems with computer-based systems. Common applications of IoT mentioned include smart homes, infrastructure management, industrial uses, healthcare, transportation and more.
Looking to build your career in IoT industry? Then knowledge of IoT and IoT applications are indispensable for any software engineer. Avantika University’s Engineering Department has the separate unit of IoT. It’s Engineering College is one of the Top Engineering Colleges in MP. Avantika university is the part of reputed MAEER's MIT Pune.
To know more details, visit us at: http://avantikauniversity.edu.in/engineering-colleges/iot-iot-applications-mp.php
This is my CV for research positions. I am open for Applied research projects with tie-ups with University labs and with corporate keen to demonstrate their skills and proof of concepts.
Trends in shaping Engineering Education in India - MIT AOEMITAcademy1
"Today, computers have invaded each facet of our lives. Whether they are medical, education, offices, industries, home, entertainment, computers have entirely changed the way of our living. Engineering has set many examples of success and has also changed the education system. Some of the top trends are discussed here. "
The document discusses various real world applications of Internet of Things (IoT) technology. It describes how IoT is used in industrial settings to improve processes and productivity through automated equipment monitoring and predictive maintenance. It also discusses consumer IoT applications for personal devices and smart home appliances. Additional sections cover IoT applications in retail supply chain management, banking security and fraud detection, healthcare remote patient monitoring, transportation fleet management, agriculture environmental monitoring, energy use monitoring, smart cities infrastructure, and military command and control systems.
The document discusses Internet of Things (IoT). It defines IoT as a network of connected devices that can collect, process, and transmit data without human intervention using wireless communication. It explains how IoT works by devices gathering data and sending it over the internet for processing, then receiving instructions to improve performance. Advantages include efficiency, cost savings, and new business opportunities, while disadvantages include privacy, security, and complexity issues. The document outlines various applications and sensors used in IoT, as well as challenges such as security, regulation, compatibility and bandwidth limitations.
Models applied in IoT solutions, Semantic models for data models, Application of semantic models,
information models, information models to structure data, relationships between data categories
The document discusses Internet of Things (IoT) and provides an overview. It defines IoT as a network of physical objects embedded with sensors, software and network connectivity that enables the collection and exchange of data. IoT allows objects to be sensed and controlled remotely across existing network infrastructure, creating opportunities to directly integrate physical systems with computer-based systems. Common applications of IoT mentioned include smart homes, infrastructure management, industrial uses, healthcare, transportation and more.
Looking to build your career in IoT industry? Then knowledge of IoT and IoT applications are indispensable for any software engineer. Avantika University’s Engineering Department has the separate unit of IoT. It’s Engineering College is one of the Top Engineering Colleges in MP. Avantika university is the part of reputed MAEER's MIT Pune.
To know more details, visit us at: http://avantikauniversity.edu.in/engineering-colleges/iot-iot-applications-mp.php
This is my CV for research positions. I am open for Applied research projects with tie-ups with University labs and with corporate keen to demonstrate their skills and proof of concepts.
Trends in shaping Engineering Education in India - MIT AOEMITAcademy1
"Today, computers have invaded each facet of our lives. Whether they are medical, education, offices, industries, home, entertainment, computers have entirely changed the way of our living. Engineering has set many examples of success and has also changed the education system. Some of the top trends are discussed here. "
Presented at the IndicThreads.com Software Development Conference 2016 held in Pune, India. More at http://www.IndicThreads.com and http://Pune16.IndicThreads.com
--
A survey on Machine Learning and Artificial Neural NetworksIRJET Journal
This research paper provides an overview of machine learning and artificial neural networks. It discusses various machine learning techniques like supervised learning, unsupervised learning, reinforcement learning, and deep learning. It also describes artificial neural networks and how they are used to mimic biological neural networks. The paper reviews several related works applying machine learning and neural networks to tasks like hydrological modeling, facial expression recognition, and cattle detection. It highlights advantages like improved accuracy and automation, as well as limitations like data and computational requirements. Overall, the paper aims to improve knowledge of machine learning and neural networks techniques and their applications.
The Role of Artificial Intelligence in Modern Information Technology.pptxKarpagam Engineering
Discover the role of artificial intelligence in modern information systems and how it is revolutionizing the way we process and analyze data. Explore the benefits and challenges of implementing AI technology and its potential impact on various industries. Stay informed about the latest advancements in AI and gain insights into its future implications for the world of information.
The document discusses various types of testing for Internet of Things (IoT) infrastructure. It covers component testing of devices, communications, and computing. It also discusses user experience testing, including usability, target audiences, and user behavior analysis. Finally, it discusses different types of infrastructure testing like integration testing, load testing, compatibility testing, and performance testing to evaluate how the IoT system performs under various conditions.
Smart Manufacturing: A Revolution in Industry 4.0 | Enterprise WiredEnterprise Wired
This article explores the multifaceted landscape of smart manufacturing, delving into its key principles, transformative technologies, applications across various industries, and the profound impact it has on shaping the future of manufacturing.
IoT Development In Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations & boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
Introduction to IoT, Current trends and challenges. It also describes some of the industry standard platforms such as Microsoft Azure IoT Edge and AWS IoT. Trends described includes Edge computing, Security, Cognitive Computing, Analytics, Containers and Microservices
Intelligent Manufacturing system Final 1Harish Pant
1. The document discusses intelligent manufacturing systems and Industry 4.0, describing how increased connectivity through technologies like the Internet of Things, cyber-physical systems, and sensors is allowing for more customized, flexible production and new areas of innovation.
2. Key aspects of Industry 4.0 include deep learning, quantum computing, advanced artificial intelligence, new IOT platforms, cloud-based analytics services, and partner ecosystems to deliver IOT solutions.
3. Examples are given of new technologies like autonomous robotic systems from companies like Festo and ABB, as well as smart factory approaches from German research initiatives and automakers like Volkswagen integrating digital technologies into new products and customized, digitally-driven production.
The Most Definitive guide to Industrial IoT ImplementationAditya Basu
Industrial IoT has the potential of USD 15.3 trillion to the global economy by 2030 subjected to an improvement of 1-1.5%. Industrial Internet is a revolutionary technology that enhances the Industrial environment with the IoT capabilities. IIoT helps to solve the bottlenecks in the business environment, provides operational efficiency, increases productivity and reduces the complexity of the process.
The main benefit of Industrial IoT is the connected enterprise that enhances the visibility across various departments and benefits with a smooth workflow. According to General Electric CEO, Jeff Immelt, IIoT has twice the market potential than that of the consumer IoT.
In this Guide you will know everything about
a) The Connected Factory! Role of IIoT
b) Evolution of IIoT to Industry 4.0
c) Industrial IoT Ecosystem
d) Value Chain Players today and what you can learn from them
e) How IIoT is Different from IoT
f) Technology Drivers and Adoption
g) Market Indicators and why you should jump the Bandwagon NOW!
h) Market Revenues and Areas of Focus
i) The Digitization Wave
j) Real World Industrial IoT Case Studies Including Solutions & Outcomes
Electronics and Robotics - Ajith AmarasekaraSTS FORUM 2016
The document discusses opportunities and challenges in the electronics industry due to paradigm shifts driven by new technologies. It notes that mechanical systems are increasingly being replaced by intelligent electronic systems, enabling autonomous operation and adaptability. However, it also notes that working with manufacturers to understand requirements, long development times, and needing skills in areas like data analytics, signal processing, machine learning and control theory present challenges. The opportunities lie in developing solutions that leverage Sri Lanka's existing strengths and addressing niche application areas.
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data
This document discusses the importance of teaching automation as an integral part of engineering education. It notes that technological developments are happening globally and India needs large numbers of technical personnel able to work with present technologies. However, while Indian universities produce many engineers, their skills do not always match industry needs. The document argues that integrating practical exposure to automation technologies through industry partnerships can help develop the multi-tasking abilities engineers require. This will better prepare them for roles in industries like textiles, electronics, and manufacturing that are adopting increasing levels of automation.
Embedded systems domain offers great career opportunity for fresh engineers. Team Emertxe had a seminar session at MVJ college of engineering, Bangalore by sharing details about the same topic.
Introduction, Relevance of IOT for the future,
IOT in Indian Scenario –
IOT and Aadhaar,
IOT for health services,
IOT for financial inclusion,
IOT for rural empowerment.
IOT Applications:
Lighting as a service (case study)
Smart Parking (case study)
IOT Development in Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations and boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
This document describes a Raspberry Pi-based health monitoring system that measures heartbeat and pulse using a Pulse Sensor. The system uses an ADS1115 ADC module to read analog voltage signals from the Pulse Sensor and send the data over I2C to the Raspberry Pi. Python code is used to analyze the sensor signals and calculate the heartbeat rate, which is displayed in Processing and also sent over serial to other devices. Circuit diagrams and instructions for installing required libraries and configuring the Raspberry Pi I2C and serial interfaces are provided.
This document provides steps to deploy a web application using Azure DevOps. It outlines 35 steps to create an Azure DevOps project, clone a repository, commit code changes locally using Git, and push the code to the Azure DevOps repository. The aim is to deploy a web application by hosting HTML code in Azure DevOps. The result is that the web application is successfully deployed using Azure DevOps.
Presented at the IndicThreads.com Software Development Conference 2016 held in Pune, India. More at http://www.IndicThreads.com and http://Pune16.IndicThreads.com
--
A survey on Machine Learning and Artificial Neural NetworksIRJET Journal
This research paper provides an overview of machine learning and artificial neural networks. It discusses various machine learning techniques like supervised learning, unsupervised learning, reinforcement learning, and deep learning. It also describes artificial neural networks and how they are used to mimic biological neural networks. The paper reviews several related works applying machine learning and neural networks to tasks like hydrological modeling, facial expression recognition, and cattle detection. It highlights advantages like improved accuracy and automation, as well as limitations like data and computational requirements. Overall, the paper aims to improve knowledge of machine learning and neural networks techniques and their applications.
The Role of Artificial Intelligence in Modern Information Technology.pptxKarpagam Engineering
Discover the role of artificial intelligence in modern information systems and how it is revolutionizing the way we process and analyze data. Explore the benefits and challenges of implementing AI technology and its potential impact on various industries. Stay informed about the latest advancements in AI and gain insights into its future implications for the world of information.
The document discusses various types of testing for Internet of Things (IoT) infrastructure. It covers component testing of devices, communications, and computing. It also discusses user experience testing, including usability, target audiences, and user behavior analysis. Finally, it discusses different types of infrastructure testing like integration testing, load testing, compatibility testing, and performance testing to evaluate how the IoT system performs under various conditions.
Smart Manufacturing: A Revolution in Industry 4.0 | Enterprise WiredEnterprise Wired
This article explores the multifaceted landscape of smart manufacturing, delving into its key principles, transformative technologies, applications across various industries, and the profound impact it has on shaping the future of manufacturing.
IoT Development In Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations & boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
Introduction to IoT, Current trends and challenges. It also describes some of the industry standard platforms such as Microsoft Azure IoT Edge and AWS IoT. Trends described includes Edge computing, Security, Cognitive Computing, Analytics, Containers and Microservices
Intelligent Manufacturing system Final 1Harish Pant
1. The document discusses intelligent manufacturing systems and Industry 4.0, describing how increased connectivity through technologies like the Internet of Things, cyber-physical systems, and sensors is allowing for more customized, flexible production and new areas of innovation.
2. Key aspects of Industry 4.0 include deep learning, quantum computing, advanced artificial intelligence, new IOT platforms, cloud-based analytics services, and partner ecosystems to deliver IOT solutions.
3. Examples are given of new technologies like autonomous robotic systems from companies like Festo and ABB, as well as smart factory approaches from German research initiatives and automakers like Volkswagen integrating digital technologies into new products and customized, digitally-driven production.
The Most Definitive guide to Industrial IoT ImplementationAditya Basu
Industrial IoT has the potential of USD 15.3 trillion to the global economy by 2030 subjected to an improvement of 1-1.5%. Industrial Internet is a revolutionary technology that enhances the Industrial environment with the IoT capabilities. IIoT helps to solve the bottlenecks in the business environment, provides operational efficiency, increases productivity and reduces the complexity of the process.
The main benefit of Industrial IoT is the connected enterprise that enhances the visibility across various departments and benefits with a smooth workflow. According to General Electric CEO, Jeff Immelt, IIoT has twice the market potential than that of the consumer IoT.
In this Guide you will know everything about
a) The Connected Factory! Role of IIoT
b) Evolution of IIoT to Industry 4.0
c) Industrial IoT Ecosystem
d) Value Chain Players today and what you can learn from them
e) How IIoT is Different from IoT
f) Technology Drivers and Adoption
g) Market Indicators and why you should jump the Bandwagon NOW!
h) Market Revenues and Areas of Focus
i) The Digitization Wave
j) Real World Industrial IoT Case Studies Including Solutions & Outcomes
Electronics and Robotics - Ajith AmarasekaraSTS FORUM 2016
The document discusses opportunities and challenges in the electronics industry due to paradigm shifts driven by new technologies. It notes that mechanical systems are increasingly being replaced by intelligent electronic systems, enabling autonomous operation and adaptability. However, it also notes that working with manufacturers to understand requirements, long development times, and needing skills in areas like data analytics, signal processing, machine learning and control theory present challenges. The opportunities lie in developing solutions that leverage Sri Lanka's existing strengths and addressing niche application areas.
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data
This document discusses the importance of teaching automation as an integral part of engineering education. It notes that technological developments are happening globally and India needs large numbers of technical personnel able to work with present technologies. However, while Indian universities produce many engineers, their skills do not always match industry needs. The document argues that integrating practical exposure to automation technologies through industry partnerships can help develop the multi-tasking abilities engineers require. This will better prepare them for roles in industries like textiles, electronics, and manufacturing that are adopting increasing levels of automation.
Embedded systems domain offers great career opportunity for fresh engineers. Team Emertxe had a seminar session at MVJ college of engineering, Bangalore by sharing details about the same topic.
Introduction, Relevance of IOT for the future,
IOT in Indian Scenario –
IOT and Aadhaar,
IOT for health services,
IOT for financial inclusion,
IOT for rural empowerment.
IOT Applications:
Lighting as a service (case study)
Smart Parking (case study)
IOT Development in Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations and boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
This document describes a Raspberry Pi-based health monitoring system that measures heartbeat and pulse using a Pulse Sensor. The system uses an ADS1115 ADC module to read analog voltage signals from the Pulse Sensor and send the data over I2C to the Raspberry Pi. Python code is used to analyze the sensor signals and calculate the heartbeat rate, which is displayed in Processing and also sent over serial to other devices. Circuit diagrams and instructions for installing required libraries and configuring the Raspberry Pi I2C and serial interfaces are provided.
This document provides steps to deploy a web application using Azure DevOps. It outlines 35 steps to create an Azure DevOps project, clone a repository, commit code changes locally using Git, and push the code to the Azure DevOps repository. The aim is to deploy a web application by hosting HTML code in Azure DevOps. The result is that the web application is successfully deployed using Azure DevOps.
The document provides steps to create a website using the Drupal content management system (CMS). It outlines 31 steps to install Drupal, configure the database, download and extract Drupal files, set the default theme, add custom blocks of content, and place blocks in specific regions of the site. The result is a successfully created website using Drupal that can be viewed locally.
The document provides steps to launch an AWS RDS MySQL database instance and connect to it from a local MySQL database. It involves opening the AWS console, selecting RDS, choosing MySQL, configuring a free-tier database, providing credentials, copying the endpoint, and connecting the local MySQL database using the endpoint and credentials. The result is that queries can successfully be executed on the AWS RDS database instance.
This document provides steps to create an S3 bucket in AWS and upload and move files within the bucket. It begins by signing into the AWS console as a root user and searching for S3. It then outlines 23 steps to create a bucket, upload a file, and move that file into a new folder within the bucket. The overall aim is demonstrated - to create an S3 bucket and work with files within it.
Dr. M. Pyingkodi of the Department of MCA at Kongu Engineering College in Erode, Tamil Nadu, India wrote a document about working with AWS EC2 instances. The 14 step process began by opening a browser to search and select EC2 instances on AWS. It then covered downloading an RDP file, using a PEM file to decrypt passwords, installing remote desktop and a Python compiler on the instance, and writing and executing a C program to test the setup. The result was that the AWS instance was successfully created and a sample program was executed.
The document discusses Amazon Web Services (AWS), which provides cloud computing services including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). It describes key AWS services such as Amazon EC2 for virtual servers, S3 for object storage, EBS for block storage volumes, RDS for SQL databases, and CloudFront for content delivery. It also covers AWS features like scalability, security, and tools for monitoring and messaging.
This document discusses various aspects of cloud security including cloud security challenges, areas of concern in cloud computing, how to evaluate risks, cloud computing categories, the cloud security alliance, security service boundaries, responsibilities by service models, securing data, auditing and compliance, identity management protocols, and Windows Azure identity standards. It provides information on policies, controls, and technologies used to secure cloud environments, applications, and data.
This document discusses cloud computing concepts presented by Dr. M. Pyingkodi of Kongu Engineering College in India. It covers topics such as virtualization, service-oriented architecture, grid computing, utility computing, cloud service models (IaaS, PaaS, SaaS), deployment models, essential cloud concepts, cloud types, reference models, communication protocols, REST, composability, connecting to the cloud, applications services, and the Chromium OS. Examples of cloud providers and technologies are provided throughout the document.
This document provides an overview of supervised machine learning algorithms. It explains that supervised learning involves training a model on labeled data so it can predict the correct output for new input data. Some examples of supervised learning tasks include image classification, disease prediction, and spam detection. Classification algorithms are used for predicting categorical outputs, like dog vs cat images. Regression algorithms predict continuous outputs, like housing prices. Common classification algorithms mentioned are random forest, decision trees, logistic regression, and support vector machines. Linear regression is also discussed as a basic regression algorithm that finds a linear relationship between variables.
The document discusses various unsupervised learning techniques including clustering algorithms like k-means, k-medoids, hierarchical clustering and density-based clustering. It explains how k-means clustering works by selecting initial random centroids and iteratively reassigning data points to the closest centroid. The elbow method is described as a way to determine the optimal number of clusters k. The document also discusses how k-medoids clustering is more robust to outliers than k-means because it uses actual data points as cluster representatives rather than centroids.
The document discusses feature engineering for machine learning. It defines feature engineering as the process of transforming raw data into features that better represent the data and improve machine learning performance. Some key techniques discussed include feature selection, construction, transformation, and extraction. Feature construction involves generating new features from existing ones, such as calculating apartment area from length and breadth. Feature extraction techniques discussed are principal component analysis, which transforms correlated features into linearly uncorrelated components capturing maximum variance. The document provides examples and steps for principal component analysis.
This document discusses normalization in database management systems (DBMS). It defines normalization as a process of decomposing complex relations into simpler, stable relations to eliminate inconsistencies, redundancies, and anomalies during data modification. The document outlines several normal forms including 1NF, 2NF, 3NF, and BCNF, and provides examples to illustrate the conditions that make a relation qualified for each normal form. The goal of normalization is to minimize data redundancy, reduce update anomalies, and simplify the relational design.
Relational databases use relational algebra and relational calculus to manipulate data. Relational algebra consists of operations like select, project, join, and divide that take relations as inputs and outputs. Relational calculus specifies queries using predicates and quantifiers without describing how to retrieve data. Structured Query Language (SQL) is the standard language used to communicate with relational database management systems. SQL allows users to define schemas, retrieve, insert, update, and delete data.
This document discusses transaction processing in database management systems (DBMS). It describes the ACID properties that transactions must satisfy - atomicity, consistency, isolation, and durability. An example of a fund transfer transaction is provided to illustrate these properties. Concurrency control is discussed as a mechanism for allowing concurrent transactions while maintaining isolation. The concepts of schedules, conflicting instructions, conflict serializability, and view serializability are introduced for evaluating the correctness of concurrent transaction executions.
The document discusses Internet of Things (IoT) frameworks. It describes that an IoT framework consists of interconnected components like sensors, gateways, apps, and data/analytical platforms that enable machine-to-machine interactions by providing secure connectivity and reliable data transfer. Real-time Innovations and Cisco are mentioned as examples of IoT framework companies that provide connectivity software and platforms for industrial IoT systems. Salesforce's IoT cloud platform is also summarized, which uses Apache technologies like Kafka, Spark, and Cassandra to process and store IoT data.
The document discusses key concepts in database management including primary keys, candidate keys, alternate keys, and foreign keys. It defines primary keys as columns that uniquely identify rows in a table. Candidate keys are attributes that could serve as primary keys. Alternate keys are candidate keys that were not selected as the primary key. Foreign keys link data between tables by referencing the primary key of another table. Maintaining proper keys is important for uniquely identifying rows, enforcing data integrity, and establishing relationships between database tables.
Serializability is a concept that helps check if schedules are serializable. A serializable schedule always leaves the database in a consistent state. Non-serial schedules may cause inconsistencies, so serializability checks if they can be converted to an equivalent serial schedule to maintain consistency. Different types of serializability include view serializability and conflict serializability. View serializability requires schedules be view equivalent to a serial schedule with matching initial reads, final writes, and update reads. Conflict serializability converts a schedule by swapping non-conflicting operations, where two operations conflict if they are in different transactions, access the same data item, and one is a write.
Virtualization allows the creation of virtual versions of servers, desktops, storage, and operating systems that can run simultaneously on a single physical machine. It provides benefits like consolidation of resources and isolation of systems. There are different types of virtualization including hardware, operating system, server, and storage virtualization. A hypervisor manages shared access to physical hardware resources and allows for the operation of multiple guest virtual machines on a single host machine. Machine imaging captures the state of a system to enable portability and deployment of virtual machines. Tools like VMware vSphere provide platforms for implementing virtualization and managing virtual infrastructures at large scale across servers, storage, and networks.
Cloud security consists of policies, controls, procedures and technologies that work together to protect cloud systems, data and infrastructure. It secures cloud environments against external and internal threats through authentication, traffic filtering and configuring security based on business needs. Key challenges include attacks moving faster than protections can be implemented and ensuring security audits and adoption of new technologies do not introduce risks. Responsibilities are divided between the customer and provider based on the cloud service model used.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
1. IoT Industry Adaptation of AI
Dr.M.Pyingkodi
Dept of MCA
Kongu Engineering College
Erode,Tamilnadu,India
2. IoT Industry Adaptation of AI
AI uses machine learning and deep learning to better analyses data and make
decisions.
• To production data to improve failure prediction and maintenance planning.
• Preventing Future Problems
• More accurate demand forecasting and less material waste.
• Preventing future problems – equipment functioning.
• Forecasting of raw material price.
• Quality control.
• Creative Generating
ML algorithms are employed to mimic the design process utilized by engineers.
Using this technique, manufacturers may quickly produce hundreds of design options
for a single product.
• Robotics
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
3. AI and IOT
• AI enables the IOT device to use gathered big data to better analyze learn and make decisions
without the need for a human.
• To create more efficient IOT operations to improve human machine interactions and enhance data
migration and analytics.
AI – Simulation of human intelligence processing by machine.
Example
natural language processing
Speech recognition
Machine vision.
Applications
Smart cities
Smart retail
Smart home
Enterprise and Industrial
Social media and human resources
Autonomous delivery robots
Healthcare
Robots in manufacturing
Self-driving car
Retail analytics
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
4. IOT and AI – Industry 4.0
Industrial Internet of Things(IIOT) and Cyber Physical Systems
Smart, autonomous systems – Uses
Computer-Based Algorithm to Monitor and Control Physical Things like,
Machinery
Robots
Vehicle
Industry 4.0
Manufacturers are integrating new technologies, including
Internet of Things (IoT), cloud computing and analytics, and AI and machine learning into their
production facilities and throughout their operations.
smart factories are equipped with advanced sensors, embedded software and robotics that collect
and analyze data and allow for better decision making
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
5. Industry 4.0 Technologies
ERP
• Business process management tools
• Manage info across an organization
IoT
Connections between physical objects like sensors/machine with internet
IIoT
Industrial Internet of Things
Connections between people, data and machines – related to manufacturing.
Big Data
• Large set of structured/unstructured data
• Compiled, stored, organized and analyzed to reveal patterns, trends, associations and
opportunities.
Artificial Intelligence
• To a computer’s ability to perform tasks.
• Make decisions
• Historically require some levels of human Intelligence.
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
6. Industry 4.0 Technologies
M2M
• Machine to Machine
• Communication – between two separate machines through wireless/wired network.
Digitization
The process of collecting and converting different types of information into digital format.
Smart Factory
Invests in and leverages industry 4.0 technology, solutions and approaches.
Machine Learning
• Ability that computers have to learn.
• Improve on their own through AI.
Cloud Computing
To the practice of using interconnected remote servers hosted on the Internet to Store,
Manage and Process Information.
Real-time data processing
Abilities if computer systems and machines to continuously and automatically process data.
Provide real time / near time outputs and insights.
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
7. Industry 4.0 Technologies
Ecosystems
Entire Operations performed in the industry
Inventory planning
Financials
Customer relationships
Supply chain management
Manufacturing execution
Cyber Physical Systems (CPS)
Industry 4.0 – enabled manufacturing environment offers
Real time data collection
Analysis
Transparency across every aspect of manufacturing operation.
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
8. Benefits Of AI For IoT
1.Reduction in Downtime
Downtime- to the period of time in which a company's factory is not producing product.
• Increase productivity, lower costs decrease accidents.
• Production - series of processes
• One process is dependent on another process.
Snowball effect
If one process is down /delay serving other dependent processes so in a waiting stage.
• Factory- is not producing anything until that single process is fixed.
• Effect the markets where products are out of stock due to the failure
• Find ways to reduce this downtime.
AI Works For
• Trigger can be given by AI Self-diagnostic tests
• Sending emergency alerts to the Technicians
• Reassigning
• Resetting time line for other dependent processes
• Alerting the entire supply chain about the process change.
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
9. Benefits of AI for IoT
2. Preventative measures to reduce downtime
With AI assist – prevent downtime
1. ML
Analyzing data generated by these machines and train them
Taking preventing actions given through triggers
2. Identify maintenance requirements
performance maintenance
3. Identify patterns – causes disruption and schedule predictive maintenance
Predictive Maintenance
Minimizing downtime in production
Uses data collected from all machinery
AI solutions analyze incoming data and monitors all machines in manufacturing
Causes of Downtime
• Inefficient processes
• Human error
• Supply chain disruptions
• Inaccurate maintenance
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
10. Benefits of AI for IoT
3. Operational Efficiency
By reducing downtime and using preventative measures
-achieve operation efficiency
Predictive analysis on supply and demand side.
based on- AI Defect
• Historical data
• Current market conditions
• Political stability
• International market influence
• Catastrophic events occur in other parts of world
Catastrophic events -involving /causing sudden great damage/suffering Unfortunate
events.
These predictions used
Schedule a production capacity
Purchase of raw material
Plan workforce
Arrange transport capacity etc.,
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
11. Benefits of AI for IoT
4. Increased Risk Management
Organization struggling for not able to predict risks in future.
• Understanding of the data in hand
• Ability to decode various internal/external factors – May effect the organization
AI - trigger a rapid response
- prevent the large losses
5.New product and services
Use of AI – open up new opportunities to launch new products and services
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
12. Use of AI in IoT with Real Life Example : IIOT
Industrial Internet of Things devices in manufacturing are in automation, remote monitoring, supply
chain optimization, digital twins, and predictive maintenance.
• Increase productivity and uptime.
• Improve process efficiencies.
• Accelerate innovation.
• Reduce asset downtime.
• Enhance operational efficiency.
• Create end-to-end operational visibility.
• Improve product quality.
• Reduce operating costs.
• Optimize production scheduling.
• Improve overall equipment effectiveness (OEE).
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
13. Use of AI in IoT with Real Life Example : Smart Farming
• Built for monitoring the crop field with the help of sensors (light, humidity, temperature, soil moisture, crop
health, etc.) and automating the irrigation system.
• Location systems like GPS and Geographical Information Systems (GIS) and Satellite Imagery
• Sensors for monitoring humidity, water levels, Soil Ph, Sunshine, and temperature
• Agriculture specific software that merges agronomy and cybernetic to make farm management hassle-free
• Communication via Cellular IoT solutions and Low-power wide-area networks (LPWANs)
• Data Analysis systems that provide farmers real-time data on crop and animal health
Sensors -Soil, water, light, humidity, temperature management
Software - Specialized software solutions that target specific farm types or applications agnostic IoT platforms
Connectivity: cellular, LoRa
Location: GPS, Satellite
Robotics: Autonomous tractors, processing facilities
Data analytics: standalone analytics solutions, data pipelines for downstream solutions
Applications:
Precision Farming - IoT-based approaches that make farming more controlled and accurate
Precision Livestock Farming – Monitors
Automation in Smart Greenhouses
Agricultural Drones
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
14. use of AI in IoT with Real Life Example : Self driving Vehicles
Sense the road, map the road, negotiate your place on the road.
IoT can connect all types of device to the Internet to share information and use added-value. Autonomous
vehicles are thus connected to share information from the on-board sensors, as well as from smart phones of
pedestrians and cyclists, traffic sensors, parking detectors, etc.
Acoustic Sensors
used to collect sound, pressure and vibration data
Ultra Sonic Sensor
Ultra Sonic sensors are most suitable for shorter range.
RADAR Sensor
electromagnetic waves in the radio spectrum frequency.
to measure the distance of objects over wide distances.
LiDAR
LiDAR stands for Light detection and ranging.
easuring distances (ranging) by illuminating the target with laser light and measuring the reflection with a sensor
CAMERA
Camera can detect traffic signs, Traffic lights, pedestrian movement, lane markers, and temperature in case of
thermal camera’s.
GPS
GPS sensors are receivers with antennas that use a satellite-based navigation system with a network of 24
satellites in orbit around the earth to provide position, velocity, and timing information
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India
15. Use of AI in IoT with Real Life Example : HealthCare
Improving Diagnostic Accuracy
Remote Patient Monitoring
advantage of IoT sensors' internet connectivity to provide doctors and nurses with updates on patient
vitals.
Reducing Need For Follow-Up Visits
track patients' health once they leave the hospital, reducing the need for follow-up visits.
Reducing Wait Times
Identifying Critical Patients
Tracking Medical Equipment
Dr.M.Pyingkodi, Assistant Professor(Sr.G), MCA Department, Kongu Engineering College, Erode, Tamilnadu, India