IIoT PROGRAMS

IIoT PROGRAMS

DEPARTMENTPROGRAM
IOT PLATFORMIOT BASIC INTRODUCTION
GENERATOR MONITORING SYSTEMCOMMUNICATION & STANDARD INTERFACES
SMART INDUSTRIAL CONNECTITY
SMART PUBLIC TRANSPORTDATA SCIENCE AND ANALYTICS
SMART MANUFACTURINGMACHINE LEARNING
SMART CITYARTIFICIAL INTELLIGENCES
MAJOR PROJECT IN EACH PROGRAM

1. IoT BASIC INTRODUCTION

OBJECTIVES

  • To learn the concepts of IOT.
  • To identify the different technology.
  • To learn different applications in IOT.
  • To learn different protocols used in IOT.
  • To learn the concepts of smart city development in IOT.
  • To learn how to analysis the data in IOT

OUTCOMES

  • Apply the concepts of IOT.
  • Identify the different technology.
    • Apply IOT to different applications using Thingworx.
    • Analysis and evaluate protocols used in IOT.
    • Design and develop smart things in IOT using Thingworx.
    • Analysis and evaluate the data received through sensors in IOT.

    SCOPE

    • IIOT Designer,
    • IIOT Developer,
    • IIOT Analyst,
    • IIOT Tester
    • Entrepreneurship

    PROJECTS

    • Develop mini IoT Project
    • LDR based Darkness activation system
    • Home Security Alarm System Using Arduino
    • Arduino Alarm Clock
    • Portable Ultrasonic Range Meter

    2. COMMUNICATION & STANDARD INTERFACES

    OBJECTIVES

    • Address the real world problems and find the required solution.
    • Design the problem solution as per the requirement analysis done.
    • Study the basic concepts of programming/ hardware/ emulator for Raspberry pi/Arduino.
    • Fabricate and implement the mini project intended solution for project based learning.
    • Build and test the mini project successfully.
    • Improve the team building, communication and management skills of the students.

    OUTCOMES

    • Identify the requirements for the real world problems.
    • Building Mashup and Widgets using Thingworx.
    • Study and enhance software/ hardware skills.
    • Demonstrate and build the project successfully by hardware requirements, coding, emulating and testing.
    • To report and present the findings of the study conducted in the preferred task.
    • Demonstrate an ability to work in teams and manage the conduct of the research study

    SCOPE

    • IIOT Designer,
    • IIOT Developer,
    • IIOT Analyst,
    • IIOT Tester
    • Entrepreneurship

    PROJECTS

    • Smart Dustbin based
    • Obstacle Avoiding Robot
    • Keypad Security for Home Automation

    3. SMART INDUSTRIAL CONNECTIVITY

    OBJECTIVES

    • To gain knowledge of installing Android Studio and Cross Platform Integrated Development Environment.
    • To learn designing of User Interface and Layouts for Android App.
    • To learn how to use intents to broadcast data within and between Applications.
    • To use Content providers and Handle Databases using SQLite.
    • To introduce Android APIs for Camera and Music system.
    • To discuss various security issues with Android Platform.

    OUTCOMES

    • Experiment on Integrated Development Environment for Android Application Development.
    • Design and Implement User Interfaces and Layouts of Android App.
    • Use Intents for activity and broadcasting data in Android App.
    • Design and Implement Database Application and Content Providers.
    • Experiment with Camera and music systems.
    • Develop Android App with Security features.

    SCOPE

    • Android Developer and Android Tester
    • Entrepreneurship

    PROJECTS

    • Smart Genset
    • Smart Street Light

    4. DATA SCIENCE AND ANALYTICS

    OBJECTIVES

    • This course will serve as a comprehensive introduction to various topics in machine learning.
    • Conceptualization and summarization of big data and machine learning, trivial data versus big data, big data computing technologies, machine learning techniques, and scaling up machine learning approaches.
    • To provide Conceptualization and summarization: Representation of data. Modeling of machine learning techniques. Application of big data computing technologies.
    • To provide Trivial data versus Big data: Representation learning. Publicly available datasets. Scalability and Scaling up techniques. Report writing using Latex.

    OUTCOMES

    • At the end of the course the students should be able to design and implement machine learning solutions to classification, regression, and clustering problems; and be able to evaluate and interpret the results of the algorithms.
    • Ability to identify the characteristics of datasets and compare the trivial data and big data for various applications.
    • Ability to select and implement machine learning tech
    • niques and computing environment that are suitable for the applications under consideration.
    • Ability to solve problems associated with batch learning and online learning, and the big data characteristics such as high dimensionality, dynamically growing data and in particular scalability issues.

    SCOPE

    • Business Analyst,
    • Product Analyst,
    • Machine Learning Engineer,
    • Data Scientist

    PROJECTS

    • Smart Transportation

    5. MACHINE LEARNING

    OBJECTIVES

    • To provide Big data computing environment: Modern data analytics technologies like Hadoop and MapReduce. Suitable programming languages like Python, Java and C. Big data friendly machine learning scikit-learn libraries. Software platforms like Matlab or R.
    • To provide Machine learning techniques: Three phases of machine learning. types of learning support vector machine. decision trees and random forests. deep learning.
    • To provide Scaling up machine learning: Dimensionality reduction techniques like principal component analysis and feature hashing. Online processing technique called stochastic gradient descent. Big data machine learning models.

    OUTCOMES

    • Ability to understand and apply scaling up machine learning techniques and associated computing techniques and technologies.
    • Ability to recognize and implement various ways of selecting suitable model parameters for different machine learning techniques.
    • Ability to integrate machine learning libraries and mathematical and statistical tools with modern technologies like hadoop and mapreduce.

    SCOPE

    • Business Analyst
    • Product Analyst
    • Machine Learning Engineer
    • Data Scientist

    PROJECTS

    • Smart Manufacturing

    6. ARTIFICIAL INTELLIGENCES

    OBJECTIVES

    • To create appreciation and understanding of both the achievements of AI and the theory underlying those achievements.
    • To introduce the concepts of a Rational Intelligent Agent and the different types of Agents that can be designed to solve problems
    • To review the different stages of development of the AI field from human like behavior to Rational Agents.
    • To impart basic proficiency in representing difficult real life problems in a state space representation so as to solve them using AI techniques.
    • To create an understanding of the basic issues of knowledge representation Logic & blind & heuristic search, as well as an understanding of other topics such as minimal, resolution, etc. that play an important role in AI programs.
    • To introduce advanced topics of AI such as planning, Bayes networks, natural language processing and Cognitive Computing

    OUTCOMES

    • Demonstrate knowledge of the building blocks of AI as presented in terms of intelligent agents.
    • Analyze and formalize the problem as a state space, graph, design heuristics and select amongst different search.
    • Develop intelligent algorithms for constraint satisfaction problems and also design intelligent systems for Game Playing
    • Attain the capability to represent various real life problem domains using logic based techniques and use this to perform inference or planning.
    • Formulate and solve problems with uncertain information using Bayesian approaches.
    • Apply concept Natural Language processing to problems leading to understanding of cognitive computing.

    SCOPE

    • AL Developer and AI Analyst
    • Data Scientist

    PROJECTS

    • Smart City Project

    PROJECTS UNDER IIoT

    • Access control to restricted areas and detection of people in non-authorized areas.
    • Asset indoor location by using active (ZigBee) and passive tags (RFID/NFC).
    • Assistance for elderly or disabled people living independent.
    • Cold Chain Monitoring and Smart Tracking
    • Control micro-climate conditions to maximize the production of fruits and vegetables and its quality.
    • Control of CO2 emissions of factories, pollution emitted by cars and toxic gases generated in farms.
    • Control of conditions inside freezers storing vaccines, medicines and organic elements.
    • Control of rotation of products in shelves and warehouses to automate restocking processes.
    • Control of routes followed for delicate goods like medical drugs, jewels or dangerous merchandises.
    • Control remotely the swimming pool conditions.
    • Control the exact conditions of plants grown in water to get the highest efficiency crops.
    • Detect leakages and wastes of factories in rivers.
    • Detection of gas levels and leakages in industrial environments, surroundings of chemical factories and inside mines.
    • Detection of windows and doors openings and violations to prevent intruders.
    • E-Health Sensor Platform for Biometric and Medical applications.
    • E-Health: Low Cost Sensors for Early Detection of Childhood Disease
    • Energy and water supply consumption monitoring to obtain advice on how to save cost and resources.
    • Energy consumption monitoring and management.
    • Environmental monitoring by Public Transportation.
    • Information collection from Can Bus to send real time alarms to emergencies or provide advice to drivers.
    • Intelligent and weather adaptive lighting in street lights
    • Intelligent Highways with warning messages and diversions according to climate conditions and unexpected events like accidents or traffic jams.
    • Liquid detection in data centers, warehouses and sensitive building grounds to prevent break downs and corrosion.
    • Measurement of water pressure in water transportation systems.
    • Monitoring and optimization of performance in solar energy plants.
    • Monitoring greenhouse conditions to develop new products in the food industry.
    • Monitoring of combustion gases and premptive fire conditions to define alert zones.
    • Monitoring of conditions inside museums and art warehouses.




      What is 8 + 2 ?