AI for Internet of Things (IoT)

Revolutionize IoT with AI: Smarter, Faster, and More Efficient Connected Systems

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MODE
Online/ e-LMS

TYPE
Self Paced

LEVEL
Moderate

DURATION
3 Weeks

About

The program explores the application of AI in IoT systems, covering AI-driven data analytics, predictive maintenance, smart devices, and automation. Participants will learn how AI can process vast amounts of sensor data, making IoT systems more efficient, scalable, and intelligent.

Aim

This program focuses on how AI enhances IoT systems by enabling smart decision-making and automating processes in real-time. It emphasizes the integration of AI in IoT for optimizing operations, improving data analytics, and supporting intelligent systems.

Program Objectives

Learn to integrate AI into IoT systems for real-time decision-making.
Implement AI-driven data analytics for processing sensor data.
Gain proficiency in predictive maintenance with AI-powered IoT solutions.
Understand the challenges of security and privacy in AI-enabled IoT.
Build and deploy an AI-driven IoT system.

Program Structure

Introduction to IoT and AI
- Overview of IoT: Concepts and Applications
- Key Components of IoT Systems (Sensors, Actuators, Connectivity)
- Role of AI in Enhancing IoT Systems
IoT Architectures and Frameworks
- Layered IoT Architecture (Perception, Network, and Application Layers)
- IoT Communication Protocols (MQTT, CoAP, HTTP)
- Edge, Fog, and Cloud Computing in IoT
AI Fundamentals for IoT Systems
- Overview of Machine Learning and Deep Learning in IoT
- AI for Real-Time Data Processing in IoT
- Lightweight AI Models for Low-Power IoT Devices
Data Collection and Management in IoT
- IoT Data Streams and Sensor Data Processing
- Data Preprocessing for AI (Filtering, Normalization)
- Real-Time Data Ingestion with Apache Kafka and MQTT
Edge AI for IoT
- Deploying AI Models on Edge Devices (Raspberry Pi, NVIDIA Jetson)
- Edge Computing vs. Cloud Computing for IoT AI Applications
- Real-Time Decision Making at the Edge
AI-Driven Predictive Maintenance in IoT
- Using AI for Predictive Maintenance in Industrial IoT (IIoT)
- Time-Series Analysis and Anomaly Detection
- AI Techniques for Fault Detection and Diagnosis
Computer Vision in IoT
- Image and Video Processing for IoT Devices
- Real-Time Object Detection and Tracking
- Use Cases: Smart Surveillance, Autonomous Vehicles
Natural Language Processing (NLP) in IoT
- Voice Assistants and Speech Recognition in Smart Devices
- NLP for Home Automation and Wearables
- Sentiment Analysis and Voice Control in IoT Systems
AI for IoT Security and Privacy
- AI for Intrusion Detection and Network Security
- Privacy Concerns in IoT Data Collection and Processing
- Federated Learning and Privacy-Preserving AI
Energy Efficiency in AI-Driven IoT
- Power Management in IoT Systems
- Optimizing AI Inference for Low-Energy Devices
- AI Techniques for Extending Battery Life in IoT Devices
Real-Time Analytics and Decision Making in IoT
- AI for Real-Time Monitoring and Control
- Stream Processing with AI in IoT Systems
- Real-Time AI Applications: Smart Cities, Healthcare, Smart Grids
Final Project
- Develop an AI-based IoT system for a specific application.
- Example: Build a predictive maintenance system for industrial equipment or a smart home automation solution using AI.

Participant’s Eligibility

IoT engineers, data scientists, AI engineers, and embedded systems developers focusing on IoT solutions.

Program Outcomes

Master the integration of AI into IoT systems for smarter decision-making.
Proficiency in building AI-driven automation and predictive maintenance systems.
Hands-on experience in deploying AI models for real-time IoT data analytics.
Knowledge of security and privacy challenges in AI-enhanced IoT systems.

Fee Structure

Standard Fee: INR ~~4,998~~ USD 78

Discounted Fee: INR 2499 USD 39

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!

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Key Takeaways

Program Assessment

Certification to this program will be based on the evaluation of following assignment (s)/ examinations:

Exam	Weightage
Mid Term Assignments	50 %
Project Report Submission (Includes Mandatory Paper Publication)	50 %

To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.

Program Deliverables

Access to e-LMS
Real Time Project for Dissertation
Project Guidance
Paper Publication Opportunity
Self Assessment
Final Examination
e-Certification
e-Marksheet

Future Career Prospects

IoT AI Engineer
Embedded AI Developer
AI-Powered IoT Specialist
Predictive Maintenance Engineer
Smart City Solution Architect
Edge AI Developer

Job Opportunities

AI-powered IoT product development for industries like smart homes, smart cities, healthcare, and manufacturing
Companies leveraging AI for IoT-based automation and predictive maintenance
Startups focusing on edge computing and AI in IoT systems