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Problem Statements

IoT, VLSI & Embedded Systems

PS-3.1

Edge-AI Wearable Health Monitoring Ecosystem

Continuous physiological monitoring generates sensitive data. Design an Edge-AI enabled wearable health ecosystem capable of real-time anomaly detection with privacy-preserving federated learning.

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PS-3.2

AI-Assisted Rural Telemedicine Platform

Rural healthcare faces doctor shortages and connectivity issues. Develop an AI-assisted telemedicine platform combining voice-based decision support, low-bandwidth imaging, and vernacular language processing.

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PS-3.3

AI-Calibrated Biosensor for Lifestyle Diseases

Early detection of lifestyle diseases requires low-cost, accurate sensors. Design a biosensor system calibrated using AI and signal processing, integrated with mobile health platforms.

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PS-3.4

AI-Optimized Electric Vehicle Charging Infrastructure

EV adoption strains power grids. Develop an AI-optimized EV charging infrastructure that enables smart charging scheduling, dynamic pricing, grid-aware load balancing, and V2G integration.

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PS-3.5

AI-Driven IoT-Based Smart Energy Management System

Develop an AI-optimized smart energy system to monitor real-time building energy consumption, predict peak usage, and automate energy-saving actions.

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PS-3.6

Intelligent Traffic Signal Controller using Embedded AI

Fixed-time traffic signals fail to adapt to dynamic traffic conditions. Develop an embedded AI system to adapt signals in real-time.

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PS-3.7

Low-Power IoT-Based Air Quality Monitoring System

Urban and industrial air pollution requires continuous, fine-grained monitoring. Design an affordable, scalable, and low-power monitoring system.

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PS-3.8

Secure Embedded System for Industrial IoT Devices

Industrial IoT devices are vulnerable to firmware attacks and data tampering. Design a secure embedded system for industrial applications.

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PS-3.9

Autonomous Smart Irrigation System using IoT and AI

Traditional irrigation methods waste water. Design an autonomous system to monitor soil and weather to optimize irrigation.

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PS-3.10

Embedded Vision System for Industrial Quality Inspection

Manual quality inspection is slow and error-prone. Develop an embedded vision system for real-time defect detection.

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