PROBLEM STATEMENTS
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TRACK 1: Smart Health Systems

Topic: Remote Patient Monitoring for Rural Healthcare.
Participants are required to develop a low-cost remote patient monitoring system using IoT-enabled wearable or portable devices that can measure vital signs such as heart rate, blood oxygen level (SpO₂), blood pressure, and body temperature. The system should transmit health data to healthcare providers through a mobile or web dashboard and generate alerts when abnormal conditions are detected. The solution should also support operation in areas with limited internet connectivity.
 
Topic: AI-Based Early Disease Prediction System
Participants are required to develop an AI-powered health prediction platform that analyzes data from wearable devices, patient medical records, and lifestyle information to identify early warning signs of potential diseases. The system should generate a risk score, provide predictive alerts to patients and doctors, and recommend preventive health measures. The solution should emphasize data-driven decision-making and personalized healthcare insights.
 
Topic: Smart Hospital Bed with Integrated Monitoring and Fall Prevention
Participants are required to design and develop a smart hospital bed system capable of detecting patient posture, movement patterns, and abnormal health conditions. The system should automatically identify risky situations such as fall attempts or sudden changes in vital signs and immediately alert nurses or caregivers. The proposed solution should improve patient safety, reduce hospital workload, and support real-time monitoring within healthcare facilities.
 
Topic: AI-Based Mental Health Monitoring Platform
Participants are required to develop a smart mental health monitoring platform that analyzes behavioral indicators such as sleep patterns, activity levels, voice characteristics, and wearable sensor data to detect early signs of mental health risks. The system should generate a stress or mood index, provide insights through a user dashboard, and recommend self-care or professional assistance when necessary.
 
Topic: Multimodal AI Health Monitoring System
Participants are required to design an AI-based multimodal health monitoring platform that integrates wearable sensor data, medical imaging information, and patient records to provide a holistic analysis of patient health. The system should utilize machine learning models to detect anomalies, predict potential health risks, and provide personalized healthcare recommendations.

TRACK 2: Agritech Solutions

Topic: Smart Irrigation Recommendation System
Participants are required to develop a smart irrigation platform that integrates IoT sensors, weather forecast data, and crop information to recommend optimal irrigation schedules. The system should monitor soil moisture levels in real time and provide actionable insights to farmers through a mobile application or dashboard. The goal is to improve water efficiency while maximizing crop yield.

Topic: Crop Price Prediction and Farmer Marketplace Platform
Participants are required to develop a machine learning-based system that predicts crop price trends across different markets using historical data and market indicators. In addition, the platform should provide a digital marketplace where farmers can directly connect with consumers, retailers, or restaurants to sell their produce without intermediaries.
 
Topic: Smart Greenhouse Environmental Monitoring System
Participants are required to develop an IoT-enabled greenhouse monitoring system that continuously tracks environmental parameters such as temperature, humidity, soil moisture, and CO₂ concentration. The system should analyze the collected data and provide recommendations or automated controls to maintain optimal conditions for plant growth. The solution should support real-time monitoring through a mobile or web interface.
 
Topic: Soil Health Monitoring and Water Optimization Platform
Participants are required to develop a digital platform that monitors soil parameters such as nutrient levels, pH, and moisture content over time. The system should analyze soil data and recommend appropriate agricultural practices, including crop rotation, fertilization strategies, and water usage optimization. The solution should help farmers adopt sustainable farming techniques while improving soil quality and productivity.
 
Topic: Voice-Based Smart Farming Assistant
Participants are required to develop a voice-enabled smart farming assistant that allows farmers to ask agricultural questions in their local languages. The system should provide responses through voice interaction and offer guidance related to crop diseases, weather conditions, fertilizer recommendations, and farming practices. Additionally, the platform may include a feature that enables farmers to rent agricultural equipment through a shared marketplace model.