HACKHERTHON

Urban homes and hostels generate large amounts of food waste, which is often discarded due to limited space and lack of proper management systems. This leads to environmental pollution and increased greenhouse gas emissions. The proposed solution is a compact, space-efficient system that converts food waste into useful products like compost or liquid fertilizer. It is designed to be user-friendly, odor-controlled, and suitable for small living spaces, promoting sustainable waste management at the source.

Buildings are exposed to environmental stress, aging, and structural loads that can weaken their integrity over time. Traditional inspection methods are periodic and may fail to detect hidden damages early. This project proposes a real-time monitoring system using embedded sensors to continuously track parameters such as vibration, strain, and cracks. The system will analyze data to provide early warnings of potential structural failures, improving safety and enabling timely maintenance.

Desalination facilities play a crucial role in providing safe drinking water, but maintaining consistent water quality is a major challenge. Variations in salinity, pH, turbidity, and chemical levels can impact health and safety standards. This project proposes a smart monitoring system that uses advanced sensors and real-time data analysis to continuously track water quality parameters. The system will provide instant alerts and automated reports to ensure the output water consistently meets required safety and health regulations.

Rising energy consumption and safety concerns in urban homes demand smarter living solutions. This project proposes an energy-efficient smart home system that automatically manages lighting, heating, and cooling to reduce utility costs and carbon emissions. It also integrates smart intrusion detection, a voice-triggered emergency activation system, and remote safety monitoring features for women living alone. The system enhances both sustainability and personal security through intelligent automation and real-time alerts.

Hazardous environments such as nuclear facilities and chemical plants pose significant risks to human inspectors. Exposure to radiation, toxic gases, and extreme conditions can lead to serious health hazards. This project proposes the development of robust, autonomous robots capable of performing real-time inspections and environmental monitoring in such high-risk areas. The system aims to enhance safety, improve inspection accuracy, and minimize human exposure to dangerous conditions.

Many health conditions such as anemia, chronic fatigue, heat stress, and certain cancers often go undetected due to irregular monitoring and lack of early symptoms. This project proposes a wearable-based health analytics platform that continuously tracks vital signs and physical activity levels in real time. Using smart sensors and data analysis, the system provides early health insights and risk alerts to both users and doctors. It aims to support preventive healthcare through continuous monitoring and timely medical intervention.

Traditional farming methods often lead to water wastage, improper fertilization, and delayed detection of crop diseases. This project proposes a precision farming system using IoT sensors to monitor soil moisture and nutrient levels for targeted irrigation and fertilization. It also integrates AI-based crop disease detection through image analysis and provides voice-based crop advisory in regional languages. The system aims to improve crop yield, reduce resource wastage, and support farmers with smart, accessible technology.

Women in urban and rural areas often face safety risks due to poorly monitored or high-crime locations.Lack of real-time information and immediate assistance can increase vulnerability during emergencies.This project proposes an AI-powered system that analyzes location data, historical crime patterns, and environmental factors to predict potentially unsafe areas. It provides real-time alerts, route recommendations, and emergency assistance features to enhance personal safety and confidence while traveling.

Hiring processes can unintentionally include biases related to gender, ethnicity, background, or other factors, leading to unfair recruitment decisions. Traditional screening methods often lack transparency and accountability in identifying such biases. This project proposes an Agentic AI system that autonomously analyzes job descriptions, resumes, and evaluation patterns to detect and mitigate bias in real time. The system promotes fair, transparent, and inclusive hiring practices by ensuring candidates are assessed based on skills and merit.

Perishable goods such as food and pharmaceuticals require strict temperature and handling conditions throughout the supply chain. Lack of transparency and real-time monitoring often leads to spoilage, quality degradation, and financial losses. This project proposes an integrated system combining IoT sensors and blockchain technology to monitor storage conditions and securely record data at every stage of transportation. The system ensures traceability, prevents data tampering, and enhances quality assurance for perishable products.

Citizens often face challenges in accessing accurate and timely information from public service departments, especially due to language barriers and complex procedures. This project proposes an NLP-based chatbot capable of understanding and responding to complex queries in multiple local languages.The system will provide reliable information, guide users through government services, and offer 24/7 assistance. It aims to improve accessibility, efficiency, and inclusivity in public service communication.

Molten glass conveyor rollers operate under extreme temperatures and continuous mechanical stress,making them highly prone to wear and unexpected failures. Sudden roller breakdowns can disrupt production, cause material wastage, and lead to costly downtime. This project proposes an intelligent predictive failure detection system that uses embedded sensors and data analytics to monitor temperature, vibration, and mechanical strain in real time. By identifying early signs of wear or malfunction, the system enables preventive maintenance, improves operational efficiency, and enhances industrial safety.

Air pollution poses serious health and environmental risks, especially in rapidly growing urban areas.Lack of real-time monitoring and public awareness often prevents timely action to reduce exposure. This project proposes an IoT-based platform that continuously tracks air quality parameters such as PM2.5,PM10, CO2, and harmful gases using smart sensors. The system analyzes data in real time and sends alerts to users and authorities, enabling preventive measures and promoting healthier living environments.

Cyberbullying is a growing concern in digital environments, often going unnoticed or unaddressed due to the sheer volume of online interactions. This project proposes an NLP-based system that analyzes text and voice communications in real time to detect signs of cyberbullying. The system identifies harmful patterns, triggers alerts for users and administrators, and provides recommendations for intervention. It aims to create safer online spaces by enabling early detection and timely response to cyberbullying incidents.

The Open Innovation Track allows participants to build creative and original solutions for real-world problems across any domain. It encourages out-of-the-box thinking, innovation, and impactful problem-solving using technology.