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Due to busy schedules and a lack of tracking of food that is stored, a lot of food is wasted every day in households. According to the UNEP Food Waste Index Report 2021, India’s household food waste amounts to 50 kg per person per year, or over 68 million tons. In 2023, India would have produced over 68 million tons of food waste. Food waste is rising quickly every year. The following variables will affect food loss and waste (FLW) at the consumer level: improper food storage, including not using it before it goes bad. Partially used ingredients, preparing meals beyond necessity, and poor visibility of food in freezers are the main causes of food spoiling at home. According to data from the Food Safety and Standards Authority of India (FSSAI), one-third of India’s food is wasted or spoils before it is eaten. This can be minimized by tracking food in smart containers, which work for both packed and unpacked food. This can be used with or without a refrigerator.

The “Transit Guard” project represents a cutting-edge endeavour aimed at revolutionizing public transportation by implementing ticketless travel on buses and trains and tracking the number of passengers traveling. This project introduces a comprehensive system designed to enhance fare compliance, improve passenger convenience, and to avoid revenue losses due to ticketless traveling. Key components of the project include the development of a user-friendly mobile app for ticket purchase and validation, giving the number of passengers traveling in the bus and at the same time keeping track of how many passengers purchased the ticket through mobile app or offline ticket purchasing for each stop. “Transit Guard” not only curbs revenue losses for transit agencies but also fosters a culture of responsible travel and adherence to transit policies. By offering multiple ticketing options and ensuring accessibility, the project caters to all passengers, regardless of smartphone ownership. The result is an equitable, efficient, and secure public transportation experience the benefits both computers and transit providers, ultimately advancing the vision of fair and reliable transit systems.

Our method is to keep a close eye on the patient’s health and inform the person responsible for their care on a regular basis. Since it is not possible for an individual to always watch over a single patient in a hospital setting, the primary objective is to monitor the patient around-the-clock. There is going to be aWe employed an apparatus that continuously observed the patient and sent frequent updates to the attending physician, regardless of the physician’s location. This device also has an extra feature that allows it to sound an alarm to notify hospital staff members of a patient emergency.

The primary objective of this project is to develop a robust and secure system that uses blockchain technology as well as Ethereum and IoT sensors to create a transparent and automated irrigation management solution for farmers. The key components of this innovative system include IoT sensors for real-time data collection, smart contracts on the Ethereum blockchain for transparent and immutable record keeping, and a user-friendly interface for farmers to monitor and control their irrigation systems remotely. The blockchain will provide data security to avoid the problem of data manipulation; because the IoT components will produce large volumes of data, the data must be securely maintained.

Sharing traffic information on the vehicular network can help in the implementation of intelligent traffic management, such as car accident warnings, road construction notices, and driver route changes to reduce traffic congestion earlier. If the exposed traffic incident is incorrect, the driving route will be misleading, and the driving response may be in danger. The blockchain ensures the correctness of data and tampers resistance in the consensus mechanism, which can solve such similar problems. The traffic data are collected through the roadside units, and the passing vehicles will verify the correctness when receiving the event notification. We employ data collection, preprocessing, sentiment analysis, geospatial analysis, and machine learning techniques to automatically identify and categorize traffic events, such as accidents, congestion, or road closures, based on information shared by users on various social media platforms. The framework aims to provide accurate and timely insights into traffic conditions, enabling better urban planning and incident response.