Sector: Food

Problem: There is a lack of Reliable data for production estimation, production planning, and market creation.

Solution: FOODPRINT™ is a produce aggregation and food traceability solution which aggregates the farm produce and implements food traceability using technology such as BLOCKCHAIN to capture the information of the product at various points in the supply chain such as production, processing, and distribution.

Problem: Most fruits and vegetables have a limited shelf life and considering the time it takes for them to go from farm to table. So there is a need to develop solutions for managing logistics operations of perishable products.

Solution: Temphawk is a sensor system to monitor and track the movement of perishable goods from farm-to-table. The startup’s system tracks temperature and humidity and records data every 10 minutes thereby giving near real-time updates via a smartphone application.

Problem: In today’s fast-paced urban life where time is very precious, if people didn’t have to do any cooking, it would save a large fraction of half a billion people, especially, women in India, approximately 3 hours a day of their lives. Working couples or roommates struggle with balancing work and putting hours of efforts in the kitchen at the end of a tiring day after work. The objective aims to describe a platform that leverages the amalgamation of technology and the art of cooking to save time and effort put in the process of cooking. 
Solution: The machine comes loaded with all the spices that are needed for cooking (stored permanently in spice boxes), and the user can add vegetables needed for cooking, and the machine then takes over. In the works is an app through which users will select the dish of their choice. The machine then indicates the canisters that need to be loaded with fresh ingredients, chopped vegetables or rice for example.

Problem: The rise in obesity rates and issues associated with poor nutrition both in the US and other countries worldwide has encouraged numerous researchers to develop mobile applications or online platforms that promote healthier lifestyle choices. To aid food enthusiasts, in their quest for wellness and fitness it is important to introduce a platform for letting people know how much calories they are intaking while consuming the dishes.
Solution: A model that combines a deep convolutional neural network (CNN) with YOLO, a state-of-the-art detection strategy.  The model is trained using a wide database of food images. The initial step in the understanding of an image is the extraction of main features such as edges. Once a food dish has been recognized through its image provided, the dish needs to be broken down into its ingredients, and the nutritional components of the dish calculated. This is done by using food mapping via the Food Data Central database. 

Problem: Due to the ongoing Covid pandemic, it is important that cafes and restaurants are allowed to be operational, keeping in mind that they should follow the enhanced safety measures and operational procedures in line with the latest FSSAI guidelines to mitigate risks and minimize food contamination and risk of the COVID-19 transmission while maintaining the hygiene of the food being cooked and served, one of the most important guidelines being avoiding of crowding situation in the premises. There is a need of a technological solution that helps in keeping a check if the cafes and restaurants are following the Covid protocols effectively and maintaining hygiene in their premises and cooking habits. 
Solution: The HungerBox platform is using AI/ ML to regulate user flow into cafeterias and enables decongestion and enables enhanced crowd management, this includes rigorous checks on operations personnel and a tech-led monitoring system that encompasses a 360-degree view of cafeteria operations. Using AI and machine learning, eleven different records would be maintained at partner kitchens, including several logs for sanitization, cooking temperature, cleaning checklists and for premises.

Problem: Customers seek convenience coupled with healthy food options. This has increased the demand for smart vending machines that display calorie counts, provide hot or cold delivery and offer several payment options.

The objective is to design a smart vending machine leveraging the use of AI for a better customer experience

Solution: The Cloud Vending machine uses computer vision and facial recognition technology to identify customers and merchandise. This smart vending machine uses AI, IoT sensors and deep learning capabilities to provide product recommendations, targeted advertising, smart inventory management and easy integration with other business systems.