Executive Summary : | India is the top producer of vegetables worldwide, however, it represents just one percent of world exports and wastes around 30-40%. Recent national initiatives in cold chain shows the Government of India’s focus for preserving agricultural products to reduce wastages, improve the gains to farmers, support urban consumers and increase export. Optimum storage condition for longer shelf life of fresh vegetables in a cold chain depends on temperature and relative humidity of the storage chamber. Fluctuation of these parameters during storage, transportation and transshipment is responsible for growth and survival of pathogenic microorganism and their toxins. Currently, most of our vegetable produces are consumed internally or are exported through air route. Sending large consignments through air is costly. Exporting through sea is risky as the produces may be spoiled en route. Therefore, there is a need to determine optimum temperature, humidity and other environmental parameters to be maintained so that microbial growths are under control and wastage is minimized. Monitoring the quality in a non-invasive manner during sea transportation requires the collection of huge volumes and varieties of data from different sensors, RFID and other IOT devices along the supply chain. Collecting, storing, cleaning and using these data for predictive analytics and visualization in real-time requires an affordable solution. This project aims to fill this void by design and prototype implementation of a techno-management framework for traceability, product quality assessment and real-time monitoring of fresh vegetable cold chain specifically for sea transport. This project has three components. The first component is to design the right information infrastructure. Here, the aim is to extend the existing standard by integrating data from IoT devices; design and validation of sensors, communication interfaces for streaming the traceability data to the cloud. The proposed information architecture can be integrated with a real-time system for cold chain monitoring during sea transport of fresh vegetables to distant countries. The second component on quality assurance aims to emulate the sea transport environment to experimentally find the optimal conditions for minimizing quality deterioration of vegetables typically exported from India. The data generated from the experiments can capture the relationships between quality level and environmental parameters and can be used for training supervised machine learning algorithms for predictive analytics. The third component is about online monitoring assessment of vegetable quality during sea export. This includes assessment of quality on local servers using handheld devices such as smartphones during transportation and cloud-based detailed analytics for assessment of remaining shelf life using past sensor data. The proposed framework will enable the exporters to take the right decisions to minimize loss and decrease wastage. |
