Democratization of artificial intelligence (AI) to small scale farmers: A framework to deploy AI models to tiny IoT edges that operate in constrained environments
ICPRAM 2020 - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods
Big Data surrounds us. Every minute, our smartphone collects huge amount of data from geolocations to next clickable item on the ecommerce site. Data has become one of the most important commodities for the individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have been largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only this is a huge missed opportunity for the big data companies, it is one of the significant obstacle in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the paper is to develop a framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.
Artificial Intelligence, Cow Necklace, Dairy Cloud, Edge, Hanumayamma, Hardware Constrained Model, IoT Device, Kalman Filter, Small Scale Farmers
Chandrasekar Vuppalapati, Anitha Ilapakurti, Sharat Kedari, Jaya Vuppalapati, Santosh Kedari, and Raja Vuppalapati. "Democratization of artificial intelligence (AI) to small scale farmers: A framework to deploy AI models to tiny IoT edges that operate in constrained environments" ICPRAM 2020 - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (2020): 652-657.