Sunday, October 30, 2022

Forecasting/predictive techniques on crop choices for rainfed agriculture

We mobilized the projects pertaining to the watershed, promoting the millets value-added companies like Earth365, Agricultural Policy Advisory Committee (APAC), Agricultural Produce Market Committee (APMC) in Sangli (Maharashtra), Yeshwanthpur (Karnataka), Salem (Tamil Nadu), Kangra (Himachal Pradesh). We developed an algorithm called Applied Engine on Nature (AEON) for creating a large dataset in terms of 1 zettabyte (~trillion Gigabyte). To create a large dataset across various sources of data both in real-time and batch processing. AEON handles large datasets of climate, environmental, soil samples, crop types, seasonal data of Rabi, Kharif rainfed farming, seed varieties of millets, rice, wheat, oil seed, fruits and vegetables, fisheries, goat farming, dairy farming, cotton, poultry farming, horticulture, composite fertilizer, organic farming, agricultural commodity price prediction. The algorithm is designed to create machine learning (ML) models, optimize the test and train datasets, achieving the right sizing for tabular and unstructured file types of real-time data streaming of videos and images. The Artificial Intelligence (AI) prediction accuracy improvement is close to the naturalistic decision. The application developed by the Nature labs team in the agricultural sector is named demand-tech for the determination of commodity pricing considering parameters like crop types, water irrigation, quality of seed and types, probability germination, and agricultural farming management. Dairy farming management related data, poultry advisory dataset, integrated farming, organic fertilizer manufacturing methods, soil moisture determination, and air moisture data acquisition is performed by the integration of Internet of Things (IoT), Google cloud-native service work procedure in Big Query, Vertex AI, SerpAPI, Python, TensorFlow, Keras framework for deep learning. Nature Labs is the team of agriculture specialist in food safety and smart agriculture, and technology partnering working in IBM global business service. Nature Labs project in charge of a professional team of consultancy and delivery and fully dedicating ourselves in working on solutions to the agriculture domain. Our team is comprised of 24 FTE with a Bachelor of Science in Information and Information Engineering from University. All the members have solid theoretical professional foundations, an average of 15 years of working experience in transnational corporations also accumulated rich practical experiences in agriculture. Nature Labs joined the IBM Corporation in 2009, after which we began to work on solutions for food and agriculture. After fourteen years of research finally being accepted by famous enterprises and awarded as an innovative solution in food safety and smart agriculture.

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