Artificial Intelligence Based Rural E-Commerce Boosting Using Big Data

Following 40 years of reform and opening up, India's economy has achieved a new peak, with rural ecommerce emerging as a key driver of this expansion. As the state's policy continues to develop to encourage rural ecommerce, the sector has opened up a big historical opportunity, with the size of the market growing and the sector's social awareness rising rapidly. With the widespread use of big data networks, big data-driven, AI-powered e-commerce has also grown rapidly in recent years. The use of electronic commerce is more common in urban regions than in rural ones. As part of the plan for "revitalizing the countryside," widespread use of ecommerce in rural regions will be a major step toward bolstering the rural economy. The growth of this route has the potential to strongly encourage the modernization of antiquated production techniques in rural regions while also improving the accessibility and efficiency of the flow of agricultural goods inside India and so facilitating their eventual export. The third-party distribution model was used as the logistics approach, and agricultural items from Mysore City, such as paddy and vegetables, served as the primary research objects to illustrate the utility of the Novel Colony Algorithm in the context of rural e-commerce. The issue of the third-party distribution model is examined through the process of model building. In light of this, PyCharm is used to determine the shortest path and total cost using a novel colony algorithm. In this research, we evaluate the models and conduct analyses of the efficiency and cost issues that arise when changing the parameters.