Local Serve: Equitable Dynamic Pricing for Local Services

The goal of Local Serve: Equitable Dynamic Pricing for Local Services is to tackle the difficulties involved in setting a dynamic and fair price for local services. Nevertheless, traditional pricing models sometimes overlook the socioeconomic diversity of communities, resulting in price differences that may make inequality worse. With LocalServe, dynamic pricing is approached in a new way that considers the particulars of each local service as well as the state of the economy in the communities they serve. The approach involves integrating machine learning algorithms with data-driven insights to develop a dynamic pricing system that prioritizes sustainability, accessibility, and equity. It can ascertain the cost of various services by utilizing our data-driven insights, which consider supply and demand. Additionally, the system strives to offer consumers prompt and effective assistance. The employee's details will be updated for the customer, and the job will be assigned to the local person closest to them. This paper takes a comprehensive approach to improving the effectiveness and accessibility of neighborhood services. This significantly improves resident lives and promotes a more dynamic local environment by fusing technology, cooperation, and community involvement. This accomplishment will serve as a testament to the possibility of creative ways to revolutionize grassroots service delivery.