I-Corps: Computer Vision-Based Intelligent Service Recommendation System

University Of Arkansas Little Rock, Little Rock AR

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a computer vision technology that aims to connect local service seekers and service providers to facilitate property maintenance work. Home improvement, maintenance and emergency spending increased by nearly 20% from last year, with individuals spending an average of $15,880. The proposed technology is designed to find local service providers faster using computer vision technology. The current online marketplace is more than $30 billion dollars annually and is projected to grow. Most of the transactions are offline even though there are existing online marketplaces. This difference may bring more service seekers like homeowners to the computer vision-based artificial intelligence (AI) marketplace. This I-Corps project is based on the development of artificial intelligence (AI) and machine learning (ML) solutions to identify and connect local service seekers and service providers more rapidly. The technology uses an algorithm to recognize and match the type of service needed from an image or video from a camera in a smart device and image-based service provider reviews. Using geolocation technology to find local service professionals, the proposed technology is used for schedule optimization in real time to keep service seekers informed about the requested service. Natural language processing-based language translation will be used to establish a communication channel between service seekers and service providers. The goal of the proposed technology is to create a highly scalable platform that may connect local service professionals faster using a computer vision-based recommendation system to facilitate home repair projects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.