{"id":5902,"date":"2018-02-05T14:15:15","date_gmt":"2018-02-05T13:15:15","guid":{"rendered":"https:\/\/www.intellias.com\/?p=5902"},"modified":"2023-09-15T13:40:05","modified_gmt":"2023-09-15T11:40:05","slug":"e2e-predictive-maintenance-software","status":"publish","type":"post","link":"https:\/\/intellias.com\/e2e-predictive-maintenance-software\/","title":{"rendered":"E2E Predictive Maintenance Software"},"content":{"rendered":"

Business challenge<\/h2>\n

Our client is a Canadian software firm that serves automakers with personalized, user-centric SaaS solutions, and\u00a0automobile maintenance software<\/span>. End customers use our client\u2019s software to process vehicle preventive maintenance requests from owners. Requests can be based on a maintenance schedule, advice from remote diagnostic systems, or predictions from a cloud-based machine learning system. Our client specializes in technology solutions for the automotive<\/a>, energy, and banking sectors.<\/p>\n

\"E2E<\/p>\n

Our client acquired a large contract with an international auto manufacturer to help the manufacturer\u2019s Canadian dealers schedule vehicle maintenance. To serve the large user base \u2013 all owners of vehicles by the manufacturer \u2013 our client started developing the online-based preventive maintenance software solutions for cars.<\/p>\n

Their biggest challenge for predictive maintenance software was handling a large volume of vehicle data, including data on the performance of individual vehicle parts. To analyze this data smartly, we proposed introducing consumer IoT solutions and machine learning algorithms as well as an online support system with high fault tolerance. Our client already had related experience with online systems but was looking for a partner with experience both in the automotive sector and with SaaS development to get things done with speed and quality. Their search led to Intellias, as our company is well known for its focus on the automotive sector and its experience with SaaS solutions across industries.<\/p>\n

Technology solution<\/h2>\n

We developed an automotive predictive maintenance software with online support system based on Microsoft Azure cloud services that processes requests for appointments and matches drivers with nearby dealer service centers.<\/p>\n

The online system also notifies drivers by phone message or email about the need to check parts that have exact maintenance schedules stated in the vehicle specifications, which are synchronized with the online system.<\/p>\n

Machine learning algorithms will recognize:<\/b>\u00a0<\/span><\/p>\n