Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems

Author(s): K. Aswarth and S. Vasavi * .

DOI: 10.2174/9781681089553122010013

A Framework of Smart Mobile Application for Vehicle Health Monitoring

Pp: 160-180 (21)

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  • * (Excluding Mailing and Handling)

Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

Abstract

The smart system integrates cloud computing and mobile computing, also known as mobile cloud computing. This smart system helps monitor the vehicle's health condition on any device, i.e., platform-independent. Using machine learning algorithms, the smart system helps predict vehicle health and maintain the vehicle's and the driving person's safety. The cloud computing used to deploy this smart system for monitoring the vehicle condition is the Google Cloud Platform. Google Cloud Platform provides various services like Computing and Hosting, Networking, Storage, etc., which help deploy and host web applications on Google Cloud using multiple services. One of the best securities is achieved using the Google Cloud Platform. Several layers are encrypted with specially designed algorithms for the safety of the customer data and applications. Google Cloud Platform helps provide data integrity, making it better for storing all the data. It also provides Denial of Service protection which helps realtime protection of servers for hosting the data. The smart system is deployed to only authenticated users eligible to monitor the vehicle's health condition. The health of the car may be tracked in the cloud and on every device with an internet connection and communication services. The mobile application is deployed from the webserver, facilitating secure and safe data browsing. The smart system is developed for displaying vehicle conditions dynamically, Google Maps for tracking the present vehicle location, and manual testing of the vehicle health by entering the values in the portal, which helps notification of risk, medium risk, and no risk of the vehicle condition using machine learning algorithm, which runs at the backend of the application.

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