D.M.T. Sasindula, H.M.P.B Piyathilaka, M.J.M. Rasha , S. Gunawardhana
This project features the first phase of the design and development of a fleet monitoring system over cellular networks using mobile data. The system consists of an embedded device to be fixed at the vehicle and a server side application at the control room. All the data regarding the whole vehicle fleet is at the fingertips of the operators at the control room, which will be used for analysis and reporting.
Key Words: Fleet Monitoring, GPS, OBD, Tracking, Driver behavior analysis
Key tasks of a fleet monitoring systems is to assist the management of vehicles, people, and transportation-related assets and support the bookkeeping process. The Internet of
Things (IoT) is one of the most famous technologies in the modern world interconnecting all the devices around us. Traditional transportation systems can be enhanced using the power of IoT solutions.
This work features an IoT-based SaaS solution for fleet monitoring system named SL-Fleet. It is a cloud-based IoT solution designed for fleet tracking and fleet management features to provide users better service through a centralized server. The two most critical components of this system are the embedded IoT device implemented using RaspberryPi which is installed in target vehicles for data acquisition and the Cloud-based Web application which displays required information to its operators using a customizable cutting-edge GUI. Interconnection between the embedded device and the server is through cellular data networks. New technologies such as AWS, VueJs, Laravel, Zabbix, NiFi, Asteris telecommunication frameworks are used to implement this as an enterprise solution implementation.
- Vehicle location and traverse path tracking (live or on-demand)
- Query the OBD II data
- Query telemetry data
- Custom configuration for queried data and query timing
- Custom alarms for drivers and the operators
- Custom communication protocol between the embedded device and the central server
- Optional soft PABX for communication between the drivers and the central control station
- Optional alarms at accident prone areas courtesy of Sri Lanka Police accident data
- Reporting and ability for big-data analysis Project Contacts: Dr. Subodha Gunawardena (firstname.lastname@example.org)