Collect, stream, log and analyze OBD II data using Raspberry Pi with offline sync and local alerting on a Highly Available computer layer
About the Client
Robert Boschprovides technology and services in various sectors and has a large development center in India for engineering and technology solutions, including several connected IoT solutions for automobiles and mechanical systems.
Analysis of Data sourced from 500+ vehicles in Realtime
Report generation in less than 1 hour
Highly available trigger notification enabled
The project demanded real-time monitoring, scaling of the ingestion layer to handle up to 500+ linked automobiles, management of offline data logging, live event detection, a user database, and an Android app for administration and user interface.
Deploy Raspberry Pi with OBD Bluetooth adaptor to collect car data using OBD II Protocol on the Fog layer.
Use MQTT to stream all data and enable offline sync.
Enable driver identification with voice recognition and profile creation.
Stream and sync data with IoT Green Grass, log in S3.
Enable local alerts for over speeding with Green Grass integration.
Build HA compute layer with 8+ EC2 instances, Load Balancer, and DynamoDB for driver session analysis and Lead foot detection.
Ensure cloud ingestion layer is highly available and scalable for 500+ cars.
CloudThat successfully implemented edge device for 500+ cars with live data and 99.9% availability and report generation in less than 1 hour.