Case Study
The Client
Ampere Electric is a pure-play Electric Vehicle player in the EV industry, providing a wide range of energy-efficient products and solutions. Headquartered in Bengaluru with its manufacturing plants in Ranipet Tamil Nadu, they are backed by Greaves Electric Mobility. They offer eco-friendly transportation solutions including electric scooters, cycles, three wheelers, and customized vehicles. They serve customers through dealers in India with the option to shop online.
Project Objective: IoT-based Telematic Platform
Business Value: Niveus provided a seamless, secure, and user-friendly experience for Ampere Electric users. We designed and developed a scalable IoT-based Telematic Platform available on Android and iOS devices that provides real-time insights into their fleet of connected vehicles.
The client was looking to build a Cloud-native Telematics platform capable of supporting two versions of vehicles: the current ones, connected to mobile phones via Bluetooth Low Energy, and newer generation vehicles equipped with IoT devices. The solution is expected to roll out in a phased manner. For the initial phase, the client aimed to create a scalable pilot involving 100 two-wheelers.
Business Solution
We enabled better customer experience and improved security with –
- A Cloud-native Telematics platform to generate and monitor data from their connected vehicles, providing users with information on general vehicle use and diagnostics
- Support for both legacy Bluetooth Low Energy (BLE) connected scooters as well as IoT-enabled scooters
- Augment the IoT telematics solutions with backend to support the consumer application
- The on-demand nature of Cloud-native platform that gives a phased approach to scaling with respect to their business goal
The Impact
Improved fleet management and fleet health for a multinational restaurant chain with a fleet of over 10k connected vehicles
Implementations
- The pilot phase consists of 80% IoT devices and 20% Bluetooth connected mobile phones. These devices generated data from different components of the vehicle, such as the battery, motor, and engine/flags
- Verne was used for interacting with MQTT clients and push the data to Pub/Sub topics
- Dataflow was used to process data on a real-time basis before loading it into the Cloud BigQuery
- BigQuery was the target layer with Looker Studio over its table to create dashboards for the monitoring team
- Google Cloud Storage was used for long term data storage & archival purposes
Low application latency
Technology Stack
BigQuery
Dataflow
Cloud BigTable
Cloud Pub/Sub
Cloud Storage
Looker Studio
