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The ML Asset Management and Tracking System for Rahat Group, designed and implemented by Dwisetech, is an intelligent fleet and asset monitoring solution built to ensure operational efficiency, asset safety, and real-time visibility. The system integrates IoT sensors, machine learning, and geospatial tracking to provide continuous insights into vehicle health, driver behavior, and asset conditions.
Environmental Monitoring
Real-time temperature and humidity monitoring
Continuous condition tracking for sensitive assets
Alerts on abnormal environmental changes
Fuel & Battery Monitoring
Live fuel level monitoring
Battery health and status tracking
Early alerts to prevent breakdowns and downtime
Speed & Driving Behavior Monitoring
Real-time speed monitoring
Over-speed detection and alerts
Driver behavior insights for improved safety compliance
Geo-Fencing & Route Intelligence
Custom geo-fence creation
Alerts on route deviation from predefined geo-fences
Location tracking with route visualization
Safety & Incident Detection
Alerts on truck/vehicle accidents
Seat belt violation monitoring
Driver safety score insights for performance evaluation
Operational Control
Remote stop monitoring functionality
Centralized dashboard for asset oversight
Real-time alerts and notifications
With this solution, Dwisetech enabled Rahat Group to:
Achieve real-time visibility of fleet and assets
Improve driver safety and compliance
Reduce fuel misuse and operational losses
Enhance asset security through geo-fencing and alerts
Enable data-driven fleet management decisions
This project demonstrates Dwisetech’s expertise in ML-driven asset tracking, IoT integration, and large-scale fleet intelligence systems, delivering end-to-end solutions that combine hardware, software, and advanced analytics.
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