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Case Study: Supply Chain
Smart Logistics Cloud
An advanced logistics management platform that integrates IoT sensors from thousands of vehicles into a centralized cloud dashboard for real-time monitoring and predictive maintenance.
ReactGolangKubernetes
The Challenge
The client had no way to predict vehicle failures, leading to costly downtime and disrupted delivery schedules. Data from various GPS and IoT providers was fragmented and incompatible.
Our Solution
Btechly built a unified data ingestion engine in Go that standardized cross-provider IoT streams. We implemented a predictive maintenance algorithm that uses historical sensor data to flag potential mechanical issues before they lead to breakdown.
We utilized a cloud-native approach, focusing on high availability and sub-second latency for critical operations. The integration layer was decoupled to allow for seamless third-party service connections without impacting the core engine.