I am building a hybrid employee-tracking and productivity platform that must follow workers seamlessly from outdoor job sites straight into indoor facilities. Outdoors we will rely on Teltonika GPS devices; once a person moves inside, Kontakt.io or Estimote BLE beacons will take over. All raw location data should flow through Traccar, then into a custom back-end where it is fused, cleaned, and enriched. The end-goal is clear: measurable productivity improvement. I need automated reports that show employee movement tracking VS idle time. Reports should generate on a schedule (daily, weekly, or on-demand) and arrive as shareable PDF or CSV files. We also want the ability to access live data. So the data layer you build must be structured so we could expose real-time views. Core work items: • Configure Teltonika, Kontakt.io / Estimote, and Traccar so indoor-to-outdoor handoff is continuous and latency stays under a few seconds. • Develop the back-end logic (preferred stack is open to suggestion) that merges GPS and BLE events, stores them efficiently, and computes the two KPIs. • Build a reporting engine that plugs into this data store, formats the analytics cleanly, and emails/export them automatically. • Deliver clean, well-documented code—Docker-ready, with environment files, readme, and a short video or live session walking me through deployment. Acceptance criteria: devices switch seamlessly between technologies; location accuracy meets manufacturer specs; time-on-task and movement calculations align with sample ground-truth data I will supply; automated reports arrive without manual intervention. If you have proven experience with Traccar integrations, BLE beacons, or similar real-time IoT analytics, I’d like to review your approach and timeline.