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GPS Tracking & Equipment Management App for Mining Operations
- Why I developed
A mining company in South America needed a way to monitor heavy machinery and field teams across large, remote sites. Supervisors had no real-time visibility into machine locations, actual operating hours, or how much time was lost to idle periods. Field crews relied on paper logs and radio check-ins, so data was often incomplete, delayed, or lost. They needed a cross-platform app that worked on-site, even with poor connectivity, and gave managers access from anywhere.
- What This APP Solved
Real-time GPS tracking shows each machine's exact location, route history, and path logs per shift. Operation time tracking and idle detection replaced manual logging, giving managers accurate usage data for every piece of equipment. Operator assignments,...
- The Result
The App reduced equipment downtime by giving managers clear insight into idle periods and scheduling gaps. Transparency improved across the site, leading to better shift planning and smarter resource allocation. The offline sync was a game changer, because work in...
- Why I Am Sharing
This I built this project and wanted to share it as a real world example of how technology solves genuine problems in industries like mining. I cannot provide links, source code, or technical details due to a signed NDA, and I apologise for that. I hope this...
This is a really practical use case for GPS tracking. Real-time visibility for heavy equipment can save huge operational costs in mining. Curious — did you face any challenges handling connectivity issues in remote sites?
Thanks! Yes, connectivity was big challenge. The app runs a lightweight health check ping to the server at regular intervals to detect connection status. While offline, all GPS data and activity logs are queued locally with timestamps. Once the ping succeeds, the app syncs...
That’s a smart approach. Queueing the GPS data locally with timestamps and syncing once connectivity is restored is a really clean way to handle intermittent networks. Did you also implement any conflict resolution or data compression during sync to keep uploads efficient?
Good point! The main conflict I faced was with equipment logs. When a device goes offline mid-operation, the server already has part of that equipment's log from the real-time sync before disconnection. So when the offline data syncs back, some log entries already exist in the...
How did you handle GPS drift and battery drain from continuous location tracking, especially during long shifts?
GPS on mobile devices often reports noisy coordinates - jumps of 10-50 meters even when stationary. Running continuous high-accuracy GPS also kills battery fast on 8-12 hour mining shifts.
Good question.
For GPS drift, I implemented a filtering layer before storing coordinates. When the device is detected as stationary (speed below a threshold), incoming GPS points that fall within a defined radius of the last confirmed position are discarded rather than logged -...
For battery, continuous high-accuracy GPS wasn't sustainable. I used an adaptive polling strategy - high-frequency updates (every few seconds) only when the equipment is actively moving, and dropping to low-frequency pings (every 30-60 seconds) during idle detection. The shift...
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Here’s how the system actually works.
A stranger sees your offer.
They click.
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But getting the lead is only the beginning.
The system now needs to know:
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Where did they come from?
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Then things start to branch.
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If they book → the conversation changes.
If they don't respond → they enter another follow-up.
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If they buy → they leave the sales journey and enter another one.
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That's the part of automation I find interesting.
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Hey, I built the entire application end to end. The real challenge inside the CRM automation is the perfect stages tagging along each stage if & else coordinations.
I built the entire wireframe. I can share with you.
Noor — Merchant Admin & Operations Admin (Delivery Service)
Three production admin systems for a delivery service — built solo end-to-end, including real-time chat and billing logic.
Problem
A delivery service needed three separate operational systems working at once: a panel for merchants to manage their own orders and billing, a central ops panel for the company's own courier fleet, and a customer-facing tracking site — each with a completely different user and a different job.
Constraint
Real production traffic, existing users depending on the systems daily, and — on the merchant panel — real money moving through billing logic that had to be correct, not just functional-looking.
Solution
Merchant admin panel: built almost entirely solo (359 of 368 commits) — orders, tariffs, promo codes, invoices, reporting, real-time chat with customers/support (websocket), and later real billing logic (cash accounting, commission tracking, payment-status handling).
Central operations admin (cpanel) — the company's largest internal system: courier management, live GPS tracking, in-app chat, and the fleet-management/credit system for company-owned courier scooters. Built largely solo through its first year (~84% of commits in that period), then onboarded and reviewed a successor once my focus shifted to the merchant panel's billing work.
Customer-facing delivery website (Next.js 15, React 19): live GPS courier tracking with animated route rendering, rendering-performance and memory optimization, i18n, Framer Motion, OTP-based auth.
Result
Three systems still running in production today, each shipped and maintained by me for over a year. This is real, closed-source production work — not a personal or practice project.
359 of 368 commits solo on the merchant panel is a good way to put a number on scope. The part I'd want to know more about is the billing logic — cash accounting plus commission tracking for couriers gets messy fast when payouts and platform fees touch the same ledger. Did you...