Smart Factory Monitoring Platform

Project Overview
We are building a full-stack Industrial IoT platform that digitizes factory operations by turning each piece of shop-floor equipment into a real-time data source. Wireless sensors capture key parameters like temperature, speed, and downtime, streaming them to a cloud-native backend built with Python and modern JavaScript. The system replaces manual logs and spreadsheets with automated data collection, intuitive dashboards for operators, drill-down analytics for managers, and company-wide OEE tracking for executives. Key capabilities include real-time alerts, historical performance analysis, multi-shift reporting, and scheduled PDF/Excel exports. The platform is designed for scale, enabling deployment across multiple factories with minimal setup, significantly reducing manual work and enabling faster, data-driven decision-making at all levels of manufacturing.
Technology Stack
Application Showcase
User Interface
The application features a clean, intuitive interface designed for optimal user experience. Each screen was carefully crafted to provide easy navigation and clear information hierarchy.
- Responsive design across all devices
- Streamlined user flows
- Accessibility-focused interface
Development Process
Data Collection & Research Phase
In-depth analysis of industry competitors and existing platforms. Stakeholder interviews and technical discovery sessions to capture user needs, KPIs, and operational requirements. Defined user journeys for logistics staff, admins, and analytics teams. Created detailed documentation, including a Product Requirements Document (PRD), sitemap, data flow diagrams, and API expectations. Regulatory research included maritime logistics standards and environmental compliance.
Discovery & UX Phase
Collaborated with stakeholders to convert business goals into wireframes and screen flows. Designed the UX for desktop dashboards, mobile control panels, and admin tools. Special focus on dark-themed UI for control room environments, real-time visual feedback, and accessibility. Prototyped screens for ship route monitoring, sensor health, cargo data, and AI forecasting overlays.
Back-end Development
Developed robust, scalable APIs in Python (Django/FastAPI) with modular architecture. Integrated ship telemetry, sensor inputs (temperature, pressure, diagnostics), and cargo data pipelines. Connected to PostgreSQL + Redis for storage and caching. Built core services for route logging, cargo tracking, energy conversion stats, waste handling validation, and user authentication. Used Celery with RabbitMQ for task queues, job scheduling, and bulk processing.
Front-end Development
Built a responsive SPA using React.js + TypeScript, styled with TailwindCSS. Implemented dynamic dashboards: ship movement maps, loading progress bars, smart filter panels, and live metrics. Added chart components for trends, sensor outputs, and efficiency KPIs. Integrated secure user sessions, admin roles, and real-time WebSocket support for live updates. Ensured UI scaling for desktop displays and control terminals.
Sensor Integration
Integrated multiple hardware and sensor input formats, including industrial Smart Meters, GPS beacons, and environmental IoT data. Data was normalized and processed through secure WebSocket streams or batched MQTT endpoints. Developed alerting logic for abnormal temperature, pressure, or energy output. Ensured accurate time-series storage and real-time diagnostics dashboarding. Enabled edge-to-cloud syncing for remote maritime zones.
Mobile App
Developed a cross-platform mobile app using React Native, supporting route monitoring, cargo updates, and system alerts. Real-time sync with backend APIs. Push notifications for port arrivals, delays, or anomaly triggers. Enabled offline data entry and delayed sync for at-sea scenarios with limited connectivity. Optimized UX for fast field interaction by port agents and onboard crew.
CRM System
Built a powerful internal admin system to manage ship profiles, cargo manifests, energy processing events, port stops, compliance logs, and fleet-wide analytics. Features included role-based access, auditing, custom filtering, and exportable reports. CRM integrates with external compliance bodies and partner networks via secure APIs.
CI/CD & Deployment
Deployed via Docker containers with infrastructure managed through Terraform. CI/CD powered by GitHub Actions with pre-prod staging, unit/integration test pipelines, and Sentry error tracking. Hosted on AWS with multi-zone redundancy and auto-scaling enabled. Web frontend deployed to Cloudflare Pages + CDN caching for optimal load speed.
QA & Testing
Implemented a layered testing approach: Unit tests (Pytest, Vitest) E2E tests (Playwright, Cypress) Manual QA covering transport logic, user roles, data filters, and dashboard rendering Security validation included XSS/CSRF protection, HTTPS enforcement, API throttling, and secure token management.
Post-Launch Support
Ongoing A/B testing for dashboards and alert UX. Monitoring usage heatmaps with PostHog. Conducted performance audits and scaling improvements. Set up user feedback loop with email follow-ups and dashboard survey prompts. Maintained weekly patch release cycle with hotfix capability. Prepared documentation and provided handover training for internal ops teams.
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