The client needed a smart farm monitoring system capable of real-time air quality tracking across six barns using Renke sensors and USR-DR404 IoT gateways. The goal was to visualize NH₃, CO₂, PM, temperature, and humidity data live, trigger instant alerts, and manage access based on user roles (Admin, Operator, Viewer). The solution also had to comply with USDA/OSHA standards, support predictive analytics, and scale effortlessly to additional farms. The result was an intuitive, role-secured, AI-powered dashboard—future-ready for automation, growth, and regulatory reporting.
Sensor data resided in isolated OEM platforms, limiting real-time decision-making and delaying hazard recognition. Staff struggled with slow access and lacked centralized oversight across barn environments.
Threshold breaches for harmful gases were recorded manually, often after the fact. This reactive approach increased health risks for animals and reduced staff response efficiency during emergencies.
Different stakeholders—owners, supervisors, auditors—needed tailored views. A lack of role-based access made managing permissions cumbersome and exposed sensitive data to unauthorized users.
The client had to maintain precise, timestamped records to meet USDA and OSHA regulations on ammonia and COâ‚‚ levels, requiring automated logging and on-demand data exports.
Scaling to multi-farm operations demanded a modular and easily extensible system, capable of onboarding new barns and sensor types without costly rewrites or technical overhead.
Delivering a unified, real-time, role-aware platform that modernizes air quality monitoring with predictive analytics and scalable infrastructure.
All sensor outputs (NH₃, CO₂, PM, temp, RH) were aggregated in a time-stamped MongoDB stream. Data was served live to the UI using WebSockets, enabling instant visibility and analysis.
We introduced baseline models to forecast ammonia spikes using historical data. This ai air quality monitoring approach gave operators early warnings, improving animal safety and barn ventilation timing.
The AWS SNS module dispatched alerts instantly when readings exceeded thresholds. Operators received notifications, logged responses, and ensured accountability via built-in activity trails.
JWT-based authentication and role-based access control (RBAC) ensured that each user type—Admin, Operator, Viewer—saw only the barns and actions relevant to their responsibilities.
A guided import wizard allowed staff to add the initial six barns seamlessly, with the flexibility to onboard more locations later without requiring code or developer support.
An interactive dashboard displayed real-time levels of NH₃, CO₂, PM, temperature, and humidity, using color-coded visuals to highlight danger zones and support rapid decision-making.
Threshold-based rules automatically triggered AWS email alerts. Operators could respond promptly, acknowledge events, and maintain logs for transparency and future audits.
Users could manage multiple barns and locations from one login, with permissions defined per user. This streamlined operations across various farms with role-specific control.
Filtered CSV exports allowed users to generate reports by barn, date, or parameter. This ensured USDA/OSHA reporting was fast, accurate, and entirely digital.
Every login, logout, alert acknowledgment, and user creation was logged. This improved traceability, reinforced accountability, and supported internal and external audits.
Widgets flagged upcoming NH₃ or CO₂ spikes 2–3 hours in advance, helping operators respond proactively to hazardous conditions in any ammonia sensor barn.
MongoDB
JWT Auth
NestJS
AWS EC2
Kubernetes
AWS
Consolidated six disconnected OEM tools into one audit-ready dashboard, empowering managers with a unified view of all critical environmental data.
Color-coded live charts and instant email alerts reduced reaction time to dangerous ammonia levels from several hours to just minutes, significantly improving animal welfare outcomes.
Custom export tools made regulatory reporting effortless. Auditable, time-stamped logs aligned perfectly with USDA and OSHA standards, removing the need for manual logbooks.
Role-based access and full user tracking brought accountability to every action taken on the platform, from login to alert acknowledgment to configuration changes.
With plug-and-play onboarding, the client can easily add new barns or sensors, future-proofing the solution for long-term growth in the smart farming sector.
Predictive analytics flagged harmful ammonia patterns early, allowing preemptive ventilation adjustments and strengthening the platform's value as a true smart farm monitoring system.
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