Post-Harvest Storage Monitoring for a Small Farm Cooperative
Challenge
A small agricultural cooperative specializing in potato and vegetable cultivation faced consistent challenges in maintaining optimal conditions in their storage facilities (warehouses/cellars) after harvest.
These issues led to:
Crop Spoilage and Quality Degradation
Inconsistent temperature and humidity levels within storage areas often resulted in premature sprouting, rot, or mold growth, significantly reducing the marketable yield.
Manual and Infrequent Monitoring
Staff had to manually check temperatures and humidity using basic thermometers, which was time-consuming, prone to human error, and provided only snapshots, not continuous data. Critical changes could go unnoticed for hours.
Lack of Proactive Alerts
There was no system to alert farmers immediately when conditions deviated from ideal ranges, making it impossible to take corrective action before substantial damage occurred.
No Historical Data for Analysis
Without continuous data, the cooperative couldn't analyze past storage conditions to understand why spoilage occurred or how to optimize storage for future harvests.
A small agricultural cooperative specializing in potato and vegetable cultivation faced consistent challenges in maintaining optimal conditions in their storage facilities (warehouses/cellars) after harvest.
These issues led to:
Crop Spoilage and Quality Degradation
Inconsistent temperature and humidity levels within storage areas often resulted in premature sprouting, rot, or mold growth, significantly reducing the marketable yield.
Manual and Infrequent Monitoring
Staff had to manually check temperatures and humidity using basic thermometers, which was time-consuming, prone to human error, and provided only snapshots, not continuous data. Critical changes could go unnoticed for hours.
Lack of Proactive Alerts
There was no system to alert farmers immediately when conditions deviated from ideal ranges, making it impossible to take corrective action before substantial damage occurred.
No Historical Data for Analysis
Without continuous data, the cooperative couldn't analyze past storage conditions to understand why spoilage occurred or how to optimize storage for future harvests.
Solution
Our team developed a Storage Monitoring Solution leveraging ThingsBoard, specifically designed to provide essential environmental insights.
The solution comprised:
Simplified Data Ingestion Layer
We set up generic MQTT integration within ThingsBoard. This allowed the cooperative's chosen low-cost temperature and humidity sensors (which broadcast data via MQTT, typically through a local gateway or Wi-Fi) to easily push their readings to the platform. We provided clear instructions for sensor configuration.
Basic Asset & Device Management
We structured the storage areas within ThingsBoard, defining each storage room/cellar as an 'Asset' and linking the respective temperature/humidity sensors as 'Devices'. This provided a logical overview of the entire storage infrastructure.
Essential Rule Engine for Alerts
We configured ThingsBoard Rule Chains to monitor incoming sensor data. Simple rules were set up to:
- Detect when temperature or humidity values exceeded or fell below predefined thresholds (e.g., temperature above 10°C or below 4°C for potatoes).
- Trigger immediate email notifications to key personnel (e.g., farm manager, storage supervisor) when an alert condition was met.
User-Friendly Monitoring Dashboard
We designed a clean and intuitive dashboard within ThingsBoard. This dashboard provided:
- Real-time display of current temperature and humidity for each storage area.
- Historical graphs showing trends over hours, days, or weeks.
- A simple alert log.
Historical Data Access
The platform automatically stored all sensor data, allowing the cooperative to review past conditions, identify patterns, and correlate environmental factors with spoilage events.
Our team developed a Storage Monitoring Solution leveraging ThingsBoard, specifically designed to provide essential environmental insights.
The solution comprised:
Simplified Data Ingestion Layer
We set up generic MQTT integration within ThingsBoard. This allowed the cooperative's chosen low-cost temperature and humidity sensors (which broadcast data via MQTT, typically through a local gateway or Wi-Fi) to easily push their readings to the platform. We provided clear instructions for sensor configuration.
Basic Asset & Device Management
We structured the storage areas within ThingsBoard, defining each storage room/cellar as an 'Asset' and linking the respective temperature/humidity sensors as 'Devices'. This provided a logical overview of the entire storage infrastructure.
Essential Rule Engine for Alerts
We configured ThingsBoard Rule Chains to monitor incoming sensor data. Simple rules were set up to:
- Detect when temperature or humidity values exceeded or fell below predefined thresholds (e.g., temperature above 10°C or below 4°C for potatoes).
- Trigger immediate email notifications to key personnel (e.g., farm manager, storage supervisor) when an alert condition was met.
User-Friendly Monitoring Dashboard
We designed a clean and intuitive dashboard within ThingsBoard. This dashboard provided:
- Real-time display of current temperature and humidity for each storage area.
- Historical graphs showing trends over hours, days, or weeks.
- A simple alert log.
Historical Data Access
The platform automatically stored all sensor data, allowing the cooperative to review past conditions, identify patterns, and correlate environmental factors with spoilage events.
Results
The implementation of our Solution provided immediate benefits for the small farm cooperative, directly addressing their critical challenges:
Reduction in Post-Harvest Spoilage
Continuous, real-time monitoring and timely alerts allowed the cooperative to identify and rectify adverse storage conditions much faster, significantly reducing losses from rot and spoilage.
Eliminated Manual Checks and Errors
The automated system removed the need for time-consuming and error-prone manual temperature checks, freeing up staff and ensuring data accuracy.
Improved Product Quality and Marketability
By consistently maintaining optimal storage conditions, the quality of stored crops remained higher, leading to better market prices and reduced rejections from buyers.
Proactive Problem Solving
Farmers received instant alerts for critical deviations, enabling them to take immediate corrective actions (e.g., adjusting ventilation, identifying faulty insulation) before extensive damage occurred.
Data-Driven Storage Optimization
Access to historical temperature and humidity data provided valuable insights, allowing the cooperative to refine their storage practices for future harvests, leading to continuous improvement.
The implementation of our Solution provided immediate benefits for the small farm cooperative, directly addressing their critical challenges:
Reduction in Post-Harvest Spoilage
Continuous, real-time monitoring and timely alerts allowed the cooperative to identify and rectify adverse storage conditions much faster, significantly reducing losses from rot and spoilage.
Eliminated Manual Checks and Errors
The automated system removed the need for time-consuming and error-prone manual temperature checks, freeing up staff and ensuring data accuracy.
Improved Product Quality and Marketability
By consistently maintaining optimal storage conditions, the quality of stored crops remained higher, leading to better market prices and reduced rejections from buyers.
Proactive Problem Solving
Farmers received instant alerts for critical deviations, enabling them to take immediate corrective actions (e.g., adjusting ventilation, identifying faulty insulation) before extensive damage occurred.
Data-Driven Storage Optimization
Access to historical temperature and humidity data provided valuable insights, allowing the cooperative to refine their storage practices for future harvests, leading to continuous improvement.