Droughts, unpredictable rains, and pests can wipe out as much as half of a harvest. For Brazil, which supplies 40% of global coffee, these aren't hypothetical risks. Under extreme weather conditions, farms can lose an estimated 20% - 50% of annual yields. Brazil's coffee exports generated $10.37 billion in 2024 (Statista), making these losses economically devastating for both individual farms and the national economy.
Traditional farming relies on experience and scheduled interventions, but climate change and rising global demand have made this approach insufficient. On top of that, many plantations are located in remote regions, far from reliable infrastructure. Farmers face labor shortages precisely when they need more intensive monitoring and faster response time.
Edge computing changes this equation. By processing data locally and automating responses without depending on constant connectivity, platforms like ThingsBoard Edge allow farmers to monitor soil conditions, control irrigation, and prevent crop loss—even when the internet fails for days. This is exactly why Brazil's most progressive coffee farmers are adopting edge-enabled IoT solutions.
This article is the third part of our series on IoT in Brazil. In earlier stories, we explored Brazil's connectivity paradox, and how edge computing enables life-saving healthcare monitoring in remote communities. Now, we explore how the same technology protects Brazil's most valuable crop.
How Edge Computing Makes It Work
Remote coffee farms need an IoT platform that continues to operate when the Internet fails, and syncs with cloud for analytics when connectivity returns. ThingsBoard's Edge-Cloud architecture was designed precisely for this scenario. Here's how the components work together to provide continuous monitoring and automation regardless of network conditions:
Collect
ThingsBoard Edge integrates with any sensor type via the variety of supported protocols. In coffee farming deployments, this typically includes:
- Soil sensors: Moisture, pH, NPK nutrients, temperature (LoRaWAN/Modbus)
- Weather stations: Rainfall, humidity, wind, solar radiation (MQTT)
- Crop monitoring: Drone imagery, pest traps, disease detection cameras
- Equipment telemetry: Pump status, valve positions, water tank levels
All sensors transmit to local gateways, which aggregate and normalize data in real-time, no cloud connection required.
Connect
For sensor communication, LoRaWAN provides 5-15km range with minimal power consumption—ideal for coffee plantations where cellular coverage is spotty. Sensors can operate for years on battery power while continuously feeding data to the local edge gateway.
Visualize
ThingsBoard dashboards provide multiple visualization layers accessible from desktop or mobile:
- Farm overview: Interactive map displaying all sensor locations, current readings, and active alerts
- Zone details: Drill down into specific plots to see soil moisture trends, irrigation history, and yield comparisons
- Equipment status: Monitor pump operations, valve positions, and system health in real-time
- Historical analysis: Compare conditions across seasons, identify patterns, optimize resource allocation
Figure 1. Smart irrigation dashboard
Farm managers access these dashboards via web browser, even during internet outages. See how IoT data visualization works in practice.
Automate
ThingsBoard's Rule Chain engine transforms data into action via:
Complex multi-condition logic:
// Automated Irrigation Rule Example
IF (soil_moisture < 25%
AND weather_forecast.rain == false
AND water_reservoir > 40%)
THEN {
activate_drip_irrigation(duration: 2hrs, zones: affected_zones);
send_notification(manager, "Irrigation activated in Zone A");
}
Alert prioritization:
- Critical events (pest detection spike) → SMS + push notification
- Warnings (gradual pH drift) → Email summary
- Info (scheduled maintenance due) → Dashboard notification
These rules are executed locally on Edge, all without internet dependency. Explore our smart irrigation solution showing how to manage farming processes intelligently.
Figure 2. ThingsBoard Edge architecture for coffee farm deployment. Sensors communicate via LoRaWAN to the local gateway, which processes all data and automation locally. ThingsBoard Cloud provides long-term analytics and remote access when connectivity is available.
This architecture addresses the fundamental challenge of remote IoT: maintaining operational continuity when connectivity is unreliable. For Brazilian coffee farms hundreds of kilometers from infrastructure, this is the difference between 24/7 crop monitoring and systems that go dark during multi-day outages.
Explore real-world IoT success stories in agriculture.
Two Farms, Two Approaches: Traditional vs. Edge-Enabled Farm
To clearly understand the real impact of an edge-driven strategy, let’s compare two hypothetical 100-hectare coffee farms in interior Minas Gerais with identical conditions. The first one (Farm A) follows traditional farming methods. The other one (Farm B) has deployed ThingsBoard Edge on site. Here's what the operational differences look like:
Table 1. Side-by-side illustrative operational comparison. Note: Figures and behaviors are illustrative, collected from published research on IoT and precision-agriculture systems. Actual results will vary by region, soil, and implementation.
Annual Results Comparison
After 365 days, the small, daily advantages of the Edge-enabled farm compound into a significant financial return.
Figure 4. Key Annual results comparison
The following metrics should also be considered:
- Crop Loss Prevention: Early detection of drought stress and pest outbreaks protects an estimated 10–15% more yield compared to reactive traditional methods — directly increasing harvest revenue.
- Resource Optimization: Precision irrigation reduces water consumption by 15–30%, while soil monitoring enables targeted fertilizer application reducing overuse by 20–25%. Combined input cost savings: R$25,000–40,000 ($5,000–8,000 USD) annually.
- Labor Efficiency: Remote monitoring reallocates ~40% of field surveillance time to higher-value tasks like pruning and harvest planning — increasing productivity without additional hiring.
- Equipment Uptime: Predictive maintenance alerts and instant failure detection minimize emergency repairs, preventing costly irrigation disruptions during critical growth periods.
For a 100-hectare farm, these improvements can amount to hundreds of thousands of dollars in preserved revenue and cost savings annually.
Table 2. Side-by-side annual costs comparison. Note: Figures and behaviors are illustrative, collected from published research on IoT and precision-agriculture systems. Actual results will vary by region, soil, and implementation.
By comparing these two approaches, we can estimate annual savings of up to $70,000.
The Path Ahead for Brazil’s Coffee Farms
Brazil's coffee industry won't wait for perfect rural internet connectivity to arrive—and it doesn't have to. While government initiatives continue expanding infrastructure and 5G networks gradually reach more regions, the farms need solutions that work today, in current conditions.
For Brazilian coffee farmers, this isn't about adopting technology for technology's sake. It's about surviving droughts, responding to pest outbreaks in minutes instead of days, and optimizing resource use across plantations too vast for manual monitoring.
This is what we’re exploring in this series: whether protecting elderly patients in rural healthcare facilities, monitoring coffee harvests across remote plantations—the challenge remains consistent. Brazil's digital transformation is happening in regions where connectivity can't be guaranteed. Edge-first architecture isn't a workaround; it's the foundation.
Next in this series: We'll explore how Brazilian cities are using edge computing for smart waste management and urban resource optimization—solving logistics challenges in areas where traditional cloud platforms struggle with scale and connectivity.
Interested in exploring edge-powered healthcare monitoring? Try ThingsBoard Edge platform now for free!
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