The Impact of LoRaWAN Diesel Level Sensors on Industrial Farming

ellenex team
Mar 26
9 min read

In industrial farming, where production takes centre stage, efficient management of resources and processes is crucial for maximizing yield and profitability. One of the critical challenges faced by industrial farmers is ensuring optimal operations across vast sugarcane fields and manufacturing facilities. However, the advent of LoRaWAN-enabled sensors has shifted the paradigm, revolutionizing sugar manufacturing. In this blog, we will explore the challenges that industrial farmers faced before adopting LoRaWAN sensors, the significant impact on labour and time savings, and the diverse applications that these sensors enable in sugar production. Let’s see how one of our largest clients and sugar manufacturers in the USA has overcome this issue.

The Remote diesel Level Sensor Ecosystem

Remote diesel monitoring in industrial environments utilizes the Long Range Wide Area Network (LoRaWAN) protocol to address connectivity gaps in rural areas. Unlike traditional wireless technologies, LoRaWAN is optimized for long-range communication (up to 15 km in rural settings) with minimal power consumption.

Technical Specifications of the PLS2-L

The Submersible Level Sensor(PLS2-L) is an industrial-grade sensor engineered to withstand harsh conditions, including exposure to volatile hydrocarbons, high humidity, and extreme temperatures ranging from -20°C to 85°C.The PLS2-L operates on the principle that the pressure at the bottom of a fuel tank is directly proportional to the height of the liquid.

Measurement Method: The sensor utilizes hydrostatic pressure measurement, which offers superior reliability over non-contact sensors that can be affected by internal tank structures or fuel vapors.
Precision: It features a typical accuracy of ±0.25% Span and a resolution of ±0.01% Span.
Longevity: Designed for ultra-low power consumption, the device can achieve a battery life of over 10 years, supporting upwards of 100,000 readings.
Vented Compensation: A vented cable allows the sensor to compensate for changes in atmospheric pressure, ensuring accurate readings regardless of barometric fluctuations.

Challenges in Industrial Farming Without LoRaWAN Sensors

Inefficient Resource Management: Industrial farmers grappled with the task of manually monitoring vast sugarcane fields, often leading to inefficient resource management. Without real-time data, they faced difficulties in optimizing irrigation, fertilization, and pest control, which directly impacted the crop yield and quality.
Labour-Intensive Inspections: Traditional methods of inspecting equipment and machinery relied heavily on manual labour. Regular checks on equipment conditions, such as sugar processing machinery and storage tanks, were time-consuming and resource-intensive.
Limited Visibility in Remote Areas: Industrial farms often span vast landscapes, including remote areas where access is challenging. This lack of visibility made it difficult for farmers to respond promptly to issues or optimize operations in these regions.

Operational Impact and Statistics

The integration of LoRaWAN diesel level sensors has fundamentally altered the operational landscape of industrial farming by moving from a reactive to a proactive management model.

Labor Cost Reduction: Automated data collection eliminates the need for manual inspections, leading to labor cost savings of up to 25%.
Water and Energy Savings: By integrating fuel data with soil moisture sensors, farmers can optimize irrigation schedules. This can result in water savings of up to 30% while maintaining or increasing yields.
Yield Improvements: Precision agriculture enabled by these sensors has shown remarkable increases in crop yields, typically ranging from 10% to 20%.
Predictive Maintenance: Analyzing fuel consumption trends allows for the implementation of predictive maintenance, addressing potential engine or pump issues before they lead to breakdowns.
Return on Investment (ROI): Most industrial operations achieve a full return on investment within 12 to 24 months through reduced operational effort and optimized inventory management.

Security: The "Silent Thief" and Leak Detection

Fuel is a significant operating expense, often accounting for 35% of a professional fleet's logistics budget. This makes fuel tanks a frequent target for theft and a potential environmental risk.

Theft Prevention: Fuel theft in the United States exceeded $2.1 billion in 2023 . The PLS2-L acts as a "silent auditor," detecting even small changes in tank volume. Any sudden drop that does not correspond to machine runtime triggers an immediate alert .
Leak Detection: Consistent fuel tracking is the first line of defense against unnoticed leaks. Automated monitoring alerts showing volume inconsistencies allow facility managers to act before environmental contamination spreads.

Case Study: Large-Scale Sugar Production in Florida, USA

Partner: Simply Connected Systems

Client: One of the largest farm management companies in Florida

Industry: Sugarcane Production and Manufacturing

In the Florida Everglades, sugarcane production spans approximately 434,000 acres. Before adopting LoRaWAN sensors, this client faced significant challenges in monitoring remote drainage and irrigation pumps across vast landscapes.

By partnering with Simply Connected Systems to deploy a LoRaWAN infrastructure, the company achieved the following:

Scale of Deployment: The network supports 24 data gateways across 255,000 acres.
Real-Time Monitoring: 347 fuel-level sensors were installed across hundreds of machines and stationary tanks.
Centralized Control: Managers in a Harvest Control Room monitor every gallon of fuel used in the fields via a digital dashboard accessible on desktop and mobile devices.
Elimination of Downtime: The system automatically triggers proactive fuel deliveries when levels are low, ensuring that harvesting and processing operations—which run continuously during the "grinding season"—never sit idle due to empty tanks.

Diesel level sensor mounted on a diesel tank in a farm — Remote Diesel Tank Monitoring Solution

What are the other application and challenges that Ellenex Sensor can address?

The versatility of LoRaWAN sensors has enabled various applications that address key challenges in sugar manufacturing:

Soil Moisture Monitoring: By deploying soil moisture sensors across the fields, farmers gain precise insights into soil conditions, optimizing irrigation schedules, and ensuring efficient water usage. This results in improved crop health and higher sugar yields.
Temperature and Humidity Control: In manufacturing facilities, LoRaWAN sensors can be utilized to monitor temperature and humidity, ensuring optimal conditions during the sugar processing stages. This leads to better sugar quality and reduced wastage.
Water Savings: With soil moisture sensors providing accurate data on soil conditions, industrial farmers can reduce water wastage significantly. Studies have shown that implementing smart irrigation systems based on sensor data can lead to water savings of up to 30% while maintaining or even increasing crop yields.
Yield Increase: The precision agriculture enabled by LoRaWAN sensors has shown a remarkable increase in sugar cane yields. On average, industrial farmers have reported yield improvements of 10% to 20% after adopting smart farming techniques and leveraging sensor data for optimized crop management.
Labor Cost Reduction: The implementation of LoRaWAN sensors and automation technologies has resulted in reduced labor costs in both sugarcane fields and manufacturing facilities. Some industrial farmers have reported labour cost savings of up to 25% due to reduced manual inspections and optimized workforce allocation.
Fertilizer Optimization: By analyzing data from soil sensors and weather stations, farmers can optimize fertilizer usage, resulting in cost savings and reduced environmental impact. Studies have shown that precision agriculture practices can reduce fertilizer usage by 10% to 20% without compromising crop yield.
Environmental Impact: Smart farming practices driven by LoRaWAN sensors contribute to sustainability efforts in the agricultural sector. Reduced water usage, optimized pesticide and fertilizer application, and more efficient energy consumption all contribute to a lower overall environmental impact.
Data-Driven Decision Making: Industrial farmers leveraging sensor data have reported making more informed decisions across various aspects of their operations. Approximately 75% of farmers who have adopted data-driven practices say it has positively impacted their decision-making capabilities.
Scalability: LoRaWAN sensor networks are highly scalable, making them suitable for large-scale industrial farming operations. The technology can be easily expanded to cover vast areas of sugarcane fields and facilities without compromising data transmission quality.
Return on Investment (ROI): Studies have indicated that the ROI on implementing LoRaWAN sensor networks in industrial farming can be achieved within a short period, often within a year or two. After the initial investment, ongoing cost savings and increased productivity contribute to substantial long-term benefits.

Conclusion

The incorporation of LoRaWAN sensors into industrial farming has unlocked new possibilities for sugar manufacturers. By streamlining operations, optimizing resource usage, and implementing predictive maintenance, industrial farmers can now elevate their productivity and profitability to unprecedented levels. The ability to remotely monitor vast sugarcane fields and manufacturing facilities ensures that no aspect of the operation goes unnoticed, fostering a more sustainable and efficient approach to sugar production. These statistics demonstrate the tangible benefits that LoRaWAN sensors bring to industrial farming and sugar manufacturing, emphasizing their potential to revolutionize the agricultural sector and contribute to more sustainable and profitable practices. As the technology continues to evolve, the future of industrial farming looks promising, with LoRaWAN sensors playing a pivotal role in shaping the landscape of modern sugar manufacturing.

Frequently Asked Questions

How does the LoRaWAN Submersible level sensor measure fuel levels, and why is it superior to traditional methods?
The PLS2-L utilizes hydrostatic pressure measurement to determine the exact volume of diesel in a tank. The sensor probe is submerged at the bottom of the tank, where it measures the pressure exerted by the column of liquid above it. This pressure is calculated using the formula P = d*g*h, where P is the hydrostatic pressure, d is the liquid density, g is the gravitational constant, and h is the height of the fuel. To ensure precision regardless of weather conditions, the device features a vented cable that provides an atmospheric pressure reference, allowing the sensor to automatically compensate for barometric fluctuations.
This hydrostatic method is generally preferred over traditional mechanical floats or ultrasonic sensors because it is not affected by internal tank structures, foam, or fuel vapors that often deceive non-contact sensors. With a typical accuracy of ±0.25% and a resolution of ±0.01%, the PLS2-L provides professional-grade data that eliminates the human error associated with manual "sticking" or visual inspections. Furthermore, the lack of moving parts reduces the need for frequent calibration and maintenance, ensuring a long-term durable performance even in the harsh, corrosive environments common in industrial farming.
Why is LoRaWAN preferred over cellular (NB-IoT) for remote agricultural monitoring?
LoRaWAN is often the "de facto" choice for large-scale farming because it allows operators to deploy private networks without relying on third-party telecommunications providers. In remote areas like the Florida Everglades, where cellular coverage is frequently spotty or non-existent, LoRaWAN gateways can provide a stable signal over a radius of 15 kilometers in open terrain. Because it operates on unlicensed radio spectrum, there are no recurring monthly subscription fees for each device on a private network, which significantly lowers the long-term operational costs compared to cellular NB-IoT or LTE Cat M1 options.
Power efficiency is another critical factor. LoRaWAN is optimized for devices that transmit small packets of data periodically, allowing sensors like the PLS2-L to achieve a battery life of over 10 years on a single charge. In contrast, cellular networks require more frequent communication with towers to maintain a connection, which depletes batteries faster and often necessitates replacements every 5 to 10 years. Additionally, LoRaWAN's Chirp Spread Spectrum (CSS) modulation provides superior signal penetration through dense vegetation and metal enclosures, ensuring reliable data transmission from remote pumps and storage sheds.
How does the monitoring system protect against fuel theft and environmental leaks?
The monitoring system acts as a "silent auditor" by providing real-time visibility into every gallon of fuel stored. Because the PLS2-L has a high resolution that can detect volume changes down to the millimeter, any sudden drop in fuel levels that does not correspond with an engine's runtime triggers an immediate alert for managers. This transparency deters "micro-theft" or siphoning, which can account for up to 10% of fuel volume monthly in unmonitored fleets. Some advanced systems can even integrate with pump controls to instantly shut down fuel dispensers if a breach or unauthorized access is detected.
For environmental safety, the system provides a proactive defense against unnoticed leaks. Constant inventory reconciliation allows facility managers to spot discrepancies early, preventing hazardous substances from contaminating the soil or nearby waterways—a critical concern for compliance with environmental regulations such as those from the FDEP in Florida. Automated alerts notify operators of volume inconsistencies or pressure changes, enabling a rapid response that can prevent a minor equipment failure from escalating into a catastrophic environmental incident or a costly remediation project.
What specific labor and cost-saving benefits can industrial farms expect?
Industrial farmers typically see a significant reduction in operating expenses, with some reporting labor savings of up to 25% by automating routine inspections. Traditionally, technicians spend hundreds of hours annually traveling to remote sites just to check fuel levels; with LoRaWAN sensors, this data is delivered directly to a central dashboard, allowing the workforce to focus on high-value production tasks rather than logistics. Studies have shown that this automation can lead to an overall reduction of 15% to 22% in fuel-related operating costs by optimizing delivery schedules and eliminating "emergency" refilling trips.
Beyond direct labor, the system enhances efficiency through predictive maintenance and reduced downtime. By analyzing fuel consumption patterns, the software can identify failing pumps or engines requiring a tune-up before they break down. This proactive approach extends the lifespan of expensive machinery and ensures that critical operations, such as harvesting, are never interrupted by an empty fuel tank. Because of these combined efficiencies, most agricultural operations report a full return on investment (ROI) within 12 to 24 months of implementation.
How does this technology support precision agriculture and environmental sustainability?
The integration of fuel sensors into a wider IoT ecosystem is a cornerstone of precision agriculture. By combining fuel data with soil moisture and weather sensors, farmers can ensure that diesel-powered irrigation pumps only run when absolutely necessary, which can lead to water savings of up to 30%. This precise management not only conserves water but also increases crop yields by10% to 20%, as it ensures crops receive optimal hydration and nutrients without the stress of over-irrigation.
From a sustainability perspective, reducing diesel consumption has a direct impact on a farm's carbon footprint. Each liter of diesel consumed releases approximately 2.7kg of carbon dioxide into the atmosphere; therefore, the 20% reduction in fuel use often achieved through optimized routing and monitoring represents a substantial decrease in greenhouse gas emissions. Furthermore, precision monitoring allows for the more targeted application of fertilizers and pesticides, reducing chemical runoff that can damage local ecosystems and ensuring that large-scale industrial farming remains viable and environmentally responsible for future generations.