1. Introduction
Overview of IoT Technology in Industrial Monitoring
The Internet of Things (IoT), particularly ESP 32-based systems, plays a crucial role in industrial monitoring by enabling real-time data collection, remote control, and automation. In anaerobic digestion (AD), ESP 32 facilitates precise monitoring of key parameters such as temperature, pH, and methane concentration, ensuring process stability, methane yield optimization, and system efficiency. Its wireless connectivity and edge processing capabilities enhance data acquisition and predictive analytics for better operational control.
The Role of ESP 32 Microcontrollers in Real-Time Data Collection
The ESP32 microcontroller, developed by Espressif Systems, provides low-cost, wireless IoT capabilities ideal for biogas reactor monitoring. Featuring Wi-Fi and Bluetooth connectivity, the ESP 32 allows seamless integration with sensors measuring pH, temperature, REDOX potential, ammonium concentration, and methane production.
Importance of Efficient Biogas Reactor Monitoring for Sustainability
Biogas production relies on microbial balance and environmental conditions. Traditional monitoring methods require manual sampling, which is labor-intensive and prone to delays. ESP32-based IoT systems provide automated, real-time monitoring, ensuring stable methane output and reduced operational inefficiencies.
How Low-Cost IoT Systems Improve Anaerobic Digestion Performance
An IoT-driven biogas monitoring system facilitates:
- Early detection of process inefficiencies through automated alerts.
- Optimized methane production tracking, improving overall yield.
- Remote access to real-time reactor data, allowing immediate corrective actions.
2. The Need for ESP32-Based IoT Bioreactor Monitoring
Challenges in Traditional Biogas Reactor Monitoring
Anaerobic digestion (AD) depends on precise microbial interactions, requiring continuous monitoring to prevent process instability. Traditional monitoring challenges include:
- Manual sampling—time-consuming and resource-intensive.
- Offline analysis—requires sophisticated lab equipment.
- Limited real-time detection—difficult to predict sudden fluctuations in methane yield.
Benefits of Real-Time Sensor Data Acquisition Using ESP 32
Using ESP32 improves reactor monitoring by:
- Reducing reliance on manual interventions via automated sensor logging.
- Enhancing methane production tracking, minimizing performance deviations.
- Lowering costs by replacing expensive lab-based analytical techniques with online monitoring.
Comparison: Traditional vs. ESP 32-Powered IoT Monitoring Systems
| Aspect | Traditional Monitoring | ESP32-Based IoT Monitoring |
|---|---|---|
| Sampling Method | Manual, periodic | Continuous, automated |
| Process Control | Requires human intervention | Remote adjustments & automated optimization |
| Methane Measurement | Gas chromatography (costly) | CO2 scrubber-based analysis |
| Data Storage | Local files or spreadsheets | Cloud-based SQL database |
| Alerts for Process Instability | Requires manual detection | Automated notifications via IoT sensors |
Impact on Biogas Yield, Methane Concentration, and Process Stability
By integrating ESP32-based monitoring, anaerobic biogas reactors experience:
- Higher methane yield consistency due to automated regulation.
- Improved stability in temperature, pH, and REDOX potential monitoring.
- Faster response to substrate loading adjustments, preventing operational inefficiencies.
3. Methodology: Implementing ESP 32 Based IoT Monitoring
Integration of Sensors for Temperature, pH, REDOX Potential, and Ammonium
To effectively monitor the anaerobic digestion (AD) process, the ESP32-based IoT system integrates multiple sensors:
- Temperature Sensor (DS18B220): Tracks real-time substrate temperature within the bioreactor to maintain optimal microbial conditions.
- pH Electrode (GE 117-BNC): Ensures microbial stability by monitoring pH variations, preventing process disruptions.
- REDOX Potential Electrode (GE 175-BNC): Evaluates microbial metabolic conditions, allowing early detection of AD imbalances.
- Ammonium Ion Sensor (Ammonium 3051 ISE): Measures nitrogen levels to prevent ammonia toxicity, a common issue in AD processes.
ESP 32 Microcontroller Setup and Programming Using Arduino IDE
The ESP32-WROOM-32E Firebeetle board was selected for its low cost, real-time processing capabilities, and wireless data transmission features. The programming was done using Arduino IDE, leveraging open-source libraries to streamline sensor integration and calibration.
The microcontroller was programmed to:
- Continuously log sensor data every 15 seconds.
- Trigger alerts when thresholds exceeded stability limits.
- Restart automatically at midnight to prevent software glitches.
Real-Time Data Transmission and Database Storage via Wi-Fi Connectivity
Sensor data is transmitted via HTTP POST requests to an SQL database, enabling remote monitoring and real-time data retrieval. The IoT system architecture ensures:
- Cloud-based storage, allowing historical data analysis.
- Automated anomaly detection, reducing reaction time to process deviations.
- Secure, timestamped logging, ensuring traceability of bioreactor fluctuations.
Biogas Production Measurement Using Liquid Displacement Techniques
Biogas production and methane concentration were measured using ESP32-controlled volumetric displacement methods:
- Biogas Volume Measurement: Tap water adjusted to pH 3 using ortho-H3PO4 to prevent CO2 absorption.
- Methane Measurement: A CO2 scrubber filled with NaOH eliminated CO2, ensuring accurate CH4 quantification.
- Capacitive Sensors: Triggered biogas volume logging, preventing errors in gas release measurement.
4. How ESP 32 Based IoT Monitoring Works
Automated Data Collection and Logging Using ESP32
The ESP32-based system automates sensor data retrieval, ensuring:
- Consistent real-time tracking of biogas yield.
- Historical data visualization for bioreactor performance assessment.
- AI-driven predictive analytics could further optimize methane yield projections.
Methane Concentration Monitoring via CO2 Scrubber System
A sodium hydroxide (NaOH) scrubber eliminates CO2, ensuring precise methane measurements. The ESP32 controls gas injection and flow, reducing dependence on gas chromatography-based methane analysis.
IoT Architecture: Perception, Processing, Transmission, and Application Layers
| IoT Layer | Components |
|---|---|
| Perception | Sensors (pH, temperature, REDOX, ammonium, methane) |
| Processing | ESP32 microcontroller, calibration equations |
| Transmission | Wi-Fi-based SQL database logging |
| Application | Web-based monitoring dashboard |
System Validation Against Analytical Methods for Accuracy Improvement
To ensure reliable sensor readings, IoT-based methane and ammonium measurements were validated against gas chromatography and Kjeldahl Distillation analysis. The results confirmed:
- Less than 6% deviation in methane measurement.
- Consistent pH and temperature stability compared to reference methods.
- Ammonium sensor requiring frequent recalibrations due to interference.
5. Results & Real-World Applications of ESP 32 Based IoT Biogas Reactor Monitoring
Performance Analysis: Stability of Temperature, pH, and Methane Measurement Using ESP 32
| Parameter | Analytical Method Deviation |
|---|---|
| Biogas Volume | ±5.3% deviation from gas chromatography |
| Methane Concentration | ±6% deviation from chromatography |
| pH Stability | ±1.67% deviation |
| Temperature Fluctuations | ±0.15% deviation |
Quantifiable Improvements in Biogas Yield Monitoring
- Biogas production stabilized at 43.22 L/day under optimal conditions.
- Methane concentration fluctuations remained below 6% variance.
- Early detection of instability (day 41) prevented major system failures.
Case Study of IoT Integration in Pilot Anaerobic Biogas Reactors
The system was tested for 48 days of continuous operation, successfully:
- Detecting methane yield fluctuations and triggering alerts.
- Preventing process instability through automated monitoring.
- Demonstrating practical application for energy-efficient waste management.
Comparative Table: IoT-Based Monitoring vs. Conventional Methods
| Aspect | Traditional Method | IoT-Based ESP32 System |
|---|---|---|
| Methane Analysis | Gas chromatography | CO2 scrubber + ESP32 |
| Real-Time Alerts | Manual response | Automated sensor-triggered notifications |
| Long-Term Cost | High | Low-cost microcontroller integration |
6. Challenges & Future Research Directions in ESP 32 Based Stability Measurement
Technical Hurdles in IoT Adoption: Calibration, Connectivity, and Sensor Stability
Despite the success of ESP32-based IoT monitoring systems, several technical challenges must be addressed to ensure widespread adoption in anaerobic biogas reactors:
- Sensor Calibration Issues: The ammonium ion-selective electrode (ISE) required frequent recalibration due to interference from other ions in the anaerobic medium, affecting accuracy. Future sensor designs must consider improved selectivity and filtering mechanisms.
- Connectivity Challenges: ESP32 relies on Wi-Fi connectivity, which may pose issues in field-based applications where stable internet access is unavailable. Implementing edge computing and offline data logging could mitigate this limitation.
- Long-Term Sensor Stability: Electrodes used for pH, REDOX potential, and ammonium monitoring showed performance degradation due to substrate sedimentation and exposure to bioreactor conditions. Periodic maintenance protocols and robust sensor housings are necessary to extend operational lifespans.
Potential AI Integration for Predictive Analytics in ESP 32 Based Biogas Production
Artificial Intelligence (AI) presents an opportunity to optimize anaerobic digestion (AD) efficiency:
- AI-driven predictive maintenance: Machine learning models can analyze historical sensor data to detect early signs of instability, allowing timely corrective actions.
- Automated methane yield forecasting: AI algorithms can predict biogas output fluctuations based on real-time data inputs.
- Neural networks for feedstock optimization: AI can assist in determining the ideal organic loading rate (OLR), improving methane yield consistency.
Long-Term Impact on Energy Efficiency and Waste Management
The implementation of IoT monitoring systems in biogas reactors enhances sustainable waste management and energy efficiency:
- Optimized methane recovery reduces reliance on fossil fuels, promoting renewable energy generation.
- Real-time waste monitoring enables better substrate utilization, minimizing feedstock waste.
- Reduced greenhouse gas emissions through improved process control in anaerobic digesters.
Future Enhancements: Machine Learning Algorithms for Optimal Bioreactor Control
Future research should explore:
- AI-based anomaly detection to improve process stability.
- Blockchain integration for secure, real-time energy trading from biogas plants.
- Advanced IoT sensors capable of measuring volatile fatty acids (VFAs) and microbial activity, further refining reactor performance.
7. Conclusion
Summary of ESP 32 Advantages in Anaerobic Reactor Monitoring
The ESP32-based IoT system successfully monitored critical bioreactor parameters, demonstrating advantages over traditional offline measurement techniques:
- Low-cost implementation compared to conventional gas chromatography systems.
- Automated real-time monitoring of methane concentration, pH, REDOX potential, temperature, and ammonium levels.
- Improved stability analysis through continuous sensor logging and online database storage.
Encouragement for IoT Adoption in Waste-to-Energy Applications
ESP32-driven IoT monitoring offers a scalable and adaptable solution for biogas systems, particularly for pilot-scale and industrial applications. Wider adoption of wireless sensor networks can:
- Increase biogas plant efficiency while lowering operational costs.
- Enhance waste management strategies, ensuring maximum energy recovery.
- Facilitate real-time monitoring and data-driven decision-making for AD optimization.
The Role of Smart Biogas Monitoring in Improving Renewable Energy Efficiency
IoT-based monitoring bridges the gap between traditional biogas production and modern industrial automation, making waste-to-energy systems more efficient and scalable. By integrating AI, blockchain, and advanced analytics, ESP32-driven IoT systems will revolutionize the way anaerobic digesters function, paving the way for greener, more sustainable energy solutions.
Reference
Kalamaras, S.D., Tsitsimpikou, M.-A., Tzenos, C.A., Lithourgidis, A.A., Pitsikoglou, D.S., & Kotsopoulos, T.A. (2025). A Low-Cost IoT System Based on the ESP32 Microcontroller for Efficient Monitoring of a Pilot Anaerobic Biogas Reactor. Applied Sciences, 15(34). https://doi.org/10.3390/app15010034
Creative Commons License (CC BY 4.0)
This article is an open-access publication, distributed under the terms of the Creative Commons Attribution (CC BY) license.