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Renewable Energy Case Study

Full-Stack IoT Solutions for Biofuel Industries

How Osiris transformed standalone systems into connected, intelligent, and remotely manageable IoT solutions for Biofuel Industries' energy storage, water filtration, and silty imagery detection units.

Manual Checks Reduction

85%

Fault Response Time

40% ↓

Deployment Time

12 Weeks

Remote Monitoring

100%

Biofuel Industries Renewable Energy Facility
Biofuel Industries Renewable Energy Facility

About Biofuel Industries

Biofuel Industries is a leading renewable energy company specializing in the production of sustainable biofuels from agricultural waste. With multiple production facilities across Southeast Asia, they convert organic waste materials into clean energy, reducing carbon emissions and providing an alternative to fossil fuels.

Founded in 2003, the company has grown to become one of the region's most innovative players in the renewable energy sector, with a commitment to sustainability and technological advancement.

Industry & Technology

Renewable EnergyBiofuel ProductionIoT SystemsEdge Computing

Project Timeframe

Ongoing

The Challenge

Biofuel Industries' monitoring systems were local and not smart, creating several operational challenges:

  • No remote monitoring capabilities - Technicians had to physically visit each container just to check for faults or status updates
  • Limited to reactive monitoring - Issues were only discovered during on-site visits, often after problems had escalated
  • No centralized dashboard - Inability to see system-wide performance or compare data across facilities
  • No historical data or analytics - Making trend analysis and optimization nearly impossible
  • No automated alerts - Resulting in delayed responses to critical issues

While the systems already had built-in touch panels for on-site control, this localized approach was time-consuming and inefficient, especially across multiple sites. Biofuel needed to transform their standalone systems into connected, intelligent, and remotely manageable solutions.

Our Solution

Osiris designed and implemented a lightweight, modular IoT architecture powered by Raspberry Pi 4 devices as edge gateways, tailored to Biofuel's harsh operating environments:

Communication Protocols

Integrated Modbus RTU (via RS485) for industrial sensors and Bluetooth Low Energy (BLE) for wireless sensors on mobile parts of the system.

Edge Computing

Raspberry Pi 4 devices aggregated data locally and pushed to our cloud dashboard via MQTT for analytics, anomaly detection, and remote monitoring.

Adaptive Sensor Polling

Proprietary software enabled secure communication with dynamic polling rates based on operational conditions and anomaly detection.

Environmental Hardening

Waterproof enclosures, stabilized power management, and redundant communication paths for field reliability in harsh conditions.

Specialized Solutions for Each System

Energy Storage Systems

Each energy system had over 100 sensors monitoring voltage, current, and temperature. We used RS485-connected meters for stable readings and BLE sensors for movable units, with data streamed every 5 seconds to our edge devices.

Water Filtration System

The filtration system implemented a mix of pressure sensors, turbidity sensors, and valve controllers. We deployed Raspberry Pis with waterproof enclosures and integrated both BLE flow sensors and Modbus-compatible pH sensors.

Silty Imagery Detection System

Our downstream verification system included ST-730SS Inline Turbidity Sensors for high-accuracy readings, Bluetooth hardware integration, and weatherproof enclosures with optimized power management for field reliability.

The Results

After implementing Osiris' full-stack IoT solution, Biofuel Industries experienced significant operational improvements across all their systems:

Operational Efficiency

  • 85% reduction in manual checks
  • 40% faster response time to faults
  • 100% real-time visibility from remote HQ

Data Insights

  • Comprehensive trend analysis across all systems
  • Predictive maintenance capabilities
  • Early anomaly detection preventing major issues

System Reliability

  • 99.9% uptime for all monitoring systems
  • Reliable operation in harsh environmental conditions
  • Robust data integrity with redundant storage

Financial Impact

  • 25% reduction in operational costs
  • 30% decrease in maintenance expenses
  • Extended equipment lifetime through proactive maintenance

"Now that we have these automatic IoT monitoring systems in place, we have more time. We can focus on providing value for both engineers at Biofuel and our end users. The data insights have transformed how we make decisions, and the impact on our efficiency has been remarkable."

EL

Eugene Lee

Managing Director at Biofuel Industries

Technical Implementation

System Architecture

Modbus + BLE Architecture Diagram

(Contact us for detailed technical specifications)

Key Technologies

Hardware

  • • Raspberry Pi 4 edge gateways
  • • RS485 modules for Modbus RTU
  • • BLE modules for wireless sensors
  • • ST-730SS Inline Turbidity Sensors
  • • Weatherproof IP67 enclosures

Software

  • • Custom monitoring software
  • • MQTT messaging protocol
  • • Cloud-based analytics dashboard
  • • Anomaly detection algorithms
  • • Secure API integrations

Communication

  • • Modbus RTU over RS485
  • • Bluetooth Low Energy (BLE)
  • • MQTT for cloud messaging
  • • Encrypted TLS connections
  • • Redundant failover channels

Data Processing

  • • Edge processing for immediate analysis
  • • Adaptive polling algorithms
  • • Time-series database storage
  • • Machine learning for predictions
  • • Automated reporting system

Software & Communication

Our proprietary software enabled secure communication between Raspberry Pi units and sensors, with these key features:

Adaptive Sensor Polling

Dynamic polling rates that adjusted based on operational conditions, equipment status, and detected anomalies.

Intelligent Alert System

Automated triggers responded to discrepancies in sensor readings with customizable thresholds and escalation protocols.

Local Data Buffering

Edge devices stored data locally during connectivity disruptions, automatically syncing when connections were restored.

Power Management

Specialized routines optimized device power consumption while ensuring reliable 24/7 operation in remote locations.

Implementation Process

1
Week 1-2

Assessment & Planning

  • Analyzed existing system architecture and sensor requirements
  • Identified communication protocols and hardware compatibility
  • Developed custom architecture for each system type
  • Established performance metrics and security requirements
2
Week 3-6

Hardware & Software Deployment

  • Installed and configured Raspberry Pi 4 edge gateways
  • Integrated Modbus RTU and BLE communications
  • Deployed custom monitoring software
  • Established secure cloud connectivity and data flow
3
Week 7-10

Testing & Optimization

  • Validated sensor data accuracy and reliability
  • Stress-tested system under various environmental conditions
  • Optimized polling rates and communication protocols
  • Fine-tuned alert thresholds and notification systems
4
Week 11-12

Training & Handover

  • Trained Biofuel's technical team on system operation
  • Created comprehensive documentation and troubleshooting guides
  • Established ongoing support and maintenance protocols
  • Completed formal system handover with verification testing

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