[Vídeo do projeto]

Team: Grupo 07:
Pedro Afonso (Coord.) , Pedro Reis , Simão Ribeiro , Hugo Miranda
Company: EnG.IoT
Supervisors: Susana Sargento (DETI)
João Carlos Siqueira (EnG.IoT)

The Multisensor Data Logger is a system developed for real-time monitoring of industrial parameters, focusing on energy efficiency, adaptability, and scalability. By integrating current and pressure sensors with an ESP32 for data acquisition and processing, and a Raspberry Pi for centralized management and display via Home Assistant, the project delivers a robust and versatile solution for diverse industrial applications.

Challenge

ENG.IoT presented the challenge of designing a scalable and energy-efficient solution for monitoring various industrial parameters. The system was required to integrate pressure and current sensors with real-time data transmission and ensure connectivity and energy optimization through ESP32 and Raspberry Pi. Accessibility via Home Assistant, a graphical interface for remote monitoring, and energy-saving mechanisms, such as “deep sleep,” were also critical requirements.

Key Features

  1. Real-Time Monitoring
    • Collects data from current and pressure sensors.
    • Transmission of real-time data to Raspberry Pi.
    • Visualization via Home Assistant’s customizable dashboard.
  2. Energy Efficiency
    • Implements “deep sleep” modes for the ESP32 to minimize power consumption during idle periods.
  3. User-Friendly Interface
    • Graphical and interactive dashboard for monitoring, alerts, and parameter adjustments.
  4. Scalability and Modularity
    • Supports additional sensors allowing for future expansions.
    • Design flexibility for future expansions.
  5. Reliable Communication
    • Wi-Fi-based data transmission ensuring robust connectivity.

Technical Approach

  • Hardware:
    The ESP32 captures data from pressure and current sensors, conditioned for precision, while the Raspberry Pi serves as the processing and visualization hub.
    • Pressure Sensor: Measures values between 0-12 bar, conditioned for accurate ADC readings.
    • Current Sensor: Measures alternating current with calibrated RMS calculation.
    • A “step-up” converter powers the pressure sensor for stable operation.

  • Software:
    Developed using Home Assistant for intuitive visualization. The ESP32 periodically enters “deep sleep” to conserve energy, only waking to acquire and transmit data.

  • Energy Optimization:
    Configurable sampling intervals and transmission periods. The Wi-Fi module is activated only during data transmission or upon user request via a magnetic sensor.

Architecture

General Architecture - Level 0

This level represents the overall system design, focusing on the main components and their interactions:

  • Input: Current and pressure sensors collect raw data.
  • Processing: Data is processed and temporarily stored by the ESP32 before being transmitted to the Raspberry Pi.
  • Output: Processed data is visualized in real-time through a dashboard in Home Assistant.

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Detailed Architecture - Level 1

The system is divided into subsystems for better clarity:

  • Sensors: Responsible for gathering raw current and pressure data.
  • Signal Conditioning: Adjusts sensor outputs to match the ESP32’s ADC input requirements.
  • Data Transmission: ESP32 sends the data to the Raspberry Pi over Wi-Fi for further processing.

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Data Flow - Level 2

At this level, the data flow is broken down:

  • Input: Sensors provide analog signals for current and pressure readings.
  • Processing:
    • Signal conditioning for ADC compatibility.
    • ESP32 calculates RMS (current) and averages (pressure), stores, and packages the data.
  • Output: Raspberry Pi displays the processed data via Home Assistant.

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Hardware Architecture

The hardware architecture integrates two sensors (current and pressure) with the ESP32 and Raspberry Pi:

  • ESP32: Acts as the main controller, acquiring and pre-processing sensor data.
  • Raspberry Pi: Collects data from the ESP32, stores it, and serves it to the Home Assistant interface.
  • Conditioning Circuit: Adjusts sensor outputs for ADC compatibility.

Pressure Sensor Circuit:

  • A step-up converter supplies 5V to the sensor.
  • The output is conditioned to ensure compatibility with the ESP32’s ADC.

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Current Sensor Circuit:

  • An offset is applied to the signal to avoid negative voltages.
  • The RMS value is calculated for accurate current measurement.

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Software Architecture

The software stack supports efficient communication and energy management:

  • Deep Sleep: The ESP32 periodically enters a low-power state to save energy.
  • Data Processing: The ESP32 calculates sensor data averages, which are sent in batches to the Raspberry Pi.
  • User Interface: Home Assistant displays data and allows parameter configuration.

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Flow Diagram for Deep Sleep

The flow diagram outlines the ESP32’s operational states:

  1. Deep Sleep: Conserves energy during idle periods.
  2. Data Collection: Wakes up to gather data from sensors.
  3. Data Transmission: Sends collected data to the Raspberry Pi.
  4. User Adjustments: Allows configuration changes like sampling frequency via Home Assistant.

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Results

  • Functionality:
    The system successfully collects data from the sensors, processes and stores it in the Raspberry Pi, and displays it on a user-friendly Home Assistant dashboard.

  • Energy Efficiency:
    Tests confirmed battery autonomy of up to 48 hours in standard operation with “deep sleep” enabled.

  • Modular Design:
    The platform supports integration of additional sensors and functionalities, ensuring scalability for future industrial applications.

Challenges and Lessons Learned

  • Challenges:
    • Ensuring seamless integration between ESP32 and Raspberry Pi over Wi-Fi.
    • Developing accurate sensor calibration to prevent measurement errors.
  • Lessons Learned:
    • Iterative optimization of hardware and software is crucial for energy efficiency.
    • Comprehensive real-world testing enhances system reliability and usability.

Conclusion

The Multisensor Data Logger project delivers a scalable, energy-efficient, and reliable solution for real-time industrial monitoring. By integrating modern communication protocols, energy-saving features, and a user-friendly interface, the system meets the demands of contemporary industrial applications while paving the way for future enhancements.

Demo video of the final product