Empowering Smart Cities with Sustainable Solar-Powered IoT Solutions
About the Client
Company’s Request
Technology Set
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MicroPython on Pycom LoPy4
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Utilized for programming the core logic and integrating sensors, MicroPython’s efficiency was key in rapid development and complex functionality deployment.
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BLE
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Enabled short-range, low-power transmission of sensor data to nearby devices, ideal for the smart city network.
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LoRa
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A long-range data transmission to central hubs for creating a city-wide sensor network.
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Panasonic SN-GCJA5 for PM2.5 Detection
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Laser diode technology in this sensor provided accurate real-time particulate matter measurements for air quality monitoring.
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S-300-3V ELT SENSOR for CO2 Monitoring
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Employed NDIR technology for precise atmospheric CO2 level measurement.
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EC1080 for Noise and Shock Detection
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This sensor offered noise pollution analysis and shock event detection, operating in a low-power, trigger-based mode.
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Voltaic Solar Panel
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Provided sustainable power with its high-efficiency cells and durable ETFE coating.
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Li-Ion 5200mAh Battery
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Stored excess energy for uninterrupted operation.
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Texas Instruments BQ24259 Charge Controller
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Managed battery charging and power distribution, enhancing energy efficiency.
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Data Normalization and Compression Algorithms
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Prepared sensor data for transmission, reducing load and enhancing transmission efficiency.
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RTOS
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Managed tasks and resources, providing multitasking and responsive operation.
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ADCs
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Converted sensor analog signals to digital format for accurate data processing.
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Solution
Main Board
At the core of our IoT device is the Pycom LoPy4 board, which operates using an ESP32 chipset.
This board is programmed with MicroPython, chosen for its effectiveness and user-friendly nature for developing the device’s software. This advanced programming is backed by FreeRTOS, a real-time operating system pre-installed on the ESP32. FreeRTOS handles essential tasks like scheduling activities in real time and allocating resources efficiently. Our MicroPython code interacts with the hardware, sensors, and communication methods while FreeRTOS manages background operations.
Sensors
PM2.5 Monitoring:
The device employs the Panasonic SN-GCJA5 sensor for PM2.5 detection.
This sensor utilizes laser technology for precise measurement of particulate matter, even particles as small as 0.3μm. An internal fan assists in particle detection, and the sensor offers real-time data updates. Its compact design and prolonged lifespan make it suitable for space-efficient devices.
CO2 Measurement:
CO2 levels are monitored using the S-300-3V 2000PPM UART I2C ELT SENSOR.
This sensor uses Non-Dispersive Infrared (NDIR) technology to provide accurate CO2 readings. It functions effectively over various temperature and humidity conditions and offers a compact size for easy integration. Its communication versatility (I2C and UART) aligns well with our device’s design.
Noise and Shock Detection: The EC1080 sensor in our device is capable of detecting noise pollution and shock events.
It operates efficiently in a low-power mode, activating to measure noise or motion based on specific thresholds. This functionality is essential for monitoring urban environments for noise pollution and structural disturbances, contributing to battery conservation and device longevity.
Humidity and Temperature :
We also integrated the SHTC3 sensor for advanced humidity and temperature measurements.
It features Sensirion’s CMOSens® Technology, combining a single chip’s humidity and temperature sensors. The sensor’s wide measurement range, high accuracy, and low power consumption were integral to our choice.
Power System
Solar Panel:
The device’s power source is a Voltaic 5-watt, 6-volt solar panel, selected for its efficiency and outdoor suitability.
The panel is lightweight, waterproof, and UV-resistant, ensuring durability. It is compact (148 x 223 x 4 mm) and does not add significant bulk. The panel’s peak output of 5.75 Watts at 6.12V more than suffices for the device’s power needs, even after adjusting the voltage to the device’s 3.6V operational level.
Battery and Charging Management:
A 5200mAh Li-Ion battery was chosen for its high energy storage capacity and compact size.
The battery’s charging process is managed by the Texas Instruments BQ24259 controller, which efficiently handles different charging stages.
This process enhances the battery’s lifespan and ensures a consistent power supply to the device.
MPPT Algorithm Integration:
The device includes a specially developed Maximum Power Point Tracking (MPPT) algorithm in its firmware. This algorithm continually adjusts the solar panel’s load to ensure operation at the Maximum Power Point, maximizing energy harvesting. It adapts to changes in solar intensity and other environmental factors, ensuring efficient power extraction. The algorithm also effectively manages the voltage transformation from the panel’s 6.12V output to the device’s 3.6V operation.
Data Handling
Custom algorithms for sensor data normalization and compression have been implemented. These algorithms optimize the size of the data for transmission, playing an important role in conserving power during wireless communication.
Data transmission utilizes BLE for short-range, power-efficient communication and LoRa for longer-range transmissions. This dual-method approach provides flexibility in reliable and adaptable data transmission in various urban scenarios.
Value Delivered
