Temperature Monitoring using Raspberry Pi Pico

Abstract

Accurate and continuous temperature monitoring is essential in domains such as home automation, laboratory research, and industrial process control. Conventional systems often face challenges related to high cost, limited scalability, and inefficient power utilization. To address these issues, this work proposes a cost-effective temperature monitoring framework employing the Raspberry Pi Pico microcontroller. The system integrates digital or analog temperature sensors, including DS18B20 and LM35, with the Pico to acquire real-time environmental data. The collected measurements are processed locally and subsequently presented either on an LCD interface for immediate observation or transmitted to a remote server using wireless communication technologies such as Wi-Fi or Bluetooth. Experimental implementation highlights the system’s efficiency in terms of low power consumption, reliable performance, and ease of deployment. The results demonstrate that the proposed solution provides a sustainable and adaptable alternative for temperature monitoring, with potential applications across residential, scientific, and industrial environments.

Introduction

Temperature monitoring is crucial in various fields including environmental management, healthcare, industry, and smart homes. Traditional systems often suffer from high costs, power consumption, and limited flexibility, making them unsuitable for low-resource settings.

The Raspberry Pi Pico, a low-cost microcontroller with a dual-core RP2040 chip, offers a cost-effective, energy-efficient, and adaptable platform for developing real-time temperature monitoring solutions.

????? Proposed System Architecture

Core Components

• Microcontroller: Raspberry Pi Pico

• Sensors: DS18B20 (digital) or LM35 (analog)

• Display: LCD or OLED screen for real-time temperature visualization

• Connectivity: Wi-Fi (ESP8266/ESP32) or Bluetooth for remote data access

• Storage: Onboard memory or external storage for logging data

Key Functionalities

1. Temperature Sensing: Continuous ambient temperature measurement.

2. Data Acquisition: Signal processing via GPIO pins and ADC (if analog).

3. Real-Time Display: Temperature shown on local screens or serial monitor.

4. Remote Monitoring: Wireless data transfer to cloud or mobile apps.

5. Data Logging: Storage of historical data for analysis.

6. Threshold Alerts: Notifications (LED/buzzer/alerts) when values exceed limits.

7. Low Power Operation: Optimized for battery-powered or remote deployment.

???? Advantages over Existing Systems

???? Features and Applications

Distinctive Features

• ? High Accuracy

• ? Real-Time Feedback

• ? Low Power Consumption

• ? Versatile Display Options

• ? Wireless Connectivity (Wi-Fi/Bluetooth)

• ? Historical Data Logging

• ? Threshold-Based Alerts

• ? Cost-Effectiveness

Use Cases

• Residential: Room temperature control, appliance monitoring

• Industrial: Machine/process temperature regulation

• Healthcare: Storage of medicines, lab environments

• Agriculture: Crop field and greenhouse monitoring

• Laboratories: Experimental temperature tracking

?? Challenges and Limitations

???? Future Work Directions

1. Sensor Calibration Improvements – Adaptive/self-calibrating mechanisms.

2. Environmental Interference Mitigation – Use of filtering or ML-based noise handling.

3. Hybrid System Architecture – Combine Pico with edge/cloud servers.

4. Embedded Wireless Modules – Custom boards with built-in connectivity.

5. Energy Optimization – Renewable energy and low-power strategies.

6. IoT Platform Integration – Real-time cloud visualization and analytics.

7. Multi-Sensor Networks – Monitor humidity, pressure, gas, etc.

8. Machine Learning Applications – Anomaly detection, predictive modeling.

9. Advanced Communication Protocols – LoRa, NB-IoT, or 5G for wide-area deployments.

Conclusion

The present study demonstrates the successful development and implementation of a temperature monitoring system based on the Raspberry Pi Pico microcontroller. The system provides a cost-effective, energy-efficient, and reliable solution for real-time temperature measurement, display, and data acquisition. Integration of digital and analog temperature sensors, such as the DS18B20 and LM35, with the Pico enables accurate monitoring of ambient conditions across diverse environments.

References

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Copyright

Copyright © 2025 S. Sanjay, I. Akash Selvan, A. Inbaraj, R. RajaMani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.