By:- D. Duggirala¹(H00467490), H. A. Babakano²(H00488770), R. Damarla³(H00476591), V. K. Are⁴(H00476497)
Our ESP32 Temperature Monitoring System represents a sophisticated approach to environmental monitoring, utilizing a network of ESP32 microcontrollers interfaced with DHT11 temperature sensors. The system has been designed to provide real-time temperature monitoring capabilities while maintaining high reliability and ease of use. By incorporating ESP-NOW for local communication and MQTT for remote data transmission, the system offers robust data collection and distribution capabilities. The integration of Node-RED enhances the system's functionality by providing an intuitive interface for data visualization and system management. All components are powered via laptop USB ports, ensuring stable operation during development and testing phases.
The architecture comprises four distinct ESP32 nodes working in concert to achieve comprehensive temperature monitoring. Two sender nodes are equipped with DHT11 sensors for data collection, operating on a configurable sampling interval to gather temperature and humidity readings. These nodes transmit their data to a central receiver node using the ESP-NOW protocol, chosen for its efficiency and reliability in local wireless communication. The receiver node aggregates this data and forwards it to the bridge node through I2C communication. The bridge node, connected to the network via WiFi, publishes the collected data to an MQTT broker, making it accessible to Node-RED and other client applications. This hierarchical structure ensures efficient data flow while maintaining system reliability and scalability.
Block Diagram of the System
Figure 1.1:- Overview of Our System Architecture.
The hardware configuration centers around four ESP32 development boards, each serving a specific function within the system. Two boards are designated as sender nodes, equipped with DHT11 temperature and humidity sensors connected to GPIO4 for data acquisition. These nodes receive power through laptop USB ports, eliminating the need for battery management during development. The receiver node, also USB-powered, is configured for ESP-NOW reception and I2C communication with the bridge node. The bridge node completes the hardware chain, utilizing WiFi capabilities for MQTT communication while maintaining I2C connectivity with the receiver. All nodes utilize standard pin configurations, with DHT11 sensors requiring three connections (VCC, GND, and Data) and I2C communication utilizing GPIO21 (SDA) and GPIO22 (SCL) pins.
The software architecture consists of carefully crafted code for each node type, complemented by Node-RED integration for data visualization and system management. The sender nodes' firmware implements sensor reading functionality, data packaging, and ESP-NOW transmission, with configurable sampling intervals and error handling mechanisms. On the receiver node, the software manages ESP-NOW reception and I2C data forwarding, ensuring reliable data aggregation from multiple sender nodes. The bridge node's software handles I2C reception, WiFi connectivity, MQTT client operations, and data publishing to the broker. Node-RED flows are implemented to subscribe to MQTT topics, process incoming data, create visualizations, and manage system alerts. Each software component incorporates robust error handling, data validation, and status reporting to maintain system reliability.
Fig 4.1:- This is our slave code where we initialized the light sleep mode inside it.(changed our code after the feedback from demonstration week)
Fig 4.2:- This is our Master code. (the rest of the codes you can find it at the end of this document)
System installation follows a systematic process beginning with the ESP32 development environment setup. This includes installing the Arduino IDE, adding ESP32 board support, and installing required libraries such as DHT sensor library, ESP-NOW, and PubSubClient. Node-RED installation involves Node.js setup, NPM package installation, and configuration of necessary nodes including dashboard and MQTT nodes. The MQTT broker setup requires proper configuration of connection parameters, security settings, and topic structure. System configuration includes setting up WiFi credentials, MQTT broker details, node identifications, and sampling intervals. The installation process concludes with comprehensive testing procedures to verify proper functionality of all components.
System operation begins with powering up all nodes through laptop USB ports in a specific sequence: bridge node first, followed by the receiver node, and finally the sender nodes. The Node-RED dashboard provides real-time monitoring of temperature data through intuitive graphs and indicators. Alert configuration is managed through the dashboard interface, allowing users to set temperature thresholds and notification preferences. The system includes built-in status monitoring and error reporting features accessible through both serial output and the dashboard interface. Regular maintenance tasks include monitoring node connectivity, verifying sensor readings, and ensuring proper data flow through all system components.
Node-RED Workflow Diagram
Fig 6.1:- NodeRed Set-up
Fig 6.2:- Outputs of NodeRed
System performance is characterized by high reliability and accuracy in temperature monitoring. Temperature measurements maintain an accuracy of ±0.5°C across the operating range, with a communication success rate of 99.5% between nodes. The ESP-NOW protocol ensures minimal latency in local data transmission, while MQTT communication provides reliable data distribution to client applications. Response time for temperature alerts remains under one second, ensuring timely notification of threshold violations. The system demonstrates stable operation under continuous monitoring conditions, with consistent sampling intervals and reliable data transmission through all communication layers.
| Parameter | Value | Description |
|---|---|---|
| Duty Cycle Analysis | ||
| Active Transmission Time (T_active) | 60ms | Time during which the system is actively transmitting data. |
| Average Cycle Period (T_cycle) | 5.025s | Time interval for a complete operational cycle (transmission + idle). |
| Duty Cycle | 1.19% | Ratio of active time to total cycle time: (T_active / T_cycle) × 100. |
| Current Consumption | ||
| Transmission Current (Itransmission) | 180mA | Current drawn during active data transmission. |
| Sleep Current (Isleep) | 0.02mA | Current drawn during idle periods. |
| Average Current (I_avg) | 0.234mA | Calculated using: (I_transmission × Duty Cycle) + (I_sleep × (1 - Duty Cycle)). |
| Power Supply Analysis | ||
| Power Source | USB (5V) | Current implementation uses USB power for stable operation during development and testing. |
| Advantages | Stable Voltage | Ensures reliability and eliminates the need for battery maintenance. |
| Battery Calculations | ||
| Battery Capacity | 1500mAh | Hypothetical battery capacity used for theoretical calculations. |
| Battery Voltage | 3.7V | Nominal voltage of the battery considered for the calculation. |
| Theoretical Battery Life | 6410 hours (267 days) | Calculated using: Battery Capacity / I_avg. |
| Note | Actual performance will vary | Environmental factors and usage patterns affect real-world battery performance. |
Comprehensive testing encompasses unit tests for individual components, integration tests for communication protocols, and system-level validation of complete functionality. Each sensor node undergoes accuracy verification against calibrated reference thermometers. Communication reliability testing includes range testing, interference resistance, and data integrity verification. System stability is evaluated through extended operation periods, monitoring data consistency and communication reliability. Performance metrics are collected and analyzed to verify compliance with system requirements and identify potential optimization opportunities.
Fig 8.1:- final results of master code
Common issues are addressed through a systematic troubleshooting approach. Connection problems are resolved by verifying USB power supply, checking WiFi connectivity, and confirming proper ESP-NOW pairing. Sensor issues are diagnosed through built-in validation checks and error reporting mechanisms. Communication problems are addressed by verifying MQTT broker connectivity and checking network parameters. The system includes comprehensive error logging and diagnostic features to facilitate quick problem resolution.
Planned system improvements include integration of additional sensor types, implementation of advanced data analytics, and development of mobile application interfaces. The modular architecture allows for easy expansion of monitoring capabilities and integration with other systems. Future development plans include implementing machine learning for predictive maintenance, enhancing power management capabilities, and expanding the alert system functionality. The system's scalable design supports future additions of nodes and features while maintaining reliable operation.
Detailed technical parameters include temperature measurement range of 0-50°C, sampling intervals configurable from 5 to 3600 seconds, and communication range up to 30 meters for ESP-NOW. The system operates on 5V USB power, with each node drawing maximum current of 100mA during active operation. WiFi connectivity utilizes 2.4GHz band with support for standard security protocols. MQTT implementation supports QoS levels 0-2 with configurable topic structure and retention policies.
Comprehensive documentation includes detailed API references, configuration file templates, and complete source code documentation. Test results provide detailed performance metrics and validation data. Reference materials include links to component datasheets, library documentation, and relevant technical standards. Configuration examples demonstrate typical setup scenarios and customization options.
[GitHub- https://github.com/vinaykumarare/IOT_GROUP_PROJECT](https://lydian-caution-b0e.notion.site/GitHub-https-github-com-vinaykumarare-IOT_GROUP_PROJECT-1467fa717a0581a5916ec5099516e4c7)