Fire Gas Leakage Detection Housekeeping Robot using ESP32

Fire Gas Leakage Detection Housekeeping Robot using ESP32

Sherin N R

Assistant Professor, Department of Electronics and Communication Engineering Muslim Association College of Engineering Trivandrum, India

Mubarak P J

Student, Department of Electronics and Communication Engineering Muslim Association College of Engineering Trivandrum, India

Ashkar S

Student, Department of Electronics and Communication Engineering Muslim Association College of Engineering Trivandrum, India

Aseem Manoj

Student, Department of Electronics and Communication Engineering Muslim Association College of Engineering Trivandrum, India

Akber Saifudeen

Student, Department of Electronics and Communication Engineering Muslim Association College of Engineering Trivandrum, India

Abstract – Fire incidents and combustible gas leaks present serious dangers in homes, workplaces, laboratories, and storage areas. Traditional re and gas detection systems are typically xed in place, restricting their coverage to specic spots and rendering them ineffective at identifying hazards in remote or blocked areas. This paper describes the design and development of an ESP32-powered autonomous housekeeping robot that can carry out environmental monitoring and cleaning tasks at the same time. The system combines an MQ-2 gas sensor for detecting ammable gases, an infrared ame sensor for identifying res, ultrasonic and infrared sensors for avoiding obstacles, a motor driver for self-guided movement, and a vacuum mechanism for cleaning purposes. An ACS712 current sensor keeps a constant watch on electrical current levels, while a relay-controlled ventilation unit activates automatically when dangerous gas levels are sensed. The ESP32 microcontroller handles sensor data in real time and triggers the necessary safety measures, including sound-based alerts, automatic airow control, and unobstructed navigation. Testing and evaluation conrm that the robot effectively combines environmental safety monitoring with autonomous cleaning, offering an affordable and practical solution for smart homes, laboratories, academic institutions, and industrial settings.

Index TermsESP32, Housekeeping Robot, Gas Leakage De- tection, Fire Detection, Autonomous Navigation, Vacuum Clean- ing, Embedded Systems, Industrial Safety.

1. INTRODUCTION

   The increasing demand for intelligent automation has ac- celerated the adoption of robotic systems in domestic, com- mercial, and industrial environments. Housekeeping robots

   are no longer limited to cleaning tasks but are increasingly expected to provide additional safety functions such as hazard detection, environmental monitoring, and emergency response. Integrating these capabilities into a single autonomous plat- form can signicantly improve both operational efciency and workplace safety. Fire outbreaks and combustible gas leakages remain among the leading causes of industrial and residential accidents. Hazardous gases such as Liqueed Petroleum Gas (LPG), methane, and propane may accumulate without im- mediate detection, increasing the risk of explosions and re. Conventional detection systems are typically installed at xed locations and cannot effectively monitor large areas or inacces- sible spaces. As a result, hazardous conditions may remain un- detected until they become critical.The increasing demand for intelligent automation has accelerated the adoption of robotic systems in domestic, commercial, and industrial environments. Housekeeping robots are no longer limited to cleaning tasks but are increasingly expected to provide additional safety functions such as hazard detection, environmental monitoring, and emergency response. Integrating these capabilities into a single autonomous platform can signicantly improve both operational efciency and workplace safety. Fire outbreaks and combustible gas leakages remain among the leading causes of industrial and residential accidents. Hazardous gases such as Liqueed Petroleum Gas (LPG), methane, and propane may accumulate without immediate detection, increasing the risk of explosions and re. Conventional detection systems are

   typically installed at xed locations and cannot effectively monitor large areas or inaccessible spaces. As a result, haz- ardous conditions may remain undetected until they become critical.

2. RELATED WORK

   Autonomous mobile robots have gained signicant attention in recent years due to their ability to perform repetitive tasks with minimal human intervention. In domestic and industrial environments, robotic platforms have been widely employed for oor cleaning, surveillance, warehouse automation, and environmental monitoring. Recent advancements in embed- ded systems and Internet of Things (IoT) technologies have further enhanced the intelligence and functionality of these robots.Several studies have proposed autonomous cleaning robots equipped with ultrasonic and infrared sensors for obstacle detection and navigation. These robots efciently perform cleaning tasks by avoiding collisions and adapting their movement to dynamic environments. However, most commercially available cleaning robots focus primarily on housekeeping functions and provide limited environmental safety monitoring. Fire and combustible gas detection systems have also been extensively investigated for residential and industrial safety. Sensors such as the MQ-2 gas sensor and infrared ame sensor are commonly used to detect hazardous gases and re at an early stage. Although these systems improve safety, they are generally installed at xed locations, restricting their monitoring capability to specic areas. Recent research has explored the integration of environmental sensing with autonomous robotic platforms. By combining gas sensors, ame detectors, obstacle avoidance, and embedded controllers such as the ESP32, mobile robots can continuously patrol an area while simultaneously identifying hazardous conditions. These systems provide improved coverage compared to sta- tionary monitoring devices and reduce the need for constant human supervision. Despite these developments, many exist- ing robotic systems concentrate on either cleaning or safety monitoring independently. The proposed Housekeeping Robot addresses this limitation by integrating autonomous cleaning, obstacle avoidance, re detection, combustible gas monitoring, electrical current monitoring, and automatic ventilation control into a single ESP32-based platform. This integrated approach enhances operational efciency while providing an economical solution for smart homes, laboratories, and industrial work- places

   the robots movement and safety mechanisms. By combining housekeeping and hazard detection into a single mobile plat- form, the proposed system provides a practical solution for smart homes, laboratories, and industrial environments.

   IV. METHODOLOGY

   The proposed Fire and Gas Leakage Detection Robot with Vacuum Cleaning System continually monitors its surround- ings using the MQ-2 gas sensor, ame sensor, ultrasonic sensor, infrared sensor, and ACS712 current sensor. Two ESP32 microcontrollers are in charge of these sensors. The MQ-2 sensor can detect ammable gases including propane, methane, and LPG, whereas the ame sensor is designed to detect the presence of re. The robots infrared and ultrasonic sensors allow it to move autonomously while avoiding obsta- cles. The ESP32 analyzes sensor data in real time and contrasts it with predened threshold values. If a ame is 2 found, an aberrant urrent condition is found, or the gas concentration over the threshold, the gadget instantly sounds a buzzer to notify the user. The robot keeps moving inside the monitoring area while the vacuum cleaning apparatus gathers dust and debris. The ACS712 sensor, which continuously checks current use to maintain electrical safety, enables the system to deliver autonomous navigation, real-time danger assessment, cleaning, and dependable performance in both home and commercial settings.

   A. BLOCK DIAGRAM

   The system consists of six major functional units

   Fig. 1: System Block Diagram1

3. PROPOSED SYSTEM

The proposed Housekeeping Robot is an autonomous em- bedded system designed to perform oor cleaning while continuously monitoring the surrounding environment for haz- ardous conditions such as combustible gas leakage and re. The system integrates multiple sensors with an ESP32 micro- controller to achieve intelligent navigation, obstacle avoidance, environmental monitoring, and automatic safety response. The ESP32 serves as the central controller, collecting sensor data, executing decision-making algorithms, and controlling

Fig. 2: System Block Diagram2

1. Processing Unit The ESP32 microcontroller functions as the central processing unit of the robot. It continuously acquires sensor data, processes environmental information, controls motor movement, and activates safety mechanisms whenever abnormal conditions are detected. Its built-in Wi-Fi capability also enables future integration with IoT monitoring platforms.

2. Environmental Monitoring Unit Environmental safety is achieved using an MQ-2 gas sensor and an infrared ame sen- sor. The MQ-2 sensor continuously measures the concentration of combustible gases such as LPG, methane, and propane. When the detected concentration exceeds a predened thresh- old, the ESP32 identies the condition as hazardous. The ame sensor detects infrared radiation emitted by open ames. Upon re detection, the controller immediately initiates an emergency response by activating local warning mechanisms.

3. Navigation and Obstacle Detection Unit The robot em- ploys an HC-SR04 ultrasonic sensor together with infrared obstacle sensors to enable autonomous navigation. The ul- trasonic sensor measures the distance to nearby obstacles by transmitting ultrasonic pulses and calculating the echo return time. Infrared sensors assist in detecting nearby objects and improving navigation accuracy, particularly at short distances. Based on sensor inputs, the ESP32 determines the appropriate movement direction to avoid collisions while ensuring efcient area coverage during cleaning.

4. Cleaning Mechanism The housekeeping function is per- formed using a DC- powered vacuum cleaning unit mounted on the robot chassis. The vacuum motor operates continuously while the robot navigates through the environment, collecting dust and small debris from the oor surface. This allows the robot to perform cleaning simultaneously with environmental monitoring.

5. Electrical Safety Unit An ACS712 current sensor con- tinuously monitors the current consumed by the electrical system. Abnormal current values may indicate motor overload, short circuits, or component malfunction. Monitoring current consumption enhances system reliability and enables early identication of electrical faults.

6. Ventilation and Alert System Whenever hazardous gas concentration is detected, the ESP32 activates a relay module connected to an exhaust fan or ventilation system. Simultane- ously, a buzzer provides an audible warning to nearby users. This dual-response mechanism helps reduce gas accumulation while immediately informing occupants about the hazardous condition.

   • MQ-2 Gas Sensor

   • Flame Sensor

   • Ultrasonic Sensor

   • Infrared Sensors

   • ACS712 Current Sensor

These measurements provide real-time information re- garding environmental safety, robot movement, and elec- trical system health.

Step 3: Autonomous Navigation Distance information obtained from the ultrasonic and infrared sensors is analyzed by the ESP32. If an obstacle is detected, the con- troller automatically changes the robots direction while maintaining continuous cleaning operation. This enables autonomous movement without human intervention.

Step 4: Hazard Detection Sensor measurements are con- tinuously compared with predened safety thresholds. If combustible gas is detected, the ESP32 activates the ventilation relay and buzzer.

Step 5: Continuous Cleaning While performing naviga- tion and environmental monitoring, the vacuum cleaning motor remains active, allowing simultaneous housekeep- ing and safety surveillance.

A. ALGORITHAM

Fig. 3: Flowchart

1. SYSTEM OPERATION

   The proposed robot operates through the following se- quence.

   Step 1: Initialization After power-up, the ESP32 initializes all connected sensors, motor driver circuits, relay modules, and cleaning motor. Sensor calibration is performed before entering autonomous operation.

   Step 2: Continuous Monitoring The controller continuously reads data from:

   Fig. 4: Flowchart

   The complete system workow can be summarized as follows: Initialize ESP32 and peripheral devices.Activate the vacuum cleaning mechanism.Acquire data from gas, ame, obstacle, and current sensors.Navigate au- tonomously while avoiding obstacles.Compare sensor readings with predened safety thresholds. If haz- ardous gas is detected:Activate relay-controlled venti- lation.Activate buzzer. If re is detected:Generate an emergency alert. Continue monitoring and cleaning until system shutdown.The proposed methodology enables the robot to perform multiple tasks simultaneously, including autonomous cleaning, environmental hazard detection, obstacle avoidance, and electrical safety monitoring. The modular architecture also allows future integration of additional sensors, IoT connectivity, and articial intel- ligence for enhanced autonomous decision-making.

2. RESULTS AND DISCUSSION

   The proposed housekeeping robot was developed using an ESP32 microcontroller integrated with an MQ-2 gas sensor, infrared ame sensor, HC-SR04 ultrasonic sensor, infrared obstacle sensors, ACS712 current sensor, relay module, and a DC-powered vacuum cleaning mecha- nism. The prototype was tested under controlled indoor conditions to evaluate its navigation, cleaning capability, and environmental safety monitoring.Experimental ob- servations showed that the robot successfully navigated through the test environment while avoiding stationary obstacles using ultrasonic and infrared sensor feedback. The vacuum cleaning mechanism operated continuously during movement, enabling simultaneous housekeeping and environmental monitoring. The MQ-2 sensor reliably detected combustible gases when exposed to LPG and similar gases, triggering the relay- controlled ventilation system and audible buzzer. The ame sensor responded effectively to nearby re sources by generating immediate warning signals. Current measurements obtained from the ACS712 sensor enabled continuous monitoring of the electrical system, helping identify abnormal operating conditions.The integrated operation of navigation, clean- ing, hazard detection, and safety response demonstrated that the proposed robot can perform multiple functions simultaneously without signicant processing delay. The ESP32 efciently coordinated all sensing and control operations, making the system suitable for smart home and industrial monitoring applications.The comparison indicates that the proposed system extends the function- ality of conventional housekeepig robots by integrating environmental safety monitoring and emergency response features while maintaining a compact and economical embedded design.

3. ACKNOWLEDGMENT

   The authors sincerely thank the Department of Electron- ics and Communication Engineering, Muslim Association College of Engineering (MACE), APJ Abdul Kalam

   Technological University, for providing laboratory facil- ities, technical guidance, and continuous encouragement throughout the development of this project.

4. CONCLUSION

   This paper presented the design and implementation of an ESP32-based autonomous housekeeping robot capa- ble of performing oor cleaning while simultaneously monitoring environmental safety conditions. The inte- gration of combustible gas detection, re detection, ob- stacle avoidance, electrical current monitoring, and au- tomatic ventilation provides a comprehensive solution for intelligent indoor safety applications. Experimental evaluation conrmed reliable operation of the sensing modules and autonomous navigation mechanism under controlled conditions. The proposed system demonstrates that multiple safety functions can be integrated into a single embedded robotic platform without signicantly increasing system complexity or implementation cost. Future work may include cloud-based IoT monitoring, mobile application integration, simultaneous localization and mapping (SLAM), machine learning-based obstacle recognition, and autonomous path optimization for im- proved cleaning efciency.

5. CONCLUSION

   The proposed IoT-Based Harmful UV Rays Detector con- tinuously measures ultraviolet radiation and alerts users whenever harmful exposure occurs. Cloud connectivity enables remote monitoring and historical data analysis, making the system suitable for environmental monitoring applications.

6. REFERENCES

1. P. Gokhale, O. Bhat, and S. Bhat, Introduction to iot, International Advanced Research Journal in Science, Engineering and Technology, vol. 5, no. 1,

   pp. 4144, 2018.

2. A. Goldsmith, Wireless communications. Cam- bridge university press, 2005.

3. T. Salman and R. Jain, A survey of protocols and standards for internet of things, arXiv preprint arXiv:1903.11549, 2019.

4. A. Meddeb, Internet of things standards: Who stands out from the crowd? IEEE Communica- tions Magazine, vol. 54, no. 7, pp. 4047, 2016.

5. T. Asafa, T. Afonja, E. Olaniyan, and H. Alade, Development of a vacuum cleaner robot, Alexan- dria engineering journal, vol. 57, no. 4, pp. 2911

   2920, 2018.

6. I. Ulrich, F. Mondada, and J.-D. Nicoud, Au- tonomous vacuum cleaner, Robotics and au- tonomous systems, vol. 19, no. 3-4, pp. 233245,

   1997.

7. Y. N. Asafe, A. J. Oyeranmi, O. A. Olamide, and

   A. O. Abigael, Gas leakage detector and monitor- ing system, International Journal of Engineering and Manufacturing, vol. 12, no. 5, pp. 5665,

   2022.

8. A. Manhas, N. Chambyal, M. Raina, S. Dutta, and E. P. Singh, Lpg gas leakage detection using iot, International Journal of Scientic Research in Science and Technology, pp. 520526, 2021.

9. F. Khan, Z. Xu, J. Sun, F. M. Khan, A. Ahmed, and Y. Zhao, Recent advances in sensors for re detection, Sensors, vol. 22, no. 9, p. 3310, 2022.

10. F. Saeed, A. Paul, A. Rehman, W. H. Hong, and

    H. Seo, Iot-based intelligent modeling of smart home environment for re prevention and safety, Journal of Sensor and Actuator Networks, vol. 7, no. 1, p. 11, 2018.

11. S. R. Devanhalli, H. Wagh, and P. K. Vasani, Study of auto cut off electricity power supply on full charge of battery using microcontroller, International Journal of Innovative Research in Technology, vol. 6, p. 12, 2020.

12. A. F. Nurrohmat, D. M. Sopian, K. I. H. Pradipta,

    P. H. Suci, W. Luthana, A. P. Wahyu, et al., Electric current monitoring system using a mi- crocontroller and iot module, Central Asia & the Caucasus (14046091), vol. 23, no. 1, p. 4108,

    2022.

13. M Manasa, T. Vidyashree, V Bindushree, P. Gowra, et al., Smart vacuum cleaner, Global Transitions Proceedings, vol. 2, no. 2, pp. 553

    558, 2021.

14. A. Solo´rzano et al., Early re detection based on gas sensor arrays: Multivariate calibration and validation, Sensors and Actuators B: Chemical, vol. 352, p. 130 961, 2022.

15. L Schynowski et al., Development of a pre- ignition re detection sensor system, 2024 In- ternational Conference on Environmental Systems, 2024.

16. E. TUYISHIMIRE, Design of an iot-based loads priority and predictive maintenance for industrial transformer systems, Ph.D. dissertation, 2023.

17. F. Oliveira, D. G. Costa, F. Assis, and I. Silva, Internet of intelligent things: A convergence of embedded systems, edge computing and machine learning, Internet of Things, vol. 26, p. 101 153, 2024.

18. T. Nesti, S. Boddana, and B. Yaman, Ultra-sonic sensor based object detection for autonomous vehi- cles, in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2023,

    pp. 210218.

19. A. Alam et al., Object detection learning for in- telligent self automated vehicles, in IASC, vol. 34, 2022, p. 941.