Abstract

The intelligent monitoring system and smart assistant using IoT technology and built on the Raspberry Pi 3 Model B+ have been designed and implemented as part of this project. The primary differentiating factor of the proposed system is its ability to monitor the health of the users and detect hazards (such as smoke and gas) in the environment and report while having the ability to avoid obstacles and process images using a camera at the same time. The system is made up of several sensors connected to the embedded computing platform to facilitate the collection of data and the ability to process this data in real time and make decisions. The system can be fully programmed in Python, and because this system is designed to be monitored in real time, the embedded platform is connected to the internet, and a monitoring dashboard is created using the Flask web framework. The dashboard enables monitoring and control of the other sensors in the system. The system employs multi-threading architecture to process multiple sensors simultaneously. The system also contains other ready-made systems, such as optical character recognition (OCR), along with voice commands and AI (for user commands) to improve user and system interaction. An emergency is defined as the presence of an uncontrolled fire, gas leak, abnormal human activity, or environmental danger. An alarm system such as a buzzer, along with an email notification, can be activated to alert other systems to take control of the situation. The created platform illustrates an affordable, scalable, and intelligent solution that integrates embedded systems, IoT, computer vision, and automation. Experimental data indicate that the system provides reliable, real-time formation of alerts in response to awareness and environment monitoring. Applications of the proposed system include smart home technologies, monitoring of the elderly and health, surveillance systems, assistive devices, research labs, and industrial safety technology.

References

• Ali, Abd-elmegeid Amin, et al. "Development of an intelligent personal assistant system based on IoT for people with disabilities." Sustainability 15.6 (2023): 5166.
• Pasham, Sai Dikshit. "An Overview of Medical Artificial Intelligence Research in Artificial Intelligence-Assisted Medicine." International Journal of Social Trends 1.1 (2023): 92-111.
• Muthulakshmi, K., et al. "Internet of Things and Smart Intelligence-Based Google Assistant Voice Controller for Wheelchair." Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2023. Singapore: Springer Nature Singapore, 2023. 761-774.
• Netinant, Paniti, et al. "Development and assessment of internet of things-driven smart home security and automation with voice commands." IoT 5.1 (2024): 79-99.
• Hariharan, S., et al. "Voice Controlled Wheelchair for Physically Disabled People and Blind People." Asian Journal of Applied Science and Technology (AJAST) 9.1 (2025): 21-28.
• Manolescu, Vasile Denis, Hamzah AlZu'bi, and Emanuele Lindo Secco. "Interactive conversational AI with IoT devices for enhanced human-robot interaction." Journal of Intelligent Communication (2025).
• Okolo, Gabriel Iluebe, Turke Althobaiti, and Naeem Ramzan. "Smart assistive navigation system for visually impaired people." Journal of Disability Research 4.1 (2025): 20240086.
• Maashi, Mashael, Huda G. Iskandar, and Mohammed Rizwanullah. "IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition." Scientific Reports 15.1 (2025): 6192.
• Eduku, Stephen, et al. "Design and Implementation of a Voice-Controlled Smart Home Automation System." International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN (2025): 2278-3075.
• Manukalpa, J. M., and H. P. Dissanayake. "Empowering Communication for Paralyzed Individuals and Spinal Cord Injury Patients: An Intelligent System With Eye Gaze Tracking, Voice Assistance, and Chat-Bot Integration." International Journal of Latest Technology in Engineering, Management & Applied Science 14.3 (2025): 81-89