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@article{200366,
        author = {Palem Krishna Vamsi Reddy and Palem Suresh and Pallapothula Lakshmi Reddy and Pathuri Swaran Teja},
        title = {IoT-Based Fire Detection and Real-Time Notification System Using Cloud Services},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1238-1248},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200366},
        abstract = {The rapid detection of fire hazards is a critical challenge in urban and industrial safety, where traditional localized alarms often fail to provide remote notification during emergencies. This research proposes an intelligent, cloud-integrated fire detection system that leverages the Internet of Things (IoT) to ensure real-time monitoring and global accessibility. The system utilizes a high-sensitivity flame sensor interfaced with an ESP8266 Wi-Fi microcontroller to capture infrared signatures associated with combustion. Upon detection, the hardware triggers a local buzzer for immediate on-site evacuation while simultaneously transmitting the hazard data to the Thing Speak cloud platform for remote logging. The data management layer of the project employs the Thing Speak API to facilitate seamless communication between the hardware and software components. A backend script developed in Python programmatically retrieves the stored sensor data from the cloud to perform status analysis and trigger digital alerts. To provide an intuitive user experience, a web-based dashboard is developed using HTML and CSS, offering visual representations of the fire status through dynamic indicators and historical logs. This architecture allows homeowners and facility managers to monitor their premises from any internet-enabled device, significantly reducing the gap between ignition and emergency intervention. Experimental results demonstrate that the proposed system achieves high reliability with low communication latency, maintaining a steady connection between the edge device and the cloud. The system successfully distinguishes between ambient light and genuine fire threats, achieving an R² score of 0.94 in stability tests. By combining low-cost hardware with robust cloud analytics, this project offers a scalable and efficient solution for modern disaster mitigation. Ultimately, this research contributes to the development of smart-city infrastructure by providing a functional framework for interconnected, reliable, and affordable fire safety monitoring systems globally.},
        keywords = {IoT, Fire Detection, ESP8266, Thing Speak, Cloud Computing, Flame Sensor, Python, Web Dashboard, Remote Monitoring, API Integration, Real-Time Alerting, Smart Safety, HTML/CSS, Embedded Systems, Data Logging, Infrared Detection, Disaster Mitigation, Internet of Things, Wireless Sensor Networks, Emergency Response.},
        month = {May},
        }