• Dr. Aniket Patel
• Parikh Vishva
• Aayush Gajjar

In today’s era the rapid growth of the Internet of Things (IoT) has resulted in a surge of continuous data streams originating from sensors, smart devices, and edge nodes. To extract real-time insights effectively, it is essential to implement efficient data stream processing while addressing challenges such as computational limitations, network latency, and security risks. Decentralized processing through edge and fog computing architectures helps minimize latency and reduce bandwidth usage. However, distributed data mining approaches must strike a balance between efficiency, scalability, and privacy protection. This paper examines effective data stream mining techniques within IoT environments, emphasizing distributed mining in edge and fog computing. It also explores privacy and security challenges related to IoT data streams and outlines potential future research directions.

IoT, Edge Computing, Fog Computing, Data Stream Mining,Distributed Processing

"EFFECTIVE DATA STREAM MINING IN IOT AND EDGE COMPUTING: CHALLENGES, TECHNIQUES, AND FUTURE DIRECTIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.d689-d694, March-2025, Available :http://www.jetir.org/papers/JETIR2503376.pdf

"EFFECTIVE DATA STREAM MINING IN IOT AND EDGE COMPUTING: CHALLENGES, TECHNIQUES, AND FUTURE DIRECTIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppd689-d694, March-2025, Available at : http://www.jetir.org/papers/JETIR2503376.pdf