Journal of Ubiquitous Computing and Communication Technologies
IRO Journals
Volume 6 — Issue 4 — December 2024

Advanced-Data Processing in IoT using MQTT and OPTICS with Spiking Neural Networks and Mist Computing for Real-Time Analytics

https://doi.org/10.36548/jucct.2024.4.005
Guman Singh Chauhan
John Tesla Inc, California, USA
Joseph Bamidele Awotunde
Faculty of Information and Communication Sciences, University of Ilorin, Ilorin 240003, Kwara State, Nigeria
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How to Cite

Chauhan, Guman Singh, and Joseph Bamidele Awotunde. 2025. “Advanced-Data Processing in IoT Using MQTT and OPTICS With Spiking Neural Networks and Mist Computing for Real-Time Analytics”. Journal of Ubiquitous Computing and Communication Technologies 6 (4): 377-96. https://doi.org/10.36548/jucct.2024.4.005.
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Keywords

— IoT
— MQTT
— OPTICS
— Spiking Neural Networks (SNNs)
— Mist Computing
— Real-time Analytics
Published: 04-02-2025

Abstract

The proposed combination of Message Queuing Telemetry Transport (MQTT), Ordering points to identify the clustering structure (OPTICS), Spiking Neural Networks (SNNs), and Mist computing improves real-time processing of IoT data by tackling issues with event-driven analytics, communication, and clustering. Effective clustering and anomaly detection in big, dynamic datasets are made possible by OPTICS, while MQTT guarantees effective, low-latency communication. Biological neuron-inspired SNNs offer energy-efficient real-time event detection, while Mist Computing decentralizes computing to lower latency and bandwidth consumption. 90% energy efficiency, 92% data throughput, 95% latency reduction, and 97% anomaly detection accuracy are among the notable performance gains the system makes. Smart cities, industrial IoT, and healthcare systems are just a few examples of the sophisticated IoT applications that benefit from this all-inclusive framework's great scalability and efficiency. Through the integration of sophisticated communication protocols, clustering techniques, and real-time processing capabilities, it guarantees accurate, scalable, and energy-efficient answers to contemporary IoT problems.

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