Proposes a method to improve IoT networks' performance through predictive big data processing, highlighting its efficiency in communications.
the net of things (IoT) promises to revolutionize the way humans interact with their surroundings. Notwithstanding this promise, the deployment of IoT networks is hindered by using several challenges, particularly related to communication, scalability, and electricity performance. This paper proposes a technique to address those demanding situations through predictive big statistics processing blended with the use of new network technology. In particular, the use of prediction fashions, system studying, and analytics algorithms will permit IoT networks to investigate past and present facts in order to forecast destiny traits. Additionally, the use of latest and existing network technologies, which include extremely-low strength mesh networks, 5G, and electricity-conscious network routing protocols will help to improve the overall performance of IoT networks. In conclusion, this paper gives a method to decorate the characteristic of IoT networks through predictive big statistics processing as a way to permit more effective, efficient, and reliable communique for all related devices.
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Jain et al. (2024) studied this question.
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