The Internet of Things (IoT) is a rapidly developing industry that currently requires effective monitoring systems to process data in real time and make decisions. In this paper, a new method of multi-hop signal transmission in the IoTs is suggested to be combined with dynamic feedback loops embedded in the Oracle APEX-based monitoring systems. The challenges being addressed in the proposed system are the issues of signal degradation and network congestion. The proposed system is able to increase the efficiency of the network by adjusting to the real-time network conditions, such as packet loss, signal strength, and congestion. The key performance indicators (KPIs) used in the study include throughput, latency, packet loss, and energy consumption to measure the framework. The statistical analysis indicates that the system that has feedback loops will have an improvement of 25% in throughput, 15% reduction in packet loss, and 30% in energy consumption compared to the traditional models. The feedback loops contribute greatly to the optimization of transmission so that IoT operations can be reliable and scalable. There is also optimal utilization of the system energy efficiency, whereby dynamic control commands minimize power usage at the expense of network performance. The performance of the framework, as was assessed, proved to be good in the high-density network settings, with potential to be used on a large scale in smart cities, healthcare, and industrial IoT. The given paper can be of great use in the future since it leads to future research where machine learning-based adaptive feedback and scalability of bigger IoT networks can be studied.
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