Based on recent years' work into artificial intelligence (AI) technology implementations in the automotive sector, we are evaluating the accelerated growth of key innovations in the modern age of 'Internet with AI,' that is causing a significant shift in the automotive industry's structures, methods, and ecosystems, as much as in the creation of AI.With many numerous drawbacks i.e., technological complexities and further latency in cloud computing was replaced by edge computing for effective and appropriate resource distribution including power and battery life in internet-based industrial applications (IoT).Through AI collaboration at the edge the flexibility and processing pace of IoT-based systems in industries can be greatly improved.However in such power consuming, low battery lifespan and delay intolerant smart phones, the significant challenge is inadequate and wasteful traditional patterns in the distribution of reasonable resources.Therefore, this paper suggests a data redundancy framework via hybrid TPC and duty-cycle system for edge artificial intelligence powered IoT applications.Experimental results set shows that the new device increases energy performance and battery life at reasonable longevity by changing the service cycle and Reducing power effectively than traditional approaches.