• Ashwini P. Thokale
• Sachin A. Murab
• Parag D. Thakare
• Aniruddha.A. Kolpyakwar

Cloud computing has limitations such as computational complexity and delay. Edge computing is efficient and has fair resource allocation such as power and battery lifetime in internet of things based industrial applications. Co-ordination of AI at the edge will remarkably improve the range and computational speed of IoT based devices in industries. To solve the problem of short battery lifetime, and delay, intolerant portable devices we propose in this paper a forward central dynamic and available approach (FCDAA) by adapting running time of sensing and transmission processes in IoT based portable devices. A system level battery model by evaluating energy dissipiation. A data reliability model for edge artificial intelligence based IoT devices. .

Industrial IoT, Edge Computing, AI, FCDAA, Battery Model.

"A SURVEY ON ARTIFICIAL INTELLIGENCE BASED EDGE COMPUTING PLATFORM FOR INDUSTRIAL APPLICATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.211-214, June 2019, Available :http://www.jetir.org/papers/JETIR1907R33.pdf

"A SURVEY ON ARTIFICIAL INTELLIGENCE BASED EDGE COMPUTING PLATFORM FOR INDUSTRIAL APPLICATIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp211-214, June 2019, Available at : http://www.jetir.org/papers/JETIR1907R33.pdf