Under Water Waste Cleaning by Mobile Edge Computing and Intelligent Image Processing Based Robotic Fish

Autor:	Sahoo, Subhadeep, Dong, Xiao Han, Liu, Zi Qian, Sahoo, Joydeep
Rok vydání:	2020
Předmět:	Computer Science - Networking and Internet Architecture Computer Science - Distributed Parallel and Cluster Computing Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	As water pollution is a serious threat to underwater resources, i.e., underwater plants and species, we focus on protecting the resources by cleaning the non-biodegradable waste from the water. The waste can be recycled for further usage. Here we design a robotic fish which mainly comprises optical biosensor, camera module, piston module, and wireless transceiver. By exploiting the LTE and 5G network architecture, the fish stores the information about the underwater waste in the nearest mobile edge computing server as well as in the centralized cloud server. Finally, when the fish clears the underwater waste, it offloads the captured image of the located object to the mobile edge computing server or sometimes to the cloud server for making a decision. The servers employ intelligent image processing technology and an adaptive learning process to make a decision. However, if the servers fail to make a decision, then the fish utilizes its optical biosensor. By this scheme, the time delay for clearing any water body is minimized and the waste collection capacity of the fish is maximized. This technique can effectively help the government or municipal personnel for making clean water without manual efforts. Comment: This is an innovative project report awarded by Ericsson Innovation Award 2019
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2009.00072 Zobrazit plný text záznamu View this record from Arxiv