Aquaculture Monitoring With Machine Learning Technique

In this era of science and technology machine intelligence has wide range of scope. It can be used to improve the production in various fields. Agriculture is one industry in which machine intelligence is expected to have significant impacts. Research in this area is new but growing rapidly; so, expert system researchers and practitioners are always struggling to keep pace with research progress in this region. This paper reports on a systematic review of research in the application of Machine Intelligence. Moreover we are implementing Machine Intelligence to increase the production of fishes by monitoring the properties of water as well as environment. There are various factors to be monitored such as pH value, dissolved oxygen, salinity, temperature etc. which is responsible to maintain favorable condition for the water ecosystem. Hence continuous monitoring of data read through sensors make farmers easy to maintain the suitable condition. This leads to the increased production in aquaculture. To this end, therefore, there is still the need for more research to better understand, characterize and evaluate and implement the utility of Machine Intelligence in agriculture. This leads to the significant improvement in the production to fulfill the demands of the population. Also, advanced use of Machine Learning based aquaculture leads to the automation in monitoring which absolutely improves the production.