With the development of artificial intelligence and other associated models like machine learning, data science, industrial internet of things etc. it has become a significant challenge for the majority of the practitioners and researchers in field of environmental monitoring and management to keep pace with. Though many international universities in developed countries are making significant contributions to this field, the obstacle remained constant in Bangladesh. Focusing the background, this study is conducted to understand the challenges to integrate and implication of machine learning regarding environmental monitoring and management in Bangladesh. In this study, 20 surveys and 5 In-depth Interviews were conducted with practitioners from eight top institutes those are working on environmental monitoring and management related issues in government, non-government and academia sectors of Bangladesh. Findings revealed that in case of absence of reliable resources on an average intensity of participants is 9.15, where the Intensity of participants in favor of absence of less exposure of research upshots (average is 8.50). Also, lack of sharing information and absence of available funding are identified as major obstacles. This study may help stakeholders to take proper initiatives to encourage researchers and practitioners regarding utilization of machine learning in Bangladesh.
Cite this paper
Ali, M. , Mukarram, M. M. T. , Chowdhury, M. A. , Karin, S. and Faruq, A. N. (2021). Integration and Implication of Machine Learning: Barriers to Aid Environmental Monitoring and Management. Open Access Library Journal, 8, e7468. doi: http://dx.doi.org/10.4236/oalib.1107468.
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