NLP and ML based approach of increasing the efficiency of environmental management operations and engineering practices

Abstract

Nowadays, environmental preservation is becoming the arena where technological breakthroughs and advances are implemented as the promising way for the future sustainable development of humanity. To provide quality environmental designs and effective environmental policies as their basic functions respectively, environmental engineering and management programs are also faced with acknowledgment of modern technologies in the division of their environmental affairs. This paper proposes an approach that is based on two specific directions of information technologies (natural language processing (NLP) and machine learning (ML)) to increase the efficiency of environmental management policies and engineering practices. Those two fields of informatics are critical points in developing environmental awareness or competencies of environmental managers/engineers since there are many existing occlusions to be removed in developmental path of environmental management/engineering such as less accurate performance of systems, environmentally-savvy technologies for reforms, and so on. Literature review and stakeholder analysis methods are used in reviewing management operations and engineering practices to determine how two directions of computer science help increase the efficiency of those ecological majors and propose research informed guidelines. The results show that machine learning, and natural language processing are keys to performing “minimize risk” job assignments such as predicting and awareness.