Abstract
The integration of Artificial Intelligence (AI) into the dredging systems and dredging machinery used in "capital" and "maintenance" dredging in Bangladesh can enhance the efficiency of the machines and dredging process, enabling the operators to perform regular and repetitive dredging tasks safely in the rivers, ports, and estuaries all over the country. AI, including Big Data, Machine Learning, Internet of Thing, Blockchain and Sensors and Simulators with their catalytic potentials, can systematically compile and evaluate specific data collected from different sources, develop applications or simulators, connect the stakeholders on a virtual platform, store lakes of information without compromising their intellectual rights, predicting models to harness the challenges, minimise the cost of dredging, identify possible threats and help protect the already dredged areas by giving timely signals for further maintenance. Furthermore, the application of AI modulated dredging devices and machinery can play a significant role when monitoring aspects becomes crucial, keeping environmental impacts mitigated without affecting the quality of the human environment. This study includes the evaluation of the application of AI – its prospect and challenges in the existing dredging systems in Bangladesh against the backdrop of the challenges faced in capital and maintenance dredging in the major rivers – and assess whether such inclusion of AI is likely to minimise the cost of dredging in the rivers of Bangladesh and facilitate the materialisation of the objectives of Bangladesh Delta Plan 2100.This paper studies the organisation's infrastructural requirement for the integration of AI into dredging systems, using benchmarking such as 1- "Understanding AI Ready Approach", 2-"Strategies for Implementing AI", 3-"Data Management", 4-"Creating AI Literate Workforce and Upskilling", and 5-"Identifying Threats" concerning the management and dredging operations of Bangladesh Inland Water Transport Authority (BIWTA), under Bangladesh Ministry of Shipping and Bangladesh Water Development Board (BWDB). The paper also uses several case studies such as channel dredging to show that the use of AI can bring a significant change in the dredging operations both in reducing the cost of dredging and in terms of harnessing the barriers in adaptive management and environmental impacts.
Highlights
Dredging is a kind of default setting for Bangladesh, and the country cannot compromise it or replicate, alter, avoid or stop it
The type of machines used in the capital and maintenance dredging in Bangladesh includes Cutter Suction Dredgers (CSD), Backhoe Dredgers (BHD), Water Injection Dredges (WID), Grab Dredgers (GD), Stationary Suction Dredgers (SD) and Trailing Suction Hopper Dredgers (TSHD)
Given the country's current dredging capacity of 84.6 million cubic metres, increasing production capacity by 10% to 15% by existing cutter suction dredgers will undoubtedly reduce the cost of maintaining the navigability of 100 major rivers 7, as approved by the Executive Committee of the National Economic Council (ECNEC) in October 2019
Summary
Dredging is a kind of default setting for Bangladesh, and the country cannot compromise it or replicate, alter, avoid or stop it. The integration of AI along with its associated branches like Big Data, Machine Learning, Internet of Things (IoT), Blockchain and application of Simulators, Actuators, and Sensors can significantly impact upon areas including the management, leadership, data processing, data management, dredging methods, increasing productivity, setting up equipment guidelines, recommended practices and identifying threats. It can impact the efficiency and safety enhancement features of the dredging machines used in Bangladesh and help implement operational best practices among the stakeholders
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