Dynamic Public Participation Methodology: Integrated Long Short Term Memory Networks approach from Artificial Intelligence Field to Rebuild Public E-participation System

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Abstract Summary
Planning communities share one common agreement that the structure of public e-participation system reflecting citizens’ intentional choice and co-ordination is essential to improve participation effectiveness and degree of empowerment. In fact, various of public e-participation approaches have embedded in the planning process, with a large amount of research on detailed technical tools only. Information and Communication Technology tools (ICTs), for example, in Lukasz Damurski’s opinion, could give new opportunities for citizen involvement and strongly influences public decision-making systems. However, given the experience from practical projects, upgrading public participation tools with advanced high-technological concepts could not deal with the low use of e-participation. The problem is hard to make strong connection between citizen’s perspective and final planning “blue print”, especially in the country functioning “top-down” pattern of planning governance. Considering limitations of time and labor cost, existing public e-participation only plays a passive role in the planning procedure. Accordingly, this paper focuses on building the dynamic architecture of public e-participation system which lacks concentration from both theoretical and practical fields compared to tools-related topics. With development of Artificial Intelligence, Long Short Term Memory networks (LSTMs), as one of core methods, instead of having a single neural network layer, there are multiple layers interacting wisely and effectively. LSTMs apply recurrent neural networks allowing information to persist. The paper aims to integrate LSTMs methodology, allowing “public participation” information to persist and make influence on each step over urban planning process, via scanning existing public e-participation system, identifying challenging questions, and applying an experimental demo to test reliability of the system. The Dynamic Public E-Participation takes advantage of LSTMs structure, which could break limitations of physical space and time spam to share data of public participation from different places in the world. Moreover, the system could monitor the real time process of a project, mark changes made because of the public participation, and access to multi-disciplinary databases, like city mobility database, which could deal with problem of existing public participation system. A key challenge, also as future research directions, is public data ethics and how to balance interests among professional planning expertise, political fairness, and public willingness.
Abstract ID :
ISO169
Submission Type
Urban Planner
,
Shanghai Tongji Urban Planning & Design Institute Co.Ltd.

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