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Address-based Integration of Building Open Data Using OpenAPI - A Case Study of the Korean Public Institution Building List - 건축물 주소 기반의 OpenAPI를 활용한 공공데이터 연계 방안 - 공공기관 목록 사례분석 -
Abstract
The purpose of this article is to present an actual case study of address-based integration of public open application programming interface (OpenAPI), by developing a system for the address-based integration of the public OpenAPI, with the road name address as a reference point. In addition, this paper suggests improvements for the OpenAPI integration by investigating error cases of the system. The developed system for the integration includes an algorithm to assist integration and two OpenAPIs: Address searching API from the Ministry of Interior and Safety, and Building legister API from the Ministry of Land, Infrastructure and Transport. The address-based integration through the system is presented, with the data contains Addresses of public institutions from All public information all-in one (ALIO) and public health organizations from the Ministry of Health and Welfare. Result of the integration showed that 83 addresses among 587 addresses were unable to integrate. Based on the result, this paper classified these error cases into six categories, discovered reasons for the unavailability through expert meeting and suggested improvements. This paper mainly contributes to the analysis of actual cases of the public OpenAPI integration without constructing an additional database. Further study should be performed to develop the algorithm and to expand the range of the API integration. It is to be hoped that this paper will serve as a basis for better road address-based utilization of the public data in the construction field.
... Open APIs play a crucial role in enabling different software applications to communicate and share data effectively [150][151][152][153][154][155]. By incorporating open APIs, BIM like platforms can seamlessly interact with AI algorithms and IoT sensors [153], fostering the development of tailored solutions and applications to meet specific project needs [151,[156][157][158][159][160]. ...
The fusion of Artificial Intelligence (AI) and the Internet of Things (IoT) has brought about a paradigm shift in the realm of architecture, engineering, and construction (AEC), introducing intelligent sensing technologies that significantly enhance monitoring and control. This study delves into the varied applications, hurdles, and prospects emerging from the collaborative deployment of AI and IoT-based sensors within the AEC domain. AI-equipped smart sensors enable real-time monitoring of structural health, energy consumption, and environmental conditions in both buildings and infrastructure. These technologies empower predictive maintenance, ensuring the durability of structures while minimizing downtime. Additionally, AI-driven analytics optimize resource allocation, improve safety protocols, and streamline construction processes, thereby enhancing overall project efficiency. Through ongoing analysis of data collected by sensors integrated into HVAC systems, elevators, and lighting, maintenance teams can pre-emptively tackle potential malfunctions. Furthermore, the synergy between AI and IoT enables the development of intelligent buildings with adaptive features. Sensors that examine occupancy patterns, lighting preferences, and temperature fluctuations play a pivotal role in crafting energy-efficient and occupant-centric building designs. The security and privacy concerns associated with sensor-generated data give rise to critical issues that necessitate robust cybersecurity measures. Interoperability challenges among diverse sensor networks and AI platforms also present obstacles to seamless integration. Furthermore, the adoption of these technologies demands substantial investments in infrastructure and workforce training, requiring a strategic approach for widespread acceptance. The paper explores how the predictive capabilities of AI-driven sensors contribute to risk mitigation and cost reduction across the entire project lifecycle. Moreover, the ability to collect and analyze vast amounts of data empowers stakeholders to make well-informed decisions, fostering innovation and sustainability in the AEC industry. By addressing pivotal issues and underscoring potential benefits, it provides invaluable insights for industry professionals, researchers, and policymakers eager to harness the transformative potential of intelligent technologies in architecture, engineering, and construction.
Keywords: Artificial Intelligence, Internet Of Things, Sensors, Monitoring, Construction industry, Smart city, Automation, Construction sites.
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