Luo Chuanwen, Hui Linyuan, Shang Zikun, Wang Chenlong, Jin Mingyu, Wang Xiaobo, Li Ning
Department of Architecture, School of Architecture and Art, North China University of China, Jinyuanzhuang Road 5, Shijingshan District, Beijing 100144, China.
Beijing Historical Building Protection Engineering Technology Research Center, Beijing University of Technology, Beijing 100124, China.
Sensors (Basel). 2024 May 13;24(10):3096. doi: 10.3390/s24103096.
The built environment's impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people's travel experience and travel mode choice. The streets' built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device's power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications.
建成环境对人类活动的影响一直是城市研究中的热点问题。与机动化空间相比，步行和自行车街道空间的建成环境对人们的出行体验和出行方式选择有着显著影响。街道的建成环境数据在城市设计和管理中起着至关重要的作用。然而，建成环境的多源、异构和海量数据采集方法及工具已成为城市设计和管理的障碍。为了更好地实现数据采集并深入了解城市建成环境，本研究开发了一种新型便携式、低成本的基于 Arduino 的多传感器阵列，集成在一个便携式单元中，用于街道自行车空间的建成环境测量。该系统由五个传感器和一个 Arduino Mega 板组成，旨在测量街道自行车空间的特征。它以空气质量、人体感觉、道路质量和绿化为检测对象。集成的颗粒物激光传感器、光强传感器、温度和湿度传感器、噪声传感器以及一台 8K 全景相机用于街道的多源数据采集。该设备具有移动电源显示屏和安全数字卡，以提高其便携性。本研究以北京为例。使用街道建成环境数据采集设备在 36 个工作小时内共采集了 127.97G 的视频数据和 4794Kb 的文本记录。与去年相比，效率提高到了 8474.21%。作为用于类似目的的传统硬件的替代品，该设备无需携带多种类型和型号的传感设备，从而使基于多传感器数据的街道建成环境研究成为可能。其次，该设备的电源和存储能力使其具有便携性、独立性和可扩展性，加速了自主发展。第三，它大大降低了成本。该设备为构思新的研究场景和潜在应用提供了方法和技术基础。
