Yang Min, Ge Chengmin, Zhao Xiaoran, Kou Huaizhen
Chongqing Vocational Institute of Engineering, Chongqing, China.
Shandong Provincial University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang, China.
J Cloud Comput (Heidelb). 2023;12(1):31. doi: 10.1186/s13677-023-00410-0. Epub 2023 Mar 6.
With the awakening of health awareness, people are raising a series of health-related requirements for the buildings they live in, with a view to improving their living conditions. In this context, BIM (Building Information Modeling) makes full use of cutting-edge theories and technologies in many domains such as health, environment, and information technology to provide a new way for engineers to design and build various healthy and green buildings. Specifically, sensors are playing an important role in achieving smart building goals by monitoring the surroundings of buildings, objects and people with the help of cloud computing technology. In addition, it is necessary to quickly determine the optimal sensor placement to save energy and minimize the number of sensors for a building, which is a de-trial task for the cloud platform due to the limited number of sensors available and massive candidate locations for each sensor. In this paper, we propose a Fast Sensor Placement Location Optimization approach (FSPLO) to solve the BIM problem in cloud-aided smart buildings. In particular, we quickly filter out the repeated candidate locations of sensors in FSPLO using Locality Sensitive Hashing (LSH) techniques to maintain only a small number of optimized locations for deploying sensors around buildings. In this way, we can significantly reduce the number of sensors used for health and green buildings. Finally, a set of simulation experiments demonstrates the excellent performance of our proposed FSPLO method.
随着健康意识的觉醒，人们对居住的建筑提出了一系列与健康相关的要求，以期改善居住条件。在此背景下，建筑信息模型（BIM）充分利用健康、环境和信息技术等诸多领域的前沿理论和技术，为工程师设计和建造各类健康绿色建筑提供了新途径。具体而言，传感器借助云计算技术对建筑物、物体及人员的周边环境进行监测，在实现智能建筑目标方面发挥着重要作用。此外，有必要快速确定最优的传感器布局，以节省能源并使建筑物所需传感器数量最少，鉴于可用传感器数量有限且每个传感器有大量候选位置，这对云平台来说是一项极具挑战性的任务。在本文中，我们提出一种快速传感器布局位置优化方法（FSPLO）来解决云辅助智能建筑中的BIM问题。特别是，我们在FSPLO中使用局部敏感哈希（LSH）技术快速滤除传感器的重复候选位置，仅保留少量用于在建筑物周边部署传感器的优化位置。通过这种方式，我们可以显著减少用于健康绿色建筑的传感器数量。最后，一组仿真实验证明了我们提出的FSPLO方法的卓越性能。
