National Institute of Technical Teacher's Training and Research, Chandigarh 160019, India.
Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal.
Int J Environ Res Public Health. 2020 Jul 9;17(14):4942. doi: 10.3390/ijerph17144942.
Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015-2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.
室内空气质量一直是国际科学界关注的问题。公共卫生专家、环境管理部门和行业专家正在努力改善建筑居住者的整体健康、舒适度和幸福感。据报道,反复暴露在室内环境污染物中是导致多种慢性健康问题(如肺癌、心血管疾病和呼吸道感染)的潜在原因之一。此外,智慧城市项目正在推动使用实时监测系统来检测不利的生活环境场景。这项工作的主要目的是对基于物联网的室内空气质量监测系统的最新技术进行系统综述。本文强调了监测系统的设计方面,包括传感器类型、微控制器、架构和连接性,以及在过去五年(2015-2020 年)发表的研究中的实施问题。本文的主要贡献在于提出了现有研究、知识差距、相关挑战和未来建议的综合。结果表明,分别有 70%、65%和 27.5%的研究侧重于监测热舒适参数、CO 和 PM 水平。此外,有 37.5%和 35%的系统基于 Arduino 和 Raspberry Pi 控制器。只有 22.5%的研究在系统实施前遵循校准方法,而 72.5%的系统声称具有节能效果。