Air quality and dust level monitoring systems in hospitals using IoT

被引:0
|
作者
A. Parkavi [1 ]
B. J. Sowmya [2 ]
Sini Anna Alex [3 ]
S. Supreeth [4 ]
G. Shruthi [4 ]
S. Rohith [5 ]
Sudipta Chatterjee [6 ]
K. Lingaraj [7 ]
机构
[1] Ramaiah Institute of Technology,Department of Computer Science and Engineering
[2] Ramaiah Institute of Technology,Department of Artificial Intelligence and Data Science
[3] Ramaiah Institute of Technology,Department of Computer Science and Engineering (AI&ML)
[4] REVA University,School of Computer Science and Engineering
[5] Nagarjuna College of Engineering and Technology,Department of Electronics and Communication Engineering
[6] Brainware University,Department of Electronics and Communication Engineering
[7] Rao Bahadur Y. Mahabaleswarappa Engineering College,Department of Computer Science and Engineering
来源
关键词
Air quality; Dust level; Monitoring systems in hospitals; Internet of things;
D O I
10.1007/s43926-025-00120-w
中图分类号
学科分类号
摘要
Maintaining good indoor air quality is crucial in buildings dedicated to enhancing the health and well-being of their occupants. This challenge becomes even more complex due to the diverse range of users and spaces within a single institution. Different areas, such as operating rooms and waiting rooms, require specific air quality standards, tailored to the varying health conditions of patients and visitors. Poor air quality can hinder hospital staff in performing their duties effectively and affect patients' comfort during recovery. Hospitals can now achieve indoor air quality standards cost-effectively through Internet of Things (IoT) technology. The IoT enables remote monitoring, offering greater control over indoor conditions like air quality, temperature, humidity, and dust levels. This system monitors air quality, dust concentration, temperature, and humidity within healthcare facilities, sending notifications to staff via an app and push alerts when readings exceed normal levels. It utilizes the MQ135 sensor for air quality, the GP2Y1010AU0F optical dust sensor, and the DHT11 sensor for temperature and humidity, all interfaced with NodeMCU through the Arduino IDE. Data from these sensors is stored on a cloud platform and displayed in a mobile app, with near real-time monitoring from sensors placed throughout the facility. A time-series algorithm, such as Autoregressive Integrated Moving Average (ARIMA), is used to forecast temperature and humidity trends in wards. The system alerts staff when indoor temperature exceeds 27 °C, triggers warnings when air quality surpasses 500 ppm, and issues critical alerts for levels above 650 ppm. Sensor data, sent to the cloud every 120 s, provides staff with insights to better plan actions to improve indoor air quality.
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