Indoor Environment Monitoring System Research Articles

Retracted: Design and Research of Building Indoor Environment Monitoring System Relying on 3D Modeling and Image Processing

Retracted: Design and Research of Building Indoor Environment Monitoring System Relying on 3D Modeling and Image Processing

Indoor CO2 monitoring in a surgical intensive care unit under visitation restrictions during the COVID-19 pandemic.

Indoor CO2 concentration is an important metric of indoor air quality (IAQ). The dynamic temporal pattern of CO2 levels in intensive care units (ICUs), where healthcare providers experience high cognitive load and occupant numbers are frequently changing, has not been comprehensively characterized. We attempted to describe the dynamic change in CO2 levels in the ICU using an Internet of Things-based (IoT-based) monitoring system. Specifically, given that the COVID-19 pandemic makes hospital visitation restrictions necessary worldwide, this study aimed to appraise the impact of visitation restrictions on CO2 levels in the ICU. Since February 2020, an IoT-based intelligent indoor environment monitoring system has been implemented in a 24-bed university hospital ICU, which is symmetrically divided into areas A and B. One sensor was placed at the workstation of each area for continuous monitoring. The data of CO2 and other pollutants (e.g., PM2.5) measured under standard and restricted visitation policies during the COVID-19 pandemic were retrieved for analysis. Additionally, the CO2 levels were compared between workdays and non-working days and between areas A and B. The median CO2 level (interquartile range [IQR]) was 616 (524-682) ppm, and only 979 (0.34%) data points obtained in area A during standard visitation were ≥ 1,000 ppm. The CO2 concentrations were significantly lower during restricted visitation (median [IQR]: 576 [556-596] ppm) than during standard visitation (628 [602-663] ppm; p < 0.001). The PM2.5 concentrations were significantly lower during restricted visitation (median [IQR]: 1 [0-1] μg/m3) than during standard visitation (2 [1-3] μg/m3; p < 0.001). The daily CO2 and PM2.5 levels were relatively low at night and elevated as the occupant number increased during clinical handover and visitation. The CO2 concentrations were significantly higher in area A (median [IQR]: 681 [653-712] ppm) than in area B (524 [504-547] ppm; p < 0.001). The CO2 concentrations were significantly lower on non-working days (median [IQR]: 606 [587-671] ppm) than on workdays (583 [573-600] ppm; p < 0.001). Our study suggests that visitation restrictions during the COVID-19 pandemic may affect CO2 levels in the ICU. Implantation of the IoT-based IAQ sensing network system may facilitate the monitoring of indoor CO2 levels.

Design and Research of Building Indoor Environment Monitoring System Relying on 3D Modeling and Image Processing

In order to improve the monitoring effect of building indoor environment, this paper carries out indoor environment simulation through 3D modeling, uses image processing technology to collect environmental monitoring data, and proposes a routing algorithm applied in this environment. Moreover, this paper introduces the energy consumption model of sensor nodes and the multi-attribute decision-making method and uses the multi-attribute decision-making to propose an adaptive energy balance routing algorithm based on the indoor environment of the building. In addition, this paper establishes a simulation analysis, compares it with several other routing algorithms, and verifies that the proposed algorithm has better balance in network energy consumption and longer network life cycle. Finally, this paper combines three-dimensional modeling and image processing technology to construct the building indoor environment monitoring system. It can be seen from the simulation experiments that the proposed building indoor environment monitoring system based on 3D modeling and image processing can meet the actual needs of intelligent building indoor monitoring.

Indoor environment monitoring system tested in a living lab

Recently, an indoor environment monitoring system using the internet of things sensor has been actively used to secure the thermal comfort of occupants, reduce energy use, and control indoor air quality. However, most commercial sensor and control applications are limited to the unilateral sharing of measurement results and simple operation control of related equipment. This study describes the development of a system for real-time and easy monitoring of the indoor environment and energy consumption. This study then describes the application of the system to the living lab. The system was built using Raspberry Pi and embedded sensors (temperature, humidity, PM1.0, PM2.5, PM10, and CO2) to collect indoor air quality-related data. The data can be safely stored for a long time, and residents can easily check and interact with the data. This study presents the problems and requirements that occurred during the development and implementation of the proposed system, data measured in the living lab and discusses the analysis results. The proposed system is expected to support continuous and efficient environment monitoring and control seasonal energy use by recognizing changes in the indoor environment according to the behavior of residents and estimating energy consumption.

Sensor Mathematical Model Data Fusion Biobjective Optimization

Sensors are an important tool to quantify the changes and an important part of the information acquisition system; the performance and accuracy of sensors are more strictly desired. In this paper, a highly sensitive fiber optic sensor for measuring temperature and refractive index is prepared by using femtosecond laser micromachining technology and fiber fusion technology. The multimode fiber is first spliced together with single-mode fiber in a positive pair, and then, the multimode fiber is perforated using a femtosecond laser. The incorporation of data model sensors has led to a rapid increase in the development and application of sensors as well. Based on the design concept and technical approach of the wireless sensor network system, a general development plan of the indoor environmental monitoring system is proposed, including the system architecture and functional definition, wireless communication protocols, and design methods of node applications. The sensor has obvious advantages over traditional electrical sensors; the sensor is resistant to electromagnetic interference, electrical insulation, corrosion resistance, low loss, small size, high accuracy, and other advantages. The upper computer program of the indoor environment monitoring system was developed in a Visual Studio development environment using C# language to implement the monitoring, display, and alarm functions of the indoor environment monitoring system network. The sensor-data model interfusion with each other for mutual integration performs the demonstration of the application.

Research on Indoor Air Monitoring System Based on STM32

Adults spend 80% of their time indoors every day, so the quality of indoor air is closely related to people's health and quality of life.In this project, an indoor environment monitoring system is designed for indoor air quality. Data interaction between the system and the indoor air monitoring system is carried out by means of wireless transmission, so as to monitor indoor PM2.5 concentration, temperature and humidity in real time through mobile phones.Realization function: For the collection of various parameters of the home environment, the collected environmental parameters will be transmitted to the main control device through the RS-485 circuit, using the RS-485 circuit to transmit data, can collect data for different positions of the indoor, aiming at faster and more accurate detection of indoor air condition.

A study on vessel applicable indoor environment monitoring system

A study on vessel applicable indoor environment monitoring system

Design of the Highly Integrated Indoor Environment Monitoring System with Dual Data Transmission Mode Based on the Interconnect of Things

To overcome the disadvantages of poor adaptability and weak systematicity of the existing indoor environment monitoring instrument, a set of indoor environment monitoring system with dual data transmission mode based on the Interconnect of Things is designed in this paper, which can monitor seven different related parameters, i.e., fusion CO2, formaldehyde, volatile organic compounds, particulate matter, temperature, humidity and noise. Besides, it designs dual mode switch between GSM wireless upload and WiFi wireless upload to enhance the environmental adaptability of the monitor. It was demonstrated that, by combining with the he Internet of Things technology, the system works well to incorporate monitoring, assessment and early warning.

Hardware Implementation of STM32 Microcontroller-Based Indoor Environment Monitoring System

Microcontroller is widely used in the intelligent life of modern society. Intelligent development based on Microcontroller to solve the actual needs of people’s life, work, study and other fields is the core of Microcontroller application. Therefore, it is a task for researchers to understand the structure and performance of microcontroller, develop software, and be familiar with the method and process of intelligent development based on microcontroller. And with that in mind, this paper designs and produces a physical hardware system for indoor environment detection based on STM32 microcontroller. The system can detect the light intensity, temperature and humidity, and CO gas concentration in the indoor environment; and the data is integrated and processed by the STM32 microcontroller to display the current parameter values of each quantity in the indoor environment on a 3.5-inch resistive screen; at the same time, the PC can also log in to the OneNET cloud platform through the web page, and display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time in the device created by OneNET for real-time viewing. The system can also display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time. The hardware system has been tested and tested to achieve its function.

Indoor environment online monitoring-based on ZigBee network

An online environmental monitoring system based on ZigBee wireless sensor network is designed to overcome the drawbacks of the traditional indoor environment monitoring system, such as the difficulty of wiring and the poor flexibility. The ZigBee communication technology, web server technology and GSM communication technology are synthesized, and the indoor temperature and humidity, carbon monoxide, formaldehyde concentration and other environmental information are collected and monitored in real time by various supporting sensors. Users can complete local and remote real-time monitoring of indoor environment by opening Web pages. When a fire or gas leak occurs, users will receive alert messages in time. Experiment show that the system has the advantages of stable operation, simple use and good flexibility, and has high practical value and wide application prospects.

Smart Home IoT System by Using RF Energy Harvesting

IoT system becomes a hot topic nowadays for smart home. IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circularly polarized array rectenna system to harvest enough power from any direction to increase lifetime of the batteries used in the IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node, and a low-power microcontroller are used to operate in lower power modes. The proposed system has an 84.6-day lifetime which is approximately 10 times the lifetime for a similar system. On the other hand, the proposed power management circuit is operated at 0.3 V DC to boost the voltage to ~3.7 V from radio frequency energy harvesting and manage battery level to increase the battery lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a nonstatic plan, approve energy consumption, and avoid failure of sensor nodes in a smart home.

Design of Indoor Environment Monitoring System Based on Internet of Things

In view of the current emphasis on people’s indoor environment, an indoor environment monitoring system based on the Internet of Things and sensor technology was designed and developed. The real-time system by a plurality of sensor nodes collect indoor environment parameters, data transmitted to the mobile terminal after the fusion. Users can view indoor environment real-time data and historical data through remote terminals. Experiments show that the system can realize real-time monitoring of the indoor environment. The system of high reliability, low cost, low power, easy to operate.

EMI-Free Bidirectional Real-Time Indoor Environment Monitoring System

Indoor air quality, temperature, and relative humidity affect the thermal comfort and health of the inhabitants. Therefore, monitoring these parameters is essential to prevent indoor air pollution and to improve labor productivity. Most recently, the research conducted has used radio frequency wireless communications to monitor the indoor environment. However, long-term exposure to electromagnetic interference (EMI) causes a detrimental impact on the human body, especially on the elderly, patients, and infants, while it concurrently affects the operation of electronic devices. Thus, we propose a unique indoor environment monitoring system using an EMI-free bidirectional visible light communication technology. The sensing data from the smart sensor tag and the command data used to request the environmental sensing data are transferred bidirectionally between the base station and the smart sensor tag by being modulated into the light-emitting diode (LED) light beam. The proposed smart sensor tags are designed to measure five important parameters of indoor environments, such as CO2 concentration, volatile organic compound level, O2 concentration, temperature, and relative humidity, at multiple positions in real time. In addition, a proposed average-voltage tracking algorithm is adopted to allow the LED illumination to be used as a lighting system and as a long-range wireless communication system. As a result, the proposed system is demonstrated to be error-free when the distance between the base station and the smart sensor tags is 6 m. The measured live data are aggregated and visualized in a cloud platform by a graphical user interface. A web-based application and a mobile application are also developed to display the real-time data.

Indoor Environment Remote Monitoring System Based on NB-IOT

Aiming at the importance attached to the indoor environment, design and development of the indoor environment monitoring system based on NB-IOT and sensor technology. The real-time system by a plurality of sensor nodes collect indoor environment parameters, ZigBee embedded transmitted over the network to the gateway, and then use the NB-IoT uploaded to the service center stores the data; APP monitoring indoor environment using a mobile phone. Users can view the indoor environment in real time and historical data track through remote terminals. Experiments show that the system can achieve real-time monitoring of the indoor environment. The system is stable, low-cost, low-power, easy to operate to meet the design requirements.

Detection of occupant actions in buildings through change point analysis of in-situ measurements

The number of research studies on occupant behaviour is increasing, following four main vectors: needs of the occupants, actions, drivers and building systems. In the specific studies which preceded this one, a large amount of indoor environment data, mainly temperature, relative humidity and carbon dioxide concentration, was collected. Moreover, the installation of specific sensors to detect occupant behaviour was surmised to not always constitute the best option, due to the complexity of its installation and maintenance, as well as its impacts on occupants. This study presents itself as a contribution to the study of residential occupant behaviour. The statistical tool of Change Point Analysis (CPA) was applied in a methodology devised to detect occupant actions in residential buildings, using data from an indoor environment monitoring system including temperature, relative humidity and carbon dioxide. The principle of this methodology is based on the fact that occupant actions produce abrupt shifts on the cited parameters. Change point analysis detects the number of abrupt changes in a time series and its precise moments, which are then correlated with occupant actions.In this work, the occupants of a dwelling in Porto, Portugal were studied. In-situ measurements were taken, as well as surveys for the assessment of the main occupant actions.The application of the proposed methodology using CPA was successful. Comparing the results of action detection with the daily journals of the occupants or specific sensors used for the same purpose, an accuracy of 97% in detecting window opening, 97% in showering, 100% in heating and 85% in cooking was obtained.

Survey on Design and Implementation of Indoor Environment Monitoring and control system

The ideology of the Internet of things has emerged due to the consolidation of multiple technologies. IoT devices are a part of the larger concept of home automation, also known as domotics. The application of Internet of Things in indoor environment monitoring and control has become a major area as people paying more attention to quality of environment. Intelligent solutions are proposed by studying key technologies of IoT. The system provides a new application for IoT.

Implementation of an Intelligent Indoor Environmental Monitoring and management system in cloud

Indoor environmental monitoring and management system has played an essential role in public health sustainability. By monitoring the indoor air quality in public areas such as schools, offices, home or other buildings, the authorities will be given a better picture of the indoor air quality to take the right steps to ensure the better air quality for people inside the buildings. This system also can give information about indoor air quality information for the society. Therefore, to achieve this goal, we need to develop a monitoring system by using Information Technology based on Big Data and Cloud Computing environment to give warning. In this paper, we propose Intelligent Indoor Environment Monitoring System (iDEMS) combined with ZigBee wireless sensor network technology to store and process environmental data in HBase. The mechanism of the proposed system is classified into three stages: data collection, data processing, and information monitoring. To understand an Intelligent Indoor Environmental Monitoring, first, we collected the gas from Intelligent Indoor Environmental Monitoring through the environmental sensors with ZigBee wireless sensor network technology. We build a platform for iDEMS to collect the data related to the indoor gases. Second, the environmental data collected in the first stage will be stored and processed in HBase which support massive data storage and free to increase storage capacity for the analysis and processing of Big Data. In this stage, we also compared several data-input methods to import data in HBase much more efficient. Third, the intelligent-control socket is integrated into iDEMS and give the warning if the air quality exceeds the absolute legal limit based on the air quality index rule from the authority. Finally, iDEMS presents the resulting information by a web-based Monitoring Platform so that users can use the Internet to monitor the environment and enable them to utilize these informed decisions on managing and improving the environments.

An indoor environment monitoring system using low-cost sensor network

Energy consumption in buildings account for a significant proportion of total energy consumed worldwide. Since humans spend about 90% of their time in buildings, it is essential that the indoor environment quality is improved and energy consumption is minimised. This paper presents the development and implementation of a low-cost sensor network system that can be used to monitor important indoor parameters to achieve high indoor environment quality. The prototype system shown in this paper has been tested in an office building and improvements made. The system, with further improvements can be used to control HVACs, and indoor environment conditions automatically and has great potentials for energy saving.

Novel Electromagnetic-Interference-Free Indoor Environment Monitoring System by Mobile Camera-Image-Sensor-Based VLC

Long-term exposure to radio frequency waves can have adverse effects on human health. It may cause bad effects especially to elderly people, children, and patients with weak immune systems. On the other hand, visible light communication technologies that use a light-emitting diode (LED) light source and a photodetector to transmit and receive data through visible light have a severe demerit that the modulation and demodulation processes in the system can be complicated. This paper presents a low-cost wireless mobile indoor environment monitoring system with no additional complicated signal detecting device, except a mobile device and sensor modules. Temperature, humidity, and CO $_2$ concentration equivalent data are collected by sensor modules, and these data are modulated using frequency shift keying modulation. The modulated data are transmitted wirelessly by using a red–green–blue LED for transmitting multiple data concurrently. An Android application is developed to act as a light-signal receiver from multiple sensor modules. The image stream of the LED is captured and is processed locally in a mobile device. A single-receiver module with a camera image sensor can accept sensing data from six sensor modules simultaneously with a maximum transmission range up to 12 m and low error rate.

Implementation of Air-conditioning Control Technology Based on Wireless Sensor

Using wireless sensor networks to collect indoor temperature and humidity data, a monitoring system is built.According to the data of the central processing unit, the state of the current room is analyzed, and the cooling capacity (heat) and air volume of the central air conditioner are calculated. Meanwhile, this system calculates the relevant fees based on the amount of cold (heat) consumed by each user, and provides a more accurate data base for the central air conditioning system for energy efficiency optimization. Theresults show that this system can accurately reflect the environmental status of the target room.Therefore, it is concluded that the indoor environment monitoring system based on wireless sensor network and embedded technology proposed in this paper is effective and feasible.