Characterization of a Multi-User Indoor Positioning System Based on Low Cost Depth Vision (Kinect) for Monitoring Human Activity in a Smart Home

An increasing number of systems use indoor positioning for many scenarios such as asset tracking, health care, games, manufacturing, logistics, shopping, and security. Many technologies are available and the use of depth cameras is becoming more and more attractive as this kind of device becomes affordable and easy to handle. This paper contributes to the effort of creating an indoor positioning system based on low cost depth cameras (Kinect). A method is proposed to optimize the calibration of the depth cameras, to describe the multi-camera data fusion and to specify a global positioning projection to maintain the compatibility with outdoor positioning systems. The monitoring of the people trajectories at home is intended for the early detection of a shift in daily activities which highlights disabilities and loss of autonomy. This system is meant to improve homecare health management at home for a better end of life at a sustainable cost for the community

Performance Evaluation on Applied Low-Cost Multi-Sensor Technology in Air Pollution Monitoring

This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals.  In this study, we investigated the performance of a custom-built prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area.  The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution. &nbsp

Air Pollution Exposure Monitoring using Portable Low-cost Air Quality Sensors

Urban environments with a high degree of industrialization are infested with hazardous chemicals and airborne pollutants. These pollutants can have devastating effects on human health, causing both acute and chronic diseases such as respiratory infections, lung cancer, and heart disease. Air pollution monitoring is vital not only to citizens, warning them on the health risks of air pollutants, but also to policy-makers,assisting them on drafting regulations and laws that aim at minimizing those health risks. Currently,air pollution monitoring predominantly relies on expensive high-end static sensor stations. These stations produce only aggregated information about air pollutants, and are unable to capture variations in individual’s air pollution exposure. As an alternative, this article develops a citizen-based air pollution monitoring system that captures individual exposure levels to air pollutants during daily indoor and outdoor activities. We present a low-cost portable sensor and carry out a measurement campaign using the sensors to demonstrate the validity and benefits of citizen-based pollution measurements. Specifically, we (i) successfully classify the data into indoor and outdoor, and (ii) validate the consistency and accuracy of our outdoor-classified data to the measurements of a high-end reference monitoring station. Our experimental results further prove the effectiveness of our campaign by (i) providing fine-grained air pollution insights over a wide geographical area, (ii) identifying probable causes of air pollution dependent on the area, and (iii) providing citizens with personalized insights about air pollutants in their daily commute.Peer reviewe

Application of low-cost sensors for accurate ambient temperature monitoring

In structures with reduced monitoring budgets, the high cost of commercial metering devices is always an obstacle for monitoring structural health. This might be an issue when temperatures must be measured for both structural and environmental reasons. To fill this gap, in this paper, a novel monitoring system is proposed for the accurate measurement of indoor temperature in buildings. This protocol is characterized by its generality, as it can be easily adapted to measure any structural or environmental parameters on site. The proposed monitoring system uses from one to eight low-cost sensors to obtain multiple measurements of the ambient temperatures. The accuracy ranges of the developed monitoring systems with different numbers of sensors are statistically analysed. The results indicate that the discrepancy of the measurements decreases with the increase in the number of sensors, as the maximum standard deviation of 10 sensors (0.42) decreases to 0.32 and 0.27 for clusters of 20 and 30 sensors, respectively.This research was funded by the Spanish Ministry of Economy and Competitiveness (grant number BIA2013-47290-R, BIA2017-86811-C2-1-R, and BIA2017-86811-C2-2-R) and by the Universidad de Castilla La Mancha (grant number 2018-COB-9092).Peer ReviewedPostprint (published version

Device-Free Localization for Human Activity Monitoring

Over the past few decades, human activity monitoring has grabbed considerable research attentions due to greater demand for human-centric applications in healthcare and assisted living. For instance, human activity monitoring can be adopted in smart building system to improve the building management as well as the quality of life, especially for the elderly people who are facing health deterioration due to aging factor, without neglecting the important aspects such as safety and energy consumption. The existing human monitoring technology requires additional sensors, such as GPS, PIR sensors, video camera, etc., which incur cost and have several drawbacks. There exist various solutions of using other technologies for human activity monitoring in a smartly controlled environment, either device-assisted or device-free. A radio frequency (RF)-based device-free indoor localization, known as device-free localization (DFL), has attracted a lot of research effort in recent years due its simplicity, low cost, and compatibility with the existing hardware equipped with RF interface. This chapter introduces the potential of RF signals, commonly adopted for wireless communications, as sensing tools for DFL system in human activity monitoring. DFL is based on the concept of radio irregularity where human existence in wireless communication field may interfere and change the wireless characteristics

RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Characterization of a multi-user indoor positioning system based on low cost depth vision (Kinect) for monitoring human activity in a smart home

International audienceAn increasing number of systems use indoor positioning for many scenarios such as asset tracking, health care, games, manufacturing, logistics, shopping, and security. Many technologies are available and the use of depth cameras is becoming more and more attractive as this kind of device becomes affordable and easy to handle. This paper contributes to the effort of creating an indoor positioning system based on low cost depth cameras (Kinect). A method is proposed to optimize the calibration of the depth cameras, to describe the multi-camera data fusion and to specify a global positioning projection to maintain the compatibility with outdoor positioning systems. The monitoring of the people trajectories at home is intended for the early detection of a shift in daily activities which highlights disabilities and loss of autonomy. This system is meant to improve homecare health management at home for a better end of life at a sustainable cost for the community

Wireless Internet Of Things-Based Air Quality Device For Smart Pollution Monitoring

Living in a healthy environment is a need for every human being whether indoor or outdoor. However, pollutions occur everywhere and most people are merely mindful of the importance of having clean outdoor air to breathe and are not concerned about the indoor air quality. Indoor air quality refers to the quality within the building, and relates to the health and comfort of the building occupants. Dangerous particles exist in the outside air, pollute the indoor environment and produce harmful conditions as the polluted air travels into the house or building through windows or doors. Therefore, a wireless Internet of Things-based air quality device is developed to monitor the air quality in the indoor environment. The proposed system integrates a low-cost air quality sensor, temperature and humidity sensors, a single-board computer (Raspberry Pi 2 microprocessor) and cloud storage. The system provides real-time air quality reading, transfers the data through a wireless network to the Internet and displays the data in dedicated webpage. Furthermore, it stores records in cloud storage and sends e-mail notification message to the user when unhealthy condition is met. The study has a significant impact on promoting affordable and portable smart pollution monitoring system as the development of the device utilizing low-cost and off-the-shelf components