Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework

Sensors on Internet of Things Systems for the Sustainable Development of Smart Cities: A Systematic Literature Review

The Internet of Things (IoT) is a critical component of smart cities and a key contributor to the achievement of the United Nations Sustainable Development Goal (UNSDG) 11: Sustainable Cities and Communities. The IoT is an infrastructure that enables devices to communicate with each other over the Internet, providing critical components for smart cities, such as data collection, generation, processing, analysis, and application handling. IoT-based applications can promote sustainable urban development. Many studies demonstrate how the IoT can improve smart cities' sustainable development. This systematic literature review provides valuable insights into the utilization of the IoT in the context of smart cities, with a particular focus on its implications for sustainable urban development. Based on an analysis of 73 publications, we discuss the role of IoT in the sustainable development of smart cities, focusing on smart communities, smart transportation, disaster management, privacy and security, and emerging applications. In each domain, we have detailed the attributes of IoT sensors. In addition, we have examined various communication technologies and protocols suitable for transmitting sensor-generated data. We have also presented the methods for analyzing and integrating these data within the IoT application layer. Finally, we identify research gaps in the literature, highlighting areas that require further investigation.

Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic Review

In the last years, the issue of exposure assessment of airborne pollutants has been on the rise, both in the environmental and occupational fields. Increasingly severe national and international air quality standards, indoor air guidance values, and exposure limit values have been developed to protect the health of the general population and workers; this issue required a significant and continuous improvement in monitoring technologies to allow the execution of proper exposure assessment studies. One of the most interesting aspects in this field is the development of the "next-generation" of airborne pollutants monitors and sensors (NGMS). The principal aim of this review is to analyze and characterize the state of the art and of NGMS and their practical applications in exposure assessment studies. A systematic review of the literature was performed analyzing outcomes from three different databases (Scopus, PubMed, Isi Web of Knowledge); a total of 67 scientific papers were analyzed. The reviewing process was conducting systematically with the aim to extrapolate information about the specifications, technologies, and applicability of NGMSs in both environmental and occupational exposure assessment. The principal results of this review show that the use of NGMSs is becoming increasingly common in the scientific community for both environmental and occupational exposure assessment. The available studies outlined that NGMSs cannot be used as reference instrumentation in air monitoring for regulatory purposes, but at the same time, they can be easily adapted to more specific applications, improving exposure assessment studies in terms of spatiotemporal resolution, wearability, and adaptability to different types of projects and applications. Nevertheless, improvements needed to further enhance NGMSs performances and allow their wider use in the field of exposure assessment are also discussed.

Factorial Design Analysis for Localization Algorithms

Localization is a fundamental problem in Wireless Sensor Networks, as it provides useful information regarding the detection of an event. There are different localization algorithms applied in single-hop or multi-hop networks; in both cases their performance depends on several factors involved in the evaluation scenario such as node density, the number of reference nodes and the log-normal shadowing propagation model, determined by the path-loss exponent (η) and the noise level (σdB) which impact on the accuracy and precision performance metrics of localization techniques. In this paper, we present a statistical analysis based on the 2k factorial methodology to determine the key factors affecting the performance metrics of localization techniques in a single-hop network to concentrate on such parameters, thus reducing the amount of simulation time required. For this proposal, MATLAB simulations are carried out in different scenarios, i.e., extreme values are used for each of the factors of interest and the impact of the interaction among them in the performance metrics is observed. The simulation results show that the path-loss exponent (η) and noise level (σdB) factors have the greatest impact on the accuracy and precision metrics evaluated in this study. Based on this statistical analysis, we recommend estimating the propagation model as close to reality as possible to consider it in the design of new localization techniques and thus improve their accuracy and precision metrics.

Towards an integrated framework for air quality monitoring and exposure estimation-a review

For the health and safety of the public, it is essential to measure spatiotemporal distribution of air pollution in a region and thus monitor air quality in a fine-grain manner. While most of the sensing-based commercial applications available until today have been using fixed environmental sensors, the use of personal devices such as smartphones, smartwatches, and other wearable devices has not been explored in depth. These kinds of devices have an advantage of being with the user continuously, thus providing an ability to generate accurate and well-distributed spatiotemporal air pollution data. In this paper, we review the studies (especially in the last decade) done by various researchers using different kinds of environmental sensors highlighting related techniques and issues. We also present important studies of measuring impact and emission of air pollution on human beings and also discuss models using which air pollution inhalation can be associated to humans by quantifying personal exposure with the use of human activity detection. The overarching aim of this review is to provide novel and key ideas that have the potential to drive pervasive and individual centric and yet accurate pollution monitoring techniques which can scale up to the future needs.

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve.

Influence of air pollution on exhaled carbon monoxide levels in smokers and non-smokers. A prospective cross-sectional study

BACKGROUND

The poor air quality and cigarette smoking are the most important reasons for increased carbon monoxide (CO) level in exhaled air. However, the influence of high air pollution concentration in big cities on the exhaled CO level has not been well studied yet.

OBJECTIVES

To evaluate the impact of smoking habit and air pollution in the place of living on the level of CO in exhaled air.

METHODS

Citizens from two large cities and one small town in Poland were asked to complete a survey disclosing their place of residence, education level, work status and smoking habits. Subsequently, the CO level in their exhaled air was measured. Air quality data, obtained from the Regional Inspectorates of Environmental Protection, revealed the differences in atmospheric CO concentration between locations.

RESULTS

1226 subjects were divided into 4 groups based on their declared smoking status and place of living. The average CO level in exhaled air was significantly higher in smokers than in non-smokers (p<0.0001) as well as in non-smokers from big cities than non-smokers from small ones (p<0.0001). Created model showed that non-smokers from big cities have odds ratio of 125.3 for exceeding CO cutoff level of 4ppm compared to non-smokers from small towns.

CONCLUSIONS

The average CO level in exhaled air is significantly higher in smokers than non-smokers. Among non-smokers, the average exhaled CO level is significantly higher in big city than small town citizens. These results suggest that permanent exposure to an increased concentration of air pollution and cigarette smoking affect the level of exhaled CO.

A Fault Tolerance Mechanism for On-Road Sensor Networks

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N - x principle and the sensors' failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%.

Environmental Monitoring Based on the Wireless Sensor Networking Technology

This paper investigates real-life environmental monitoring applications based on Wireless Sensor Networks (WSNs). Wireless sensor networking is an emerging technology, which through the research in the labs and the real deployments has proved to be a significant and valuable tool for scientists in their effort to explore various environmental phenomena. During the last decades, this wireless networking technology has been adopted by many scientific fields in order to accurately and effectively monitor climate phenomena such as air pollution, destruction phenomena (i.e., landslides), etc. It has also been widely used in agriculture as well as in horticulture for field monitoring. This paper provides a critical overview of the basic components existing WSN deployments use. It also categorizes these deployments, 111 in total, into five different field categories, namely agricultural monitoring, environmental monitoring, air-water pollution monitoring, monitoring of destruction phenomena, as well as monitoring of livestock, and wild animal, in order to provide a general view of the technologies used, the conditions under which the deployments were conducted, and much more. Then, five easy-to-use guides are provided discussing basic considerations for deploying WSNs in each of these fields. These guides cover various issues, such as sensor node platforms, operating systems (OSs), topologies, installation and maintenance issues, and much more. In order to showcase the usefulness of consulting the resulted guides, this work considers representative application scenarios for each of these field deployments.