Quality of service approaches in IoT: A systematic mapping

Real-time air pollution monitoring with sensors on city bus

As air pollution is becoming the largest environmental health risk, the monitoring of air quality has drawn much attention in both theoretical studies and practical implementations. In this article, we present a real-time, fine-grained, and power-efficient air quality monitor system based on aerial and ground sensing. The architecture of this system consists of the sensing layer to collect data, the transmission layer to enable bidirectional communications, the processing layer to analyze and process the data, and the presentation layer to provide a graphic interface for users. Three major techniques are investigated in our implementation for data processing, deployment strategy, and power control. For data processing, spatial fitting and short-term prediction are performed to eliminate the influences of incomplete measurement and the latency of data uploading. The deployment strategies of ground sensing and aerial sensing are investigated to improve the quality of the collected data. Power control is further considered to balance between power consumption and data accuracy. Our implementation has been deployed in Peking University and Xidian University since February 2018, and has collected almost 100,000 effective values thus far.

UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, which generate a large number of samples, creating a big data challenge. This IoT paradigm has gained traction in recent years, yielding extensive research from an increasing variety of perspectives, including scientific reviews. These reviews cover surveys related to IoT vision, enabling technologies, applications, key features, co-word and cluster analysis, and future directions. Nevertheless, we lack an IoT scientometrics review that uses scientific databases to perform a quantitative analysis. This paper develops a scientometric review about IoT over a data set of 19,035 documents published over a period of 15 years (2002–2016) in two main scientific databases (Clarivate Web of Science and Scopus). A Python script called ScientoPy was developed to perform quantitative analysis of this data set. This provides insight into research trends by investigating a lead author’s country affiliation, most published authors, top research applications, communication protocols, software processing, hardware, operating systems, and trending topics. Furthermore, we evaluate the top trending IoT topics and the popular hardware and software platforms that are used to research these trends.

https://www.mdpi.com/2073-8994/9/12/301/pdf

Internet of Things: A Scientometric Review

Wireless Sensor Networks (WSN) consists of sensors used for sensing environmental conditions and many more applications in real world. Air pollution is a threat to the life of humans. To control the air pollution it is necessary to monitor the pollutant gases in periodically. Various air pollution monitoring systems using sensor network have been developed, deployed and tested in the literature. This paper presents a comparative study about the literature for air pollution monitoring systems based on the classification such as stationary air pollution monitoring systems, dynamic air pollution monitoring systems and pollution data analysis techniques. These pollution monitoring systems are compared based on the methodologies followed, microcontroller used, communication device used, pollutants analyzed using sensors, evaluation attributes, tested location and performance of the system. This paper also discusses the merits and demerits of the air pollution monitoring systems.

A Comprehensive Review of Wireless Sensor Networks Based Air Pollution Monitoring Systems

We have developed a low-cost wireless monitoring system, that enables air quality referential parameters measurements based on a multilayer distributed model with an Arduino platform. This is an Internet of Things application, of which a physical object is embedded with electronics, software, sensors and wireless connectivity to allow monitoring air pollution on real-time. Agile methodologies such as Scrum and Extreme Programming were used in order to ensure software quality. The electronic device is equipped with three sensors, which determines carbon monoxide (CO) as well as carbon dioxide (CO2) concentrations and powder density, using an API developed in C++ language. The validation of the mentioned concept has been realized in a variety of sites in Ecuador, namely in the cities of Quito, Amaguana and Tena. The obtained results of air pollutants concentration are compared and conformable with the referential values established by international environment organizations like World Health Organization (WHO) and US EPA.

Diego Carrera

Papers

Distributed System as Internet of Things for a new low-cost, Air Pollution Wireless Monitoring on Real Time