This is an Internet of Things application, of which a physical object is embedded with electronics, software, sensors and wireless connectivity to allow monitoring ...
2015 IEEE/ACM 19th International Symposium on Distributed Simulation and Real Time Applications
Distributed System as Internet of Things for a new low-cost, Air Pollution Wireless Monitoring on Real Time Walter Fuertes, Diego Carrera, César Villacís, Theofilos Toulkeridis, Fernando Galárraga, Edgar Torres, and Hernán Aules Computer Sciences Department, Universidad de las Fuerzas Armadas- ESPE, Sangolquí, Ecuador E-mail: {wmfuertes, dmcarrera, cjvillacis, ttoulkeridis, jfgalarraga, eptorres3, hmaules}@espe.edu.ec technologies. In [7] demonstrate a real time air quality monitoring system, through a Web application and mobile devices. In [8] developed a WSN as technology for real time data collection. Tzai-Hung Wen et al., [9] created a WSN composed of different types of nodes, including 44 sensors for air quality. In [10] studied an optimized method to use fewer sensors, in order to monitor a specific study area. However, an integral solution has not been yet achieved, due to the fact that solutions have been based on prototype construction, without establishing an adequate Software Engineering process, which produce high quality software. This project aims to present the development of a comprehensive low-cost technological solution capable of measuring CO, CO2 and the density of dust (i.e., particles in the air per cubic meter), wirelessly transferring the collected information in real-time, storing it in a relational database and displaying this information in a Web application. This involves the construction of hardware and software, which are able to interact with each other. Therefore, the main contribution of this study is to develop a complete system of hardware, software, and firmware to monitor air quality distributed, wireless and on real time. The principle goal of such objective is to establish a low-cost solution that enables to determine the concentrations of a variety of greenhouse gases and air pollution, allowing a direct observation and evaluation in real time of fundamental processes such as global warming and climate change. From the Software Engineering point of view the contribution of this project is having integrated two agile methods of software development such as Scrum and Extreme Programming, used for modeling infrastructure deployment, and the development of a software component that allows the transfer of data in real time, between (Arduino) hardware and software (Java EE) by means of an API written in language C/C++. The outcome of this project bases in the construction of a prototype that contemplates a device IoT, a package of software tools for analysis of the information in real time using wireless sensor networks (WSN) having a low energy consumption. There are obviously commercial applications of this type available with proposed ARM mbed IoT Starter Kit - Ethernet editions, but all those imply a significant increase of costs. The mentioned system has been applied in the cities of Quito, Amaguaña and two karst caves in the city of Tena, Ecuador, where in real environmental conditions (underground, fluctuation of air almost closed, moist, with
Abstract— 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, Amaguaña 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. Keywords- distributed systems, real time, IoT; Arduino; air pollution; agile methodologies; electronic sensors
I.
INTRODUCTION
Air pollution and lack of air quality monitoring points represent environmental and technological challenges for cities and environments around the world [1][2]. To face this issue, industry has focused its efforts in finding a versatile technological alternative that allows the improvement of the air quality measuring process and provides reference values in network sites where conventional monitoring fails to cover appropriately. Unfortunately, existing products and the generated results do not represent low-cost solutions. To measure the concentration of air pollutants, wireless monitoring systems are being implemented using sensors on an electronic board, developing software embedded in hardware. For instance, Prasad et al., [3], joined sensors carbon monoxide (CO), carbon dioxide (CO2), oxygen (O2) and nitrogen dioxide (NO2) in a Waspmote card. Raju et al., [4], used an Arduino board to control the ZBee expansion module and sensor MQ-7 CO. In [5] a solution is presented attached on a mobile unit, which can measure levels of CO of the environment in real time, whose node consists of a wire-less sensor that is associated with a smart phone, which is acting as an interface. In [6], air pollution is being monitored, in order to control industrial activities. In [1], real time measurements of gas concentrations, such as CO2, NO2, CO and O2 are being considered, using calibration
1550-6525/15 $31.00 © 2015 IEEE DOI 10.1109/DS-RT.2015.28
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Figure 1.
An overview of the conceptual framework of this research
multiple particles, cracks with gas, etc.) the prototype was confirmed to perform simultaneous measurement of air particles per cubic meters and CO2 ppb/ppm, on-site. The results were transmitted in real time, where air particles data were evaluated, and valid CO2 values for such an environment (establishment of values in the tangential platform) were established. The generated data (applying this method to the measurement of air quality) can also be applied worldwide for scientific purposes such as security in speleological expeditions and other multiple scientific branches. During development of our project, Arduino was used as an open hardware platform in conjunction with Java libraries using MySQL database as back-end. All mentioned tools allow cost reduction of the application development significantly, resulting to overall costs of approximately $200 USD for hardware and firmware concept. There are no costs for using the Web application, nonetheless for future works focus on big data analysis it is necessary to calculate the cost of the storage and analysis of the information provided by the sensors in real time, allowing appropriate decisions, as well as the opportune diffusion of such information. The main obstacle in the development of the WAMPS has been the achievement of the interoperability among the hardware (Arduino) and the software (Web application), since the sensors capture the information in analogical format. Subsequently, it has been necessary to program an API bridge in C/C++ to arm the frame of data in format JSON enabling the transmission to the Web application using the protocol http (Figure 1). The remainder of the article has been organized in the following manner: the theoretical framework that founded this research is described in Section 2. Section 3 explains the experiment configuration. Section 4 presents the analysis applied to the measurements of the reference values on the concentration of pollutants in the listed cities, while Section 5 presents related work. Section 6 ends with the conclusions.
II.
THEORETICAL FRAMEWORK
This research has been leveraged in a conceptual framework represented in Figure 1. As it is demonstrated, we have used a combination of tools, methods and techniques to ensemble the nature of the project. All these were based on the process for the development of an “n” layers computer system that articulates itself with the Arduino, whose slight detail is described below: A. Atmospheric Pollution and Environmental Control Air pollution and lack of monitoring points for air quality is one of the major environmental and technological challenges of the big cities of the world. In the case of Ecuador, only in the cities Quito, Guayaquil and Cuenca, air quality is monitored. Other cities are in the process of developing measurement programs. According to [11], the eight main primary pollutants generated by human activities are: nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO2), Methane (CH4, VOCs); particles (PM), free radicals persistence, Chlorofluorocarbons (CFCs), odors from decomposing garbage, industrial waste and also radioactive contaminants. According to studies by [2][12][13], high levels of the greenhouse gases CO2 and methane pollution are the main reason for the increase of the average global temperature. Additionally, to the high fluidity of transport and energy used to heat, cool and provide power to buildings in cities as coal consumption. Other studies presented by the World Health Organization (WHO) [14][15], it has been considered, that the highest level of particulate matter shall be 2.5 (PM2.5), which is the pollutant that most affects the health of people, causing serious respiratory and heart diseases. This study determined air pollution levels considering CO, CO2 and dust particles (PM) of the environment in real time, using an interface of hardware, software and firmware.
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B. Wireless Sensor Network Air Pollution Monitoring System In recent years, within the academic environment the term known as Wireless Sensor Networks has emerged. This term first appeared in military applications and aimed to detect moving objects within the battlefield [16]. Today, WSNs are used in various fields such as industrial control, precision agriculture, analysis of vital parameters in medicine, generation of ecosystem models, applications, prediction and monitoring in the environment, water pollution, besides many others [17][18]. Researchers at the University of Mauritius in 2010 [6], proposed a system of technological innovation called the "Wireless Sensor Network Air Pollution Monitoring System (WAPMS)", resulting to be an area of current active research due to the potential applications in the environment and the Earth Sciences. Our project has been designed as a WAPMS, because it also focuses on monitoring and network control air pollution, based on wireless sensors in real time with one or more nodes. We have integrated several sensors on one node was used, such as: the MG-811 for measuring CO2, the MQ-7 for measuring CO and sensor sensitivity of powder to measure PM environment.
Burn-Down Chart establishes the evolution of the work during a Sprint. On the other hand, the methodology XP defines the way in which the development team works and for that which the practices are specified. Also, the unified standard has been used for modeling (Unified Modelling Language, UML 2.0). For instance, the use case diagram has been elaborated to describe the behavior, while the class diagram represents the architecture, and finally the sequences diagram explains the interaction of the computer system. As a final point, we are convinced and therefore confirm that for this type of product, agile methodologies have been adequately chosen, instead of the Object Oriented Hypermedia Design Method, which has been used in a previous study [26]. D. Arduino Platform Arduino is an open platform for physical computing, which consists of a microcontroller mounted on a circuit board. This platform can be used to develop interactive objects capable of collecting data through sensors and control lights, motors or other physical elements [27]. The Arduino platform consists of two main elements: (1) The Electronic Arduino which has been assigned to be the hardware, where interactive objects have been constructed; (2) The software or Integrated Development Environment (IDE Arduino) used to program the microcontroller, which has been mounted on the electronic board. In this research the Arduino platform has been used for building the hardware interface that interacts with the Web system. This interaction takes place through sensors and a piece of software (bridge), which has been developed, using an Application Programming Interface (API) implemented in C/C++. This has lead for communication and data transfer with JavaScript Object Notation (JSON), including hardware, software and firmware application.
C. Tools and Development Process For the computer system implementation, Java Enterprise Edition (JEE) platform programming has been used, which aims to simplify enterprise applications development, being usually highly complex [19]. The JEE platform has been leveraged with four development tools: (1) Eclipse, which is an open source IDE (Integrated Development Environment) for developing applications in Java [20]; (2) MySQL Workbench, which is a visual design tool for MySQL, and the open source relational database management engine [21]; (3) StarUML tool case, which has been used for the system modeling; and (4) WildFly, allowing the raise of all RESTful Web services from the computer system. Similarly, the development process has been based on the interactive and incremental lifecycle, obtaining a multi-tier architecture: layer of customer JSF, Web, business, and data [22]. Continuing with the conceptual framework presented in Figure 1, two agile methodologies were integrated, being Scrum and Extreme Programming (XP) [23]. Scrum is a method used in projects that help effectively work as a team, with relatively short lead times [24]. XP, on the other hand, is a method used for software development with requirements changing or vaguely defined and where there is a high technical risk [24] [25]. In this research study, two agile methodologies were applied; Scrum has been used to establish the group of tasks between the base line of analysis and the base line of the product. As an appropriate complement, the methodology XP has been applied for the code and tests of the incremental products developed for each iteration (sprint), including hereby the whole project life cycle. As the development team carries out the control and pursuit of the work that we were planning, Scrum defines a series of devices. Each task will be prioritized and properly valued in relation to the time that will be needed to complete it. Therefore, the known diagram indicated by the
E. Programming Environment, Expansion Modules and Sensors for a network node The Integrated Development Environment (IDE) is a multiplatform program that allows composing pieces of code, also known as "sketches". These sketches will be executed by the microcontroller. The code written in this development environment is translated into C programming language before being compiled and transmitted to the Arduino for their execution [27]. The body of a piece of software or sketch, consists of two functions called setup() and loop(). The setup() function contains the code that will run only once. The loop() function is the core of the program, that will run repeatedly while the board is connected to the power supply. Expansion modules or Shields are electronic circuits that connect to the Arduino to extend functionality. These circuits are designed to provide additional capabilities to the original Arduino as data communication and Internet access via Ethernet networks and even wireless networks [27][28]. The expansion module Xbee Shield cards allows to the Arduino cards the installation of specific electronic components that facilitate wireless communication over distances of 100 feet indoors and 300 feet outdoors. This type of modules uses the
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ZigBee standard, which communicates with the microprocessor of the Arduino board through a serial connection [27][28]. This is a Wi-Fi Module built by Rovin Network that implements the IEEE 802.11 b/g for communicating with wireless networks. It is specially designed to simplify integration and reduce development time. Banzi [27] defines sensors as electronic elements capable of interacting with the environment around them. As eyes turn light into a signal that the brain transforms into images, sensors convert physical events into electrical signals that can be interpreted by the microcontroller Arduino. The dust density sensor uses an infrared diode with a phototransistor to detect the reflected light caused by the dust in the environment. This sensor is particularly effective for detecting fine particles and is commonly used in air purification systems [29]. The MG-811 sensor is highly sensitive to the concentration of carbon dioxide (CO2). The output voltage of the sensor falls when CO2 concentration increases [30]. The MQ-7 sensor detects the concentration of carbon monoxide in the air in the range of 20-2000 ppm. It has a high sensitivity and short response time, while the output of this sensor is analog.
sensors are connected to the analog inputs A0, A1 and A3 of the Arduino UNO R3 board. The expansion module comprises a socket Xbee on which the Wi-Fi module is mounted. The Xbee Shield is installed on the Arduino board as demonstrated in the illustration.
Figure 2.
Scheme of the electronic device.
F. Internet of Things The Internet of things, also known as "Internet of Objects" is changing everything, including our behavior, due to the impact that the Internet has had on education, communication, business, science, government and even humanity [28]. According to [31][32], it can build applications for the Internet of Things using the Arduino platform to automate homes, buildings and monitor remotely. This information system is an application of the Internet of Things because it uses Arduino to monitor air pollution in real time and using a wireless network to process data in a distributed information system. III.
EXPERIMENTAL SETUP
This section explains the electronic device, the functional software requirements, the software architecture, the design data model, the design pattern, the Web service design, the implementation and testing as well as the end-product of our research.
Figure 3.
Sequence diagram of steps executed by the electronic device.
Each sensor delivers a voltage value that must be interpreted and then it will be transmitted to the Web application. The sequence of the 18 steps required to perform this action are: 1) Starting the application, 2) default configuration values and initialization constant, 3) start of the serial connection between the Arduino board and module Wi-Fi connection, 4) response of connection status with the XBee module 5) connection to wireless network as configured from step 2, 6) response of the conection status with the wireless network, 7) request of the value of carbon monoxide (CO) 8) return the value obtained by the sensor, 9) interpretation of the given value, 10) request of the value of carbon dioxide (CO2), 11) return the value obtained by the sensor of carbon dioxide, 12) interpretation of the value delivered, 13) request of dust density value, 14) return the value obtained by the density sensor dust, 15) interpretation of the given value, 16) organization of information to be transmitted to the Web application, 17) Transmission of the
A. Arduino Electronic Device The electronic device is based on the Arduino UNO R3 model. It consists of an ATMega 328 microcontroller with a storage capacity of 32K, which is used to store a small program (sketch) that controls and interprets signals from sensors connected to the Arduino [31]. In this electronic board a Wi-Fi module has been added for connecting with a compatible wireless network with IEEE 802.11 b / g. Therefore, it was needed to employ an expansion module called Xbee Shield. The sensors that were configured and were used in determining the pollutant concentrations are: (1) carbon dioxide sensor (CO2) MG-811, (2) sensor carbon monoxide (CO) MQ-7 and (3) Sharp powder density GP2Y1010AU0F. Figure 2 illustrates the assembly of the elements of the electronic device. The three mentioned
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information organized and 18) response of the Web application. This sequence is illustrated in Figure 3.
reduction of the impact that changes could generate in the requirements.
B. Functional Requirements of the Software The design of the computer system identified four actors who interact with the Web application and electronic device responsible for measuring the concentration of pollutants in the environment. Two of these four actors, namely the visiting user and the advanced user, only interact with the Web application. The user visitor is able to visit the Web portal and to consult the information stored in the database. The advanced user is able to execute the actions of the visitor user and besides is allowing also the register and the management of the sensors of the electronic device connected to the Web application. The remaining two actors, namely the Arduino platform and the sensors, are electronic components that interact directly with the application server. Indeed, electronic sensors determine the contaminants concentration and communicate this information to the Arduino electronics, so that it is interpreted and organized using an API developed in C++ for this purpose. This information is stored in the Arduino’s Internal Flash Memory. Figure 4 illustrates the Use Cases that were determined under project line analysis. To the functional requirements illustrated in Figure 4, four attributes joined the Web application, such as: 1) adaptability to changing requirements, 2) future scalability, 3) ease of future maintenance, and 4) interoperability.
Figure 5.
Representation of the software layered architecture.
The four layers of the architecture of the software are: Client (JSF), Web Services (REST), Business (EJB) and Data (JPA) for the development of the project that allows having a scalable system that does not generate high losses related to costs, innovation and time. The election of the architecture in n-layers and to divide the system in subsystems, is a strategy that incorporates several advantages such as the re-use of components, the easiness in the maintenance and the reduction of the impact that may generate changes in the requirements. Using these premises figure 5 illustrates the architecture of the software that has been divided in four layers, each one representing specific functions allowing the communication to each other in order to provide the interaction among hardware (Arduino) and software (Applications Server). D. Data model design In this physical data model, there is a special emphasis on relationships and information generated by electronic sensors, taking into account that each one originates different values such as its symbol and unit. More than one sensor can be installed on an electronic Arduino board, which leads to group this information depending on the electronic device. This allowed also geo-referencing each device in order to generate a map, which may be consulted by the advanced and visitor user. Figure 6 illustrates the portion of the design of the database that responds to this configuration.
Figure 4.
E. Design Patterns Based on the work of Helm et al., [34] who argues that the use of design patterns helps achieve reusable software, we have used in this project the following design patterns: (1) Data Access Object (DAO) and (2) Model View Controller (MVC). The use of design patterns guarantees the adaptability of the system to changes in requirements, and high cohesion that each class will have within the operation of the software. The DAO design pattern has been used to access the data layer and it is separate from the business layer, while the MVC design pattern has been used to design the presentation and business layers. Figure 7 illustrates the combination of patterns used for each layer of the system and the relationships among them.
Use Cases identified within analyses and requirement specifications stage.
C. Software Architecture According to Pressman [24] the software architecture is a representation that allows analyzing the effectiveness of the design in order to meet the identified requirements, perform changes, reducing the risks at the time of programming the software. Similarly, Bennett et al., [33] argues that the choice to use architecture in layers, and split a computer system into subsystems, is a strategy that has several advantages such as the reuse of components, the ease in maintenance, and the
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using JSON format, due to the restriction of the hardware described in the Section 3, subsection A of this study. The architecture of the computer system for data persistence purposes is using DAO (Data Access Object) tier, once the electronic device is registered and authorized to transmit information. At the time of registration of the device (i.e., done by the advanced user), the computer system generates an API Key, in order to validate the electronic device access to the Web application. This information should be programmed in the firmware of the Arduino board, so that this authentication takes place at the time of the transmission.
Figure 6.
Figure 7.
G. Implementation and Testing A combination between Scrum and XP has been raised to address project implementation. Each provided the necessary elements to cover all stages of the construction of software and hardware. With the support of the methods that proposed Scrum, the planning, implementation and project documentation has been completed. For this work we have estimated duration of two months, divided into three iterations or sprints. The practices taken from XP focused on software coding needed for the experiment. The methods used were: test-driven development (TDD), incremental design, and 3) continuous integration. In this phase, using Scrum, unitary tests were carried out for each of the iterations. JUnit and Arquillian tools were used to generate the software tests required. The intention of the tests has been to evaluate the behavior of business and data layers. The Web service has been tested with Httprequester, a tool capable of generating http requests and view the respective report. In the development of the project contemplate three iterations in which liberated parts were the product that has been inspected and evaluated in order to increase the functionality and to improve quality regarding the previous version. The first iteration contemplated the construction of the hardware and it has been confirmed in two caves named “La Gruta de Virgen” and “Castle”, transmitting the obtained information through the USB port towards a laptop, with the objective of verifying the functionality of the sensors without being connected to the Internet through a Wi-Fi network. In the following iteration the computer system has been developed, with the objective of verifying the interoperability of the devices with the Web application, being connected with the Internet through a Wi-Fi network. In the last iteration we developed the GUI that allows the geo-localization of the devices through a map with the objective of visualizing in real time the gathered information. The unitary tests performed on all of the subsystems involved in the solution, proved the adequate operation of the overall system. Incremental design applies the test-driven development technique to all levels of design. In this scenario, developers work in small steps, proving each before moving to the next. The method of continuous integration has also been applied to remove the incompatibility in the operations among elements that compose the monitoring system. This allows hardware and software operation to achieve the required level of interaction.
Database physical design portion
Design Patterns combination
F. Web Service Design In relation to the Web service layer and in order to achieve the interaction between electronic devices and computer software, a Web service has been implemented so that it is capable of receiving, processing and storing information generated by the electronic sensors. This subsystem acts as a layer within the above-defined architecture and uses the business layer to accomplish data persistence once the electronic device is registered and authorized to transmit the information layer. At the registered moment of the device, the software generates an identifier and a string (API Key) to validate the electronic device access to the computer system of the experiment. This information must be programmed into the Arduino, as from which the transmission is performed by this authentication. Taking into consideration that the information sent from the sensors are analogue signals, JavaScript Object Notation (JSON) format must be used in order to transfer such information, due to the existing restriction of the Arduinobased hardware. In this context, Fain [35], points out that Restful Web services, in contrast to the SOAP type, are lighter and use the GET, POST, PUT and DELETE methods of the http protocol. The implementation must be represented
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H. End-Product Figure 8 illustrates the graphical user interface where the geo-located information is visible from the configured sensors. Besides the user interface allows to visualize the electronic devices management in Figure 9.
mAh that offered a useful time life of some two hours, enough to realize the needed measurements in the caves. The deployment of the model of this project is able to be repeated to a significant number of nodes that allows us to embrace areas where the commercial solutions are considerably expensive. The usual areas of such applications are determination of air quality, demonstrating the importance of this project in the industry of an air pollution monitoring system. IV.
Figure 8.
Figure 9.
Figure 10.
EXPERIMENTAL RESULTS
With the aim to prove results produced by the wireless monitoring system and hereby to determine the level of air pollution, the concentration of three considered contaminants (CO, CO2 and dust density) was determined in representative samples. The device runs a measurement every 15 seconds during the duration of one hour. Such data determination has been subsequently performed in three distinct places, being the sector Jipijapa inside the city of Quito, the Castle of Amaguaña in the Inter-Andean Valley, and the scientific research caves (Gruta de la Virgen and Castle) in the Amazon Basin close to the city of Tena central-east Ecuador. Some 269 carbon monoxide data were obtained, in the city of Quito. After statistical processing, with a confidence interval (CI of 95.0%), an average of 13.69 has been yielded with a standard deviation (SD) of 0.874. According to the WHO Regulations [15], the average of the maximum value for carbon monoxide should not exceed 10 micrograms/m3, while the legislation in Ecuador has established an average of 15 micrograms/m3. Nonetheless, according to the Ministry of the Environment of Ecuador the index of the annual average ranges between 17 and 20 micrograms/m3. That means, that the average value determined in our project retrieved is a permissible value that is below the average rate of the tolerated value in Ecuador but still above the values established by the WHO: 10 < 13.69 < 15. Dust density in Jipijapa (N=269), with a CI of 95.0%, an average of 0.076 ± 0.006 was obtained, where there is evidence of greater concentration in the range of [0.070, 0.082] mg/m3. For the SD, its average has been [0.036, 0.045] mg/m3. This average is below the tolerance of the breathable dust (0-0.8 mg/m3) according to standard ASHRAE - 62 for the air in internal spaces [36]; and the average concentration in air of 0.26 mg/m3 for external spaces, according to the standard of the protection of the Environment Agency of the USA (US EPA). In the same way, in order to compare the degree of contaminants, the coefficient of variation (CV) is a measure of statistical dispersion, which is calculated as relationship between the standard deviation over the average. CV = /x = 0.87/13.68 = 0.0638; 0.638*100% = 6.387%. Similarly, a measurement of pointing or kurtosis of a variable has been realized with the degree of concentration of the values around their average. For the concentration of the carbon monoxide in Quito, for example, AP = 14.66 > 0, i.e. the values are highly concentrated on the basis of its average (13.68), therefore the pointing is leptokurtic.
Graphical user interface of the Web site
Graphical User Interface where the electronic device is configured on the platform
Wireless electronic device based on the platform
To end, Figure 10 illustrates the Arduino UNO R3 board with all elements assembled. Each device has an electric power adapter that has been used for the determination of the data in Quito and the Castle of Amaguaña. Additionally, the devices used a rechargeable battery of lithium of 5000
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In summary, the results indicate that the use of the wireless monitoring system in Quito, the air quality is below the permitted limits established by the international standards, (i.e. US Environmental Protection Agency (USEPA). In the case of the caves, the study reveals that the CO2 concentration does not exceed the reference value of the atmospheric average of 400 parts per million.
Figure 11 illustrates the densities of dust in Quito, Castle and Gruta de la Virgen (i.e. a karst cave), clearly pointing a leptokurtic type. CVs are in the following order: Castle, Quito and then the Gruta de la Virgen, as follows: 51.45% < 52.72% < 57.09% respectively, the values are in the range of 5.64%. This value means an amount of dust particles in the underground environment, which just allows the presence therein, with values just below the acceptable “bigotry”. With this type of measurement on-site, one is able to monitor in real-time, the present hazards or threats potentially harmful to health. Furthermore, as seen in the boxplot of Figure 11, Quito has a higher median as measurement location, being as a metropolitan city having a higher density of dust than other two measured sites.
Figure 11.
V.
During our research has been performed, some related studies appeared. The following studies will be mentioned being the closest to our research: Huang in [1] proposes a real time system to measure the concentration of gases such as CO2, NO2, CO and O2, using calibration technologies, which focuses on the design of the hardware, with complex electronic devices, developing a Web interface to display the data. Our work implements an economical solution of hardware and software for real time air pollution monitoring, based on a distributed environment. The work proposed by Prasad et al., [3] uses a network of electronic sensors to measure the pollutants concentration at the city of Hyderabad in India. It expands its capabilities with an expansion module Xbee capable of supporting the ZigBee standard. The authors point out that they mounted the O2, CO, CO2 and NO2 sensors in a Waspmote card, supporting wireless communication, and they do not present any design for the computer system development. Compared to our work, this study focuses mainly on the hardware design, developing a Web interface to display the data. In similar context, Raju in [4], performs the hardware construction and operation of the ZigBee standard and its application in the construction of a WSN to measure the quality of the air. There, an Arduino board is used to control the expansion of the ZigBee module, and an MQ-7 sensor is used to measure the carbon monoxide (CO). Compared with our work, we have built a comprehensive solution, both in hardware and in software. Devarakonda in [5] presents an Arduino based prototype, which measures the air quality over a low cost mobile unit, which is able to measure carbon monoxide levels in real time. The node is a wireless sensor, which is associated with a smart phone in order to act as an interface with the server hosted in the cloud computing. In [6] work proposes a WAPMS in order to monitor and control the air pollution resulting from industrial activities in the city of Moka, Republic of Mauritius. This research only defines the requirements needed to build a Wireless Sensor Network (WSN), which will be capable of monitoring air pollution, and the implementation of an algorithm for data aggregation. Our work in relation to [6] and [3], implements an economical solution based on hardware and software, which will allow us to achieve real time air pollution monitoring work, using a control-data-and-errors algorithm contained in an API developed in C++. In other studies, the work proposed by [7] demonstrates a real time air quality monitoring system, through a web application and mobile devices. Four monitoring stations were used, powered by solar energy. The first two stations are equipped with sensors to measure the ozone (O3),
Dispersion and localization charts of dust density of the three measured places.
The CO2 data are illustrated in Figure 12, demonstrating a behavior type of platykurtic pointing. In this case, CV indicates that the Gruta de la Virgen is having less concentrations than the Castle of Amaguaña, and both mentioned sites are having lower concentration than Quito (i.e. CV=6.38%36.37%). Furthermore, as indicated in the box diagram of Figure 12, Quito has a higher average median as measurement location. That means that the Gruta de la Virgen being a karst cave is the one site that has less CO2 pollution compared to the other measured sites.
Figure 12.
RELATED WORK
Dispersion and localization charts of CO2
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nitrogen dioxide (NO2) and carbon dioxide (CO2) and the last two stations are only equipped with sensors to measure the hydrogen sulfide (H2S). It uses an M2M communication protocol that operates on a GPRS or 3G network, which is responsible for connecting all monitoring stations for data transfer purposes. In [8] study mentions that WSN is a technology for real time data collection that is evolving rapidly. This is why the authors used specific criteria to select monitoring nodes, located in the Centre of the city of Olomouc in the Czech Republic, in order to measure harmful atmospheric contaminants and various meteorological elements. Waspmote nodes and ZigBee communication protocol, for wireless personal area (WPAN), turned out to be the best choice for this particular type of application. Our work, in comparison with the previous two, is a true low cost alternative that allows transmitting data from Arduino board sensors, using the IEEE 802.11 specification b/g. Concerning to nodes and sensors, in [9] this research is composed of different types of nodes, including 44 sensors for air quality, 40 transmitting nodes and 4 gateway nodes; which mean that the monitored results (four months), were not directly transferred to the database, but transmitted from sensor to sensor. Each sensor node includes a module for signal processing, carbon monoxide (CO) sensor and a ZigBee wireless communications module. This WSN comprises two main components: (1) front end, i.e., the network geo-sensor and (2) back-end, i.e., the monitoring and control of the platform. The four nodes of the data gateway connect the front-end and the back-end to the Internet. Finally, in [10] research, proposed by al Hasan et al., studies an optimized method to use fewer sensors, in order to monitor a study area. In relation to [9] and [10], our research is organized in a distributed n-tier model. With the purpose of achieving interaction between the hardware and the software, a Web service REST type was implemented, capable of receiving the information generated by electronic sensors. This information is transferred in XML or JSON format, with the latter being the lightest resource due to the restriction of the Arduino-based hardware. In this context, the Web services REST-style in contrast to the SOAP are lighter. VI.
system of monitoring, as well as in the reference measurement of air contaminants concentration. As a potential future complementary study, we may focus on the implementation of software, hardware and firmware for a network of wireless nodes interconnected and intercommunicated among them, in which case every node is able to transmit information to its juxtaposed node and this one to another one and so on, until arriving to the central node that sends the information to the Internet in order to improve the communication covering. With the gathered and stored information it would be able to apply analysis processes to generate predictions and behavior models of polluted air in the cities that allows the support in the process of decision-making. ACKNOWLEDGMENTS This work has been partially funded by Distributed System, Cybersecurity, and Content Research Group of the Universidad de las Fuerzas Armadas ESPE of Sangolquí, Ecuador. The authors would want to thanks the good advices of our anonymous reviewers, who contributed favorably to this exploration. REFERENCES [1]
Huang, Le Hui, and Bin Gui. "Discussion on Air Pollution and Its Control Measures." Advanced Materials Research. Vol. 1010. 2014. [2] S. Kumar and D. Katoria. "Air Pollution and its Control Measures". International Journal of Environmental Engineering and Management. ISSN 2231-1319, Volume 4, Number 5 (2013), pp. 445-450. [3] Raja Vara Prasad, Mirza sami Baig, Rahul K. Mishra, P. Rajalakshmi, U.B. Desai, S.N. Merchant, "Real Time Wireless Air Pollution Monitoring System". ICTACT Journal on Communication Technology: Special Issue on Next Generation Wireless Networks and Applications, volume - 2, Issue - 2. ISSN: 2229-6948. 2011 [4] Raju, P. Vijnatha, R. V. R. S. Aravind, and B. Sangeeth Kumar. "Pollution Monitoring System using Wireless Sensor Network in Visakhapatnam. (2013). [5] Devarakonda, Srinivas, et al., "Real-time air quality monitoring through mobile sensing in metropolitan areas." Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing. ACM, 2013. [6] Khedo K., Perseedoss R., Mungur A. University of Mauritius, Mauritius. “A Wireless Sensor Network Air Pollution Monitoring System”. International Journal of Wireless & Mobile Networks 2.2 (2010) 31-45. [7] Kadri, Yaacoub, Mushtaha, and Abu-Dayya. "Wireless Sensor Network for Real-Time Air Pollution Monitoring". Qatar Mobility Innovations Center, 2013 IEEE. [8] Vendula Hejlová, Vít Voženílek. "Wireless Sensor Network Components for Air Pollution Monitoring in the Urban Environment: Criteria and Analysis for Their Selection". Published Online December 2013. Wireless Sensor Network, 2013, 5, 229-240. [9] Tzai-Hung Wen, Joe-Air Jiang, et al., "Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework". Published online 2013. [10] Al Hasan M., Ramachandran K.K., Mitchell J.E. Optimal placement of stereo sensors. Optim. Lett. 2008, 2, 99-111. [11] Hernández M., Encalada M., Molina S., González M., Cotacachi F., (2010). Plan Nacional de la Calidad del Aire. Ministerio del
CONCLUSIONS AND FUTURE WORK
The objective of this research was to apply a software development process. To this end, agile methodologies such as SCRUM and XP were used in a combined way. The purpose has been to build a real-time monitoring wireless system for working on air pollution. The prototype included a computer system based on architecture of n layers, whose hardware and software are open source and low-cost. In addition, in order to achieve data transmission, a software component (API) was developed and coded, using C/C++ language. With this software model and the use of the Arduino-based hardware, we sought to reduce costs in the market and provide more cost-effective solutions that compete with available commercial solutions. The proof of concept was applied in the cities of Quito, Amaguaña and Tena, Ecuador, obtaining positive results, both in the operation of the software and hardware that compose the
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