Industrial Air Pollution Monitoring System Based on Wireless Sensor Networks

Environmental conditions have a major impact on our well-being, comfort and productivity. Present state of the air quality control in almost all manufacturing industries in our country is based on taking samples one or few times a day, which means that there is no information about time distribution of polluted materials intensity during day. This paper proposes an industrial air pollution monitoring system based on wireless sensor network system that enables sensor data to be delivered within time constraints so that appropriate observations can be made or actions taken. Obtaining these accurate real-time results in-situ allows regulatory agency to take necessary action whenever pollution occurs. The analysis focuses on six substances, known as criteria air pollutants – ozone, particulate matter, sulphur oxides, nitrogen oxides, carbon monoxide, and lead. The sensors self-organize themselves in a radio network using a routing algorithm, monitor the area to measure the gas levels in air and transmit the data to a central node, sometimes called a pollution server or base station (interfaced with coordinator), or sink node, that collects the data from all of the sensors. With the results from the data acquisition system in hand, the regulatory agent need to implement a number of decisions based on the final statistics. The data obtained from the experiments were analysed in real-time analysis and the results from two sensor nodes taken for a 24 hours period were promising. The usage of this system will reduce human health effects of industrial air pollutants and potential damage to other aspects of the environment

Development of a new device for the measurement and modeling of an innovative risk index for cultural heritage application

The monitoring, as a function of time, of environmental parameters in cultural heritage is essential to preserve materials, to recognize the reasons of degradation and to evaluate their effects. The degrading effects of objects in cultural heritage field, can be classified in optical, morphological, physical-chemical/mechanical and alterations and depend by micro-climatic conditions. For this reason, in recent years, several solutions have been developed and commercialized for environmental monitoring, some compatible with general advice and others OEM (Original Equipment Manufacturing). However, the trend of application between compliant and non-ISO-compliant devices has not yet been sufficiently analyzed. In this first section, we show how in the last ten years researchers have shifted their attention to custom-made devices based on new generation sensors despite the expense of units ISO certified. The study based on a review of scientific articles has shown that: with the increase of low-cost and open-source technologies applied in the Environmental Impact Assessment (EIA) and in particular in the cultural heritage, led to a research advancement in the field, but, at the same time, increased non-homogeneity of the methods, impinging comparability of results. In recent years the trend is to use low-cost automatic wireless systems. This innovation, however, opens new scenarios and challenges on how to improve their stability, longevity, and sensitivity; reduce maintenance (battery replacement, including calibration or sensors); improve data analysis/management/display costs. In particular, it has highlighted the current difficulty of low-cost detectors to satisfy the robustness and reliability of regulatory and conventional stationary monitors at the expense of the periods and aesthetics. We have therefore paid particular attention to the sensitivity and reliability of the innovative solutions presented to overcome the traditional limitations, as well as to the real feasibility of solutions regarding sustainability, adaptability to the works of art or price. We also see the need for more communication between the scientific community and the decision-makers, who have only recently opened up to this paradigm. We highlighted the need to identify recurrent or innovative topics in the various documents concerning the approaches to preventive conservation, the preservation of damage and environmental management. After a review of state of the art regarding the different sampling device applied in cultural heritage and a survey of the parameters that involve a degradation effect on the materials, in this section, we focus our attention on a sensors-based prototype able to detect: (i) temperature and relative humidity; (ii) NO, NO2 and SO2; (iii) vibrations. In particular, this section describes the design and the validation of the Wireless Sensor Network (WSN) propose3, named WENDY, an acronym for Wireless Environmental moNitoring Device prototYpe. WENDY, built on a microcontroller of ATmega328P series, gathers signals from a sensor for temperature and relative humidity; a 9-axis MIMU; and three gas detection miniature boards (NO, NO2 and SO2). Complete the board a connector for memory card (SD) and an RTC. Additionally, a module based on the ZigBee standard could be used to transmit all data. In this section, precisely, we present the performances of the WSN node in detecting: structure tilt, vibrations and the daily cycle of humidity, temperature and gas deposition. The experimental setup used to evaluate the accuracy of MIMU system highlighted a relative error on shock acceleration measurement, in term of normalized root mean square error, lower than 0.1 % for the sinusoidal input and 0.51 % for cardinal sin input, with an average accuracy in the principal peak reconstruction of 1 % in the chosen frequency range (5 Hz to 50 Hz). The MIMU accuracy for tilt measurement, evaluated through the root mean square error was equal to 0.3° and a standard deviation always lower than 0.4° in the 0-90° tilt range. The gas detection and temperature/ humidity boards showed data comparable with the nearby certified ARPA system device. The aim of the applicative section is monitoring effects of different factors which affect the “Minerva Medica Temple,” an archeological site in Rome. In particular, we focus on: (i) the seasonal thermal variations on the structure; (ii) the contamination due to by local traffic regarding gaseous pollutant and (iii) the dynamic response of the structure to a tramway line located in Rome and called “Roma- Giardinetti.” The developed system allows for prioritization of intervention both for management and interventions planning, regarding restoration, consolidation, and conservation. Moreover, the software structure of the environmental monitoring device is presented and expounded in detail.4 Always in this section, an innovative procedure for the evaluation of the environmental hazard in cultural heritage is proposed. This risk assessment can be considered as a “relative risk assessment methodology.” In particular, it considers the impacts of microclimatic conditions on the monument, based on the international norms and the current scientific knowledge. For measurement campaigns with WENDY, the risk method proposed is applied to the results of two measurement campaigns carried out between 2017 and 2018 over two different periods (September-December and March-July), at “Minerva Medica Temple,” in Rome

Wireless Sensor Network for Real Time Pollution Monitoring and Smart Grid Applications

Wireless sensor nodes are electronic boards made up of sensors, processor and communication modules. Generally they are battery powered which limits its functionality, reliability and durability in many aspects. These nodes are use to collect information from various environments which extend from favorable one such as office environment to very harsh environments such as factories, deserts and forests. It is very important for the sensor nodes to provide the reliable information as based on these certain control systems will be planned. Apart from on-board challenges, pervasive sensor network will face many different challenges depending on the environment in which they are deployed. Every different use case has a different set of problems to be answered to make the network robust and reliable. In this thesis, we have studied the challenges of pervasive sensor network for two different applications viz., Air Pollution Monitoring and Smart Grid. We have employed a real time implementation technique to understand and analyze the problems of sensor network for Air Pollution Monitoring. As an outcome of our research, we have developed a low cost sensor node, which answers few of the problems associated with sensor networks. To study the application and challenges of pervasive sensor network in smart grid, we have adopted simulation method. Different communication technologies are simulated viz., Wi-Fi, Cognitive Radio and Cellular Networks to understand the pros and cons of each of them so that to analyze whether they meet the latency and other criteria of smart grid applications. Cognitive radio is found to be promising in providing free long distance communication for nonreal time application such as Field area network within smart grid paradigm whereas Wi-Fi could be consider as fall back medium in presence of primary user of licensed spectrum. Spectrum sensing turns out to be the biggest problem in cognitive radio technology

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Removal of Heavy Metal Ions Using Magnetic Materials

Heavy metal ions contaminate water environment through point sources and nonpoint sources. Heavy metal ions are categorized as inorganic contaminants by both the WHO and the USEPA. The heavy metal ions are increasingly being introduced into the environment as pollutants and contaminants resulting from human activities. Magnetic particles for water treatment applications have received considerable attention from researchers due to high separation efficiency. The magnetic particles behave similar to or even better than various commercial adsorbents. The magnetic particles also exhibit high selectivity for the target pollutants from the environment besides enabling ease of operation for reducing the particle separation steps from the flowing stream. A comprehensive and systematic understanding of synthesis and surface modifications of magnetic particles is significant to enhance their practicability in environmental technology. Although high removal performance and reactivity can be achieved by smaller particle size, the stability, toxicity, and recovery of the particles magnetically could be challenging. In contrast, the active surface of magnetic particles may be forfeited, while surface modifications stabilize and reduce the toxicity of the particles. Reliable surface modifications are necessarily needed for the increment of the number of active sites to remove the heavy metals. For successful environmental applications of the magnetic particles, modification on the magnetic particles is principally crucial to balance the effects on their reactivity, capacity, and reusability

Water quality monitoring in recirculating aquaculture systems

Good water quality in recirculating aquaculture systems (RAS) is crucial for ensuring the successful growth and survival of reared species. So far, there are no regulations for which parameters should be measured in RAS, and each farmer decides which parameters to follow. Traditionally, water quality parameters have been measured at certain intervals with handheld sensors and laboratory analyses, which can be labour intensive. Currently, a variety of sensors and monitoring equipment is available, even for the real-time monitoring of water quality parameters. Internet of Things-based systems and artificial intelligence can be applied for the monitoring purposes which allows real-time measurements and warnings of critical situations. However, many of the modern systems need competent users and require regular maintenance and calibration. Changes in water quality also induces changes in fish behaviour, such as swimming activity, depth, acceleration and water quality can be assessed also based on these changes. In this review, water quality parameters, variety of sensors and monitoring technologies have been summarised to provide an overview of the current monitoring systems for water quality. Additionally, analytical methods for more advanced analyses have also been briefly summarised. Although there are several advanced options available for monitoring the basic water quality parameters, real-time measurements of more advanced parameters still required require further development