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Chemicals Detection in Water by SENSIPLUS Platform: Current State and Ongoing Progress
Abstract
The challenge to detect contaminants inside water solutions is addressed in this paper, through the use of an integrated, low-cost, smart and IoT platform, namely SENSIPLUS. In particular, the complete process from the sensing phase to classification and results analysis is provided with further investigations about the limitations of the current proposal and the description of a further processing technique that promises to improve classification accuracy. The classification is performed by adopting machine learning techniques, particularly Artificial Neural Network, that well fits the implementation on a low-cost microcontroller, as the one SENSIPLUS platform uses.
“Compact and lightweight” graphene-based mortars were produced and their piezo-resistive behavior was analyzed. Such property is exploitable in the production of functional building materials, which could work as stress–strain sensors. First, graphene-isopropyl alcohol dispersion was synthesized through Liquid Phase Exfoliation and the few layered structure was evidenced via Raman spectroscopy. Afterward, “compact and lightweight” mortars-graphene based composites were produced by using, respectively, cement and cement/diatomite as matrix, the previously mentioned graphene dispersion and a suitable amount of water. The morphological, structural, thermal and electro-mechanical properties of the obtained materials were analyzed. The mix-design here discussed can pave the way for a new kind of eco-friendly, multi-applicative, multi-responsive building material.
The evaluation of measurement quality is a primary task when performing sensing activities based on low–cost sensor technologies. In detail, in this work electrical impedance measurements on different sensors are proposed in order to have a dataset of raw data to be used to perform classification of possible contaminants in water environment. In detail, the sensor technology is based on a proprietary multi-sensing platform which is arranged in a suitable set-up able to carry out measurements in water for prolonged times. Sensors metalized with different materials are jointly used to exploit sensitivity diversity to different contaminants. An ad–hoc measurement procedure has been designed, including data acquisition during warm–up period, contaminant injection and steady state conditions. Since different releases of the platform have been developed, here we propose a comparison between two versions to demonstrate the technological advance in sensor integration and miniaturization leading to higher reliable results. A metrological analysis of the obtained measurements with two different platform versions is carried out and compared results are reported.
The need to ensure future food security and issues of varying estuarine water quality is driving the expansion of aquaculture into near-shore coastal waters. It is prudent to fully evaluate new or proposed aquaculture sites, prior to any substantial financial investment in infrastructure and staffing. Measurements of water temperature, salinity and dissolved oxygen can be used to gain insight into the physical, chemical and biological water quality conditions within a farm site, towards identifying its suitability for farming, both for the stock species of interest and for assessing the potential risk from harmful or toxic algae. The latter can cause closure of shellfish harvesting. Unfortunately, commercial scientific monitoring systems can be cost prohibitive for small organisations and companies to purchase and operate. Here we describe the design, construction and deployment of a low cost (<£5,000) monitoring buoy suitable for use within a near-shore aquaculture farm or bathing waters. The mooring includes a suite of sensors designed for supporting and understanding variations in near-shore physical, chemical and biological water quality. The system has been designed so that it can be operated and maintained by non-scientific staff, whilst still providing good quality scientific data. Data collected from two deployments totalling 14 months, one in a coastal bay location, another in an estuary, have illustrated the robust design and provided insight into the suitability of these sites for aquaculture and the potential occurrence of a toxin causing algae (Dinophysis spp.). The instruments maintained good accuracy during the deployments when compared to independent in situ measurements (e.g. RMSE 0.13–0.16 °C, bias 0.03–0.08 °C) enabling stratification and biological features to be identified, along with confirming that the waters were suitable for mussel (Mytilus spp.) and lobster (Homarus gammarus) aquaculture, whilst sites showed conditions agreeable for Dinophysis spp.
Water Pollution: Causes, Effects And Control Is A Book Providing Comprehensive Information On The Fundamentals And Latest Developments In The Field Of Water Pollution.The Book Is Divided Into 28 Chapters Covering Almost All The Aspect Of Water Pollution Including Water Resources And General Properties Of Water; History Of Water Pollution And Legislation; Origin, Sources And Effects Of Pollutants; Bioaccumulation And Biomagnification; Toxicity Testing And Interaction Of Toxicities In Combination; Water Quality Standards; Biomonitoring Of Water Pollution; Bacteriological Examination And Purification Of Drinking Water; Monitoring And Control Of Pollution In Lakes, Rivers, Estuaries And Coastal Waters; Physical And Biological Structure Of Aquatic Systems; And Structure, Properties And Uses Of Water.Some Important Topics Like Eutrophication, Organic Pollution, Oil Pollution And Thermal Pollution Have Been Discussed In Detail. The Water Pollution Caused By Pesticides, Heavy Metals, Radio Nuclides And Toxic Organics And Inorganic Along With The Water Quality Problems Associated With Water-Borne Pathogens And Nuisance Algae Have Also Been Dealt With Extensively.The Book Covers In Detail The Flow Measurement And Characterization Of Waste Waters In Industries, And Control Of Water Pollution By Employing Various Techniques For Treatment Of Biological And Nonbiological Wastes. The Considerations For Recycling And Utilization Of Waste Waters Have Also Found A Place In The Book. Special Topic Has Also Been Given On Water Pollution Scenario And Water Related Policies And Programmes In India.The Book Shall Be Of Immediate Interest To The Students Of Environmental Science, Life Science And Social Sciences Both At Undergraduate And Postgraduate Levels. People From A Wide Variety Of Other Disciplines Like Civil, Chemical And Environmental Engineering; Pollution Control Authorities; Industries; And Practicing Engineers, Consultants And Researchers Will Also Find The Book Of Great Interest.
Nowadays, an increasing concern about people and environmental health and safety is spreading all over the world, and technologies such as efficient monitoring systems are furthered. In the field of air quality, filtering systems, especially based on activated carbons (ACs), are commonly used. In most cases, their state of health is not monitored, and their time of life is based on statistical and a priori evaluations. This paper proposes a novel microsensor platform for the real-time monitoring of AC filters based on the impedance measurements during gas exposition. A metrological characterization of the novel proposed instrument is provided in this paper, by comparing its output to a reference RLC meter. A calibration and adjustment procedure is developed in order to analyze the device measurement capabilities and obtain correction coefficients. Experiments with different gas typologies are presented, and the analysis of filters impedance dynamics is provided. IEEE
This paper proposes the realization and preliminary characterization of a smart sensor platform for the online monitoring of the residual life of activated carbon air based filters. The platform performs the measurement to give reliable information about the filter maintenance or early warning for the presence of dangerous gases both in industrial and military scenarios. A preliminary feasibility study has been carried out to evaluate the activated carbon filter electrical impedance sensitivity to chemicals adsorption. After a detailed presentation of the employed hardware and software solutions, a description of the experimental setup is given and a preliminary proof of the assumed relationship is provided.
Water is a vital resource for natural ecosystems and human life, and assuring a high quality of water and protecting it from chemical contamination is a major societal goal in the European Union. The Water Framework Directive (WFD) and its daughter directives are the major body of legislation for the protection and sustainable use of Euro- pean freshwater resources. The practical implementation of the WFD with regard to chemical pollution has faced some challenges. In support of the upcoming WFD review in 2019 the research project SOLUTIONS and the Europe- an monitoring network NORMAN has analyzed these challenges, evaluated the state-of-the-art of the science and suggested possible solutions. We give 10 recommendations to improve monitoring and to strengthen comprehen- sive prioritization, to foster consistent assessment and to support solution-oriented management of surface waters. The integration of effect-based tools, the application of passive sampling for bioaccumulative chemicals and an in- tegrated strategy for prioritization of contaminants, accounting for knowledge gaps, are seen as important ap- proaches to advance monitoring. Including all relevant chemical contaminants in more holistic “chemical status” assessment, using effect-based trigger values to address priority mixtures of chemicals, to better consider historical burdens accumulated in sediments and to use models to fill data gaps are recommended for a consistent assessment of contamination. Solution-oriented management should apply a tiered approach in investigative monitoring to identify toxicity drivers, strengthen consistent legislative frameworks and apply solutions-oriented approaches that explore risk reduction scenarios before and along with risk assessment.
Spectrum sensing is a fundamental task in the complex field of cognitive radio systems. It allows a cognitive terminal to scan a frequency span of interest and sense the presence of other users transmitting over it. Many spectrum sensing methods are present in literature and many interesting algorithms have been proposed. Unfortunately, very few methods allow to know the exact boundaries of the user signal, without knowing any channelization of the spectrum of interest. In this context, the paper proposes two novel algorithms, whose purpose is twofold: to keep a low computational burden and to provide information at the most detailed level with respect to the category the algorithms belong to. Tests, executed on simulated and emulated signals, have demonstrated that both algorithms allow reaching a detection probability greater then 95% and a false alarm probability lower then 5% even in scenarios characterized by SNR as low as −10 dB.
In Cognitive Radio applications, spectrum sensing plays a fundamental role in order to learn the behavior of
primary users (PUs) and access to the spectral resource opportunistically. Among the available methods, a surely promising approach is the wavelet based one. It allows to subdivide the wide-band spectrum under analysis in a proper number of sub-bands, based on Power Spectral Density (PSD) irregularities, remarked by the extrema of the Continuous Wavelet Transform (CWT) first derivative. Generally, such kind of methods works
well as long as good Signal-to-Noise Ratio (SNR) can be experienced over the span of interest. In this context, starting from an approach present in literature, the present work proposes, customizes and implements a wavelet based spectrum sensing method, thought to operate also in challenging SNR scenarios.
The paper proposes a new smoothing method to reduce noise contribution in frequency spectra, whose analysis is accomplished in order to perform spectrum sensing task for Cognitive Radio applications. The smoothing phase is a fundamental step in frequency analysis, since noise often corrupts user signals, by preventing them to be detected and, consequently, either protection or demodulation become impracticable. Such a need is usually satisfied through the use of moving average filters. These kinds of filters are affected by some problems which make the sensing stage not accurate and scarcely reliable. The authors propose the employment of Savitzky-Golay filters, which are already widely used in biomedical image analysis, but they are almost absent in Cognitive Radio field, to our knowledge. The goodness of such an approach is proved by two different figures of merit, testing the filtering abilities and the sensing performance improvement, thanks to the previous smoothing stage. A comparison is finally proposed with the standard linear moving average method.
The water quality monitoring plays an important role in water contamination surveillance and guides the water resource protection for safe and clean water. A flexible automated real-time water quality monitoring and alarm system based on the wireless sensor network(WSN) is proposed. The WSN is built in accordance with Zigbee communication protocol, which consists of the sensor nodes, route nodes and coordinator node. The sensor nodes based on cheap and efficient sensors (pH electrode, dissolved oxygen electrode, temperature senor) and wireless transreceiver collect the environmental data and transmit to the coordinator node via the route nodes. The data are sent to the remote monitoring center with the help of GPRS. The time synchronous algorithm is adopted to wake up all the nodes in the network to improve the stability and reliability of the communication. The long-time measurement results verify the real time and accuracy in data acquisition and stability and reliability in communication. The system meets the requirements of water quality monitoring, and has great practical value.
Communication networks are widespread today. New services are now starting to run on these networks to meet the requests of modern users. To offer good service typically hard constraints have to be satisfied, especially when real-time services are involved. To this aim the reliable estimation of Quality of Service (QoS) parameters as bandwidth, packet jitter, latency, one way delay, to cite a few, is a key issue for communication networks setup, monitoring and tuning Generally, the measurement of QoS parameters is a complex process that involves several troubles. Some of them depend on the measurement network features: (i) the medium employed to convey the data stream (optic fiber, wireless, wired, etc.), (ii) the type and number of network devices involved (network interface cards, switches, routers, etc.), (iii) the type of communication and access protocols, and (iv) the variability of the network background traffic which could strongly influence the measurement result. Further troubles come from the measurement chain and the measurement method adopted: type of measurement instruments, sampling and observation times, packet size, type of measurement post processing to cite a few. Therefore, they can be thought as sources of measurement uncertainty able to strongly influence the measurement process and the reliability of the results. With reference to the measurement chain and the measurement method adopted, in this paper a deep sensitivity analysis aimed to identify the main quantities influencing the measurement results and to study their modeling as uncertainty components is performed. The attention has been focused on the packet jitter estimation made on a real test bed: the fiber optic based local area network of the University of Cassino (Italy).