Flexible Monitoring Research Articles

An Emerged Challenge of Air Pollution and Ever-Increasing Particulate Matter in Pakistan; A Critical Review

This study, for the first time, aims to evaluate the situation of air quality in Pakistan critically; through a detailed assessment of sources, policies, and key challenges to identify the plausible way forward. Air pollution and particulate matter have merged as a global challenge in recent years because of its growing health and socio-economic risks. The intensity and impacts of these risks have become more pronounced, especially in developing countries like Pakistan that lack adequate warning, protection, and management systems. Various epidemiological studies have linked poor air quality with different health disorders and increasing death rates. In Pakistan, mortality rates as a result of exposure to increased levels of air pollutants, especially particulate matter, are alarming. According to the World Bank’s estimates, Pakistan’s annual burden of disease from outdoor air pollution is responsible for around 22,000 premature adult deaths and 163,432 DALYs (disability-adjusted life years) lost. The concentration of major air pollutants in Pakistan, such as NOx, O3, and SO2 have also been increasing significantly over the last two decades. Several studies are also reporting multiple instances of air quality around the major cities of Pakistan being consistently exceeding the national guidelines. During teh year 2019 PM2.5 cocnentrations in the city of Lahore revealed that almost every single day was in exceedance of the WHO and national air quality standards. Although the substantial effects of these rising pollutant concentrations in Pakistan have been stated in a few studies, however, the total extent, nature of contributing factors, and consequences remain inadequately understood. This study aims to use data available from monitoring stations, satellites, and literature to highlight the gaps in our understanding and emphasize the critical challenges associated with poor air quality faced in Pakistan. Topmost is the lack of air quality monitoring systems followed by poor initiatives by policymakers and enforcement agencies. A way forward while addressing these key challenges is also discussed, which focuses on the development of flexible monitoring, new technologies, and monitoring approaches in addition to communications among the various public, private agencies, and all relevant stakeholders.

One-sided precedence monitoring schemes for unknown shift sizes using generalized 2-of-(h+1) and w-of-w improved runs-rules

Parametric monitoring schemes are expected to perform better than their nonparametric counterparts when the assumption of a specific form of a distribution such as the normal is met. In practice, such assumption is often violated. Consequently, the performance of parametric schemes deteriorates considerably. To solve this problem, more efficient and flexible monitoring schemes based on nonparametric tests are recommended. In this paper, efficient and robust one-sided monitoring schemes are developed using generalized {1-of-1 or 2-of-(h + 1)} and {1-of-1 or w-of-w} improved runs-rules (IRR) without any distributional assumption in the zero- and steady-states modes. Moreover, the zero- and steady-states run-length properties of the resulting one-sided IRR schemes are formulated and empirically evaluated using the Markov chain technique. Comparisons with other well-known one-sided Shewhart-type nonparametric schemes (e.g., basic precedence scheme and precedence scheme with standard runs-rules) indicate that the proposed schemes have a better performance. Real data are used to demonstrate the design and implementation of the one-sided improved runs-rules precedence schemes. Finally, a discussion on the two-sided IRR precedence schemes is also provided.

Automated Data Filtering Approach for ANN Modeling of Distributed Energy Systems: Exploring the Application of Machine Learning

To realize the distributed generation and to make the partnership between the dispatchable units and variable renewable resources work efficiently, accurate and flexible monitoring needs to be implemented. Due to digital transformation in the energy industry, a large amount of data is and will be captured every day, but the inability to process them in real time challenges the conventional monitoring and maintenance practices. Access to automated and reliable data-filtering tools seems to be crucial for the monitoring of many distributed generation units, avoiding false warnings and improving the reliability. This study aims to evaluate a machine-learning-based methodology for autodetecting outliers from real data, exploring an interdisciplinary solution to replace the conventional manual approach that was very time-consuming and error-prone. The raw data used in this study was collected from experiments on a 100-kW micro gas turbine test rig in Norway. The proposed method uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to detect and filter out the outliers. The filtered datasets are used to develop artificial neural networks (ANNs) as a baseline to predict the normal performance of the system for monitoring applications. Results show that the filtering method presented is reliable and fast, minimizing time and resources for data processing. It was also shown that the proposed method has the potential to enhance the performance of the predictive models and ANN-based monitoring.

Nanowire Organic Sensor for Ammonia Detection

Ammonia is one of the largest produced chemicals with a global production of 150 million tons in 2017, expected to increase 8% in the next 4 years. It is widely used in several industries mainly in fertilizers manufacturing, but also in refrigeration systems, production of plastics, and as intermediates for pharmaceuticals synthesis. However, ammonia is highly corrosive and can damage cells in the body in contact, posing serious health risks. Despite the developments made in the detection systems, ammonia is still one of the most dangerous substances, responsible for the second highest number of chemical exposure casualties. The current detection solutions have serious limitations to be broadly used in industrial safety. Detection systems can generally fall under two categories, high-end equipment that is expensive, not user-friendly and can be only used in lab settings, and affordable devices that is prone to false alarms in a varying environment (humidity, temperature, etc.).In this presentation, we will talk about the Nanowire Organic Sensor technology as an alternative solution platform for ammonia monitoring that is affordable and can provide real-time and wide-area coverage. Our patented technology is a room-temperature process based on electrochemical deposition which facilitates scalable manufacturing directly on substrates and devices. Compared with the existing nanowire sensor fabrication methods, out innovation has four main unfair advantages. 1) By direct deposit of a solution droplet, nanowires are created right on chips or micro-fabricated devices. 2) It is a room temperature fabrication process, thus enabling less complex and capital-intensive manufacturing process. 3) It is a modular method that enables combinatory synthesis of a wide range of new organic nanowires. 4) It is a fabrication technology compatible with flexible electronics platforms. We will show how the combination of the sensor arrays, impedance spectroscopy and artificial neural networks model enhances the selectivity in varying levels of humidity. We will also talk about how the technology is compatible with the internet of things technology and cloud services, and how the combination could be leveraged to ensure more flexible monitoring of ammonia for industrial safety.Keywords: Electrochemical deposition, chemical sensing, nanomanufacturing.

Disparate Environmental Monitoring as a Barrier to the Availability and Accessibility of Open Access Data on the Tidal Thames

Open Access data plays an increasingly important role in discussions of environmental issues. Limited availability or poor quality data can impede citizen participation in environmental dialogue, leading to their voices being undermined. This study assesses the quality of Open Access environmental data and barriers to its accessibility in the Thames Estuary. Data quality is assessed by its ability to track long-term trends in temperature, salinity, turbidity, and dissolved oxygen. The inconsistencies found in the data required analyses and careful interpretation beyond what would be expected of a citizen. The lack of clear documentation and centralized database acted as a major barrier to usability. A set of recommendations are produced for estuarine monitoring, including defining minimum standards for metadata, creating a centralized database for better quality control and accessibility, and developing flexible monitoring protocols that can incorporate new hypotheses and partnerships. The goal of the recommendations is to create monitoring which can encourage better science and wider participation in the natural environment.

Performance Verification of a Flexible Vibration Monitoring System

The performance of measurement or manufacturing systems in high-precision applications is dependent upon the dynamics of the system, as vibration can be a significant contributor to the measurement uncertainty and process variability. Technologies making use of accelerometers and laser vibrometers are available to rapidly measure and process structural dynamic data but the software infrastructure is yet to be available in an open source or standardised format to allow rapid inter-platform use. In this paper, we present a novel condition monitoring system, which uses commercially available accelerometers in combination with a control-monitoring infrastructure to allow for the appraisal of the performance of a measurement or manufacturing system. A field-programmable gate array (FPGA)-based control system is implemented for high-speed data acquisition and signal processing of six triaxial accelerometers, with a frequency range of 1 Hz to 6000 Hz, a sensitivity of 102.5 mV/ms−2 and a maximum sample rate of 12,800 samples per second per channel. The system includes two methods of operation: real-time performance monitoring and detailed measurement/manufacturing verification. A lathe condition monitoring investigation is undertaken to demonstrate the utility of this system and acquire typical machining performance parameters in order to monitor the “health” of the system.

Choosing the optimal frequency of water quality monitoring on tributaries of a lowland reservoir

Water quality monitoring networks typically involve field measurements with time resolution ranging from daily or several times a week to just several times a year. This time step directly affects the reliability of any related calculations. We addressed the issue of setting the optimal monitoring frequency for different practical and research purposes. It is shown that monthly or even seasonal observations can be sufficient to estimate the annual chemical yield of a river, but to better describe the seasonal dynamics of the chemical flow it is necessary to increase the sampling frequency to at least twice per month. To explore the relationship between the water discharge and chemistry and to improve the model calculations dependent on chemical input it is necessary to establish the most detailed observation framework covering all key points of a yearly hydrograph. Regardless of specific objectives, it is recommended to always set flexible monitoring dates in accordance with the rivers flow regime.

Dynamic Contracting with Flexible Monitoring

We study a principal's joint design of optimal monitoring and compensation schemes to incentivize an agent by incorporating information design into a dynamic contracting framework. The principal can flexibly allocate her limited monitoring capacity between seeking evidence that confirms or contradicts the agent's effort, as the basis for reward or punishment. When the agent's continuation value is low, the principal seeks only confirmatory evidence. When it exceeds a threshold, the principal seeks mainly contradictory evidence. Importantly, the agent's effort is perpetuated if and only if he is sufficiently productive and the principal has enough flexibility in allocating monitoring capacity.

The Research on Key Technologies of Power Quality Comprehensive Control in Complex Distribution Network

As new types of power sources and loads such as distributed photovoltaic and electric vehicle charging facilities are connected to the distribution network, the distribution network has become more variable and complex, and the simple distribution network has evolved into a complex distribution network. The access of new elements, especially the application of power electronic devices, has a great impact on the power quality of the distribution network. The technical framework of power quality comprehensive management of complex distribution network is proposed, and the corresponding technical route is put forward from three aspects: the influence of power electronic equipment application on power quality of distribution network, power electronic equipment modeling of distribution network, flexible monitoring of power quality and rapid control.

Self-Service Cybersecurity Monitoring as Enabler for DevSecOps

Current IoT systems are highly distributed systems that integrate cloud , edge , and fog computing approaches depending on where intelligence and processing capabilities are allocated. This distribution and heterogeneity make development and deployment pipelines very complex and fragmented with multiple delivery endpoints above hardware. This fact prevents rapid development and makes the operation and monitoring of production systems a difficult and tedious task, including cybersecurity event monitoring. The DevSecOps can be defined as a cultural approach to improve and accelerate the delivery of business value by making dev/sec/ops teams’ collaboration effective. This paper focuses on self-service cybersecurity monitoring as an enabler to introduce security practices in a DevOps environment. To that end, we have defined and formalized an activity that supports ‘ Fast and Continuous Feedback from Ops to Dev ’ by providing a flexible monitoring infrastructure so that teams can configure their monitoring and alerting services according to their criteria ( you build, you run, and now you monitor ) to obtain fast and continuous feedback from the operation and thus, better anticipate problems when a production deployment is performed. This activity has been formalized using the Software & Systems Process Engineering Metamodel by OMG and its instantiation is described through a case study that shows the versioned and repeatable configuration of a cybersecurity monitoring infrastructure ( Monitoring as Code ) through virtualization and containerization technology. This self-service monitoring/alerting allows breaking silos between dev, ops, and sec teams by opening access to key security metrics, which enables a sharing culture and continuous improvement.

FlexMonitor: A Flexible Monitoring Framework in SDN

Efficient network monitoring is an important basis work for network management. Generally, many management applications require accurate and timely statistics about network states at different aggregation levels at low cost, such as malicious traffic detection, traffic engineering, etc. Moreover, the network environment to be monitored is constantly changing and expanding, including not only the data center for cloud computing but also the Internet of Things (IoT) for smart urban sensing, which requires the intensive study of more fine-grained network monitoring. As is well known, the development of efficient network monitoring approaches greatly relies on a flexible monitoring framework. Software defined network (SDN) can provide dramatic advantages for network management by separating the control plane and data plane. Therefore, it is a good choice to design a flexible monitoring framework based on the advantages of SDN. However, most research works only take advantage of the centralized control feature in SDN, which leads to limited improvement in the flexibility of the monitoring framework. This paper proposes a flexible monitoring framework named FlexMonitor, which can realize greater flexibility based on not only the centralized control feature, but also the high programmability in the controller and the limited programmability in the openflow switches in SDN. There are two key parts in FlexMonitor, namely the monitoring strategy deployment part and the monitoring data collection part, which can enrich the deployment methods of monitoring strategies and increase the kinds of monitoring data sources, respectively. Based on the NetMagic platform, this monitoring framework was implemented and evaluated through realizing a distributed denial of service (DDoS) detection approach. The experimental results show that the proposed DDoS detection approach has a better detection performance compared with other related approaches as well as indirectly show that FlexMonitor can flexibly support a variety of efficient monitoring approaches.

Ultrahigh Sensitivity to Strain of Cracked Thin Films Based on Metallic Nanoparticles in a Dielectric Matrix

Platinum nanoparticle-based strain gauges are elaborated by means of atomic layer deposition on flexible polyimide substrates. Their electromechanical response is tested under mechanical bending at strain levels up to 1. Sudden changes in electrical resistance are observed above 0.6 strain when straight cracks are formed in the nanostructured thin film. Scanning electron microscope (SEM) experiments reveal that these cracks are preferentially formed next to the interface with aluminum top electrodes. After crack formation, a giant gauge factor of 2 104 is measured at a strain level of 0.3. This high sensitivity to strain is attributed to the gradual opening (or closing) of the cracks when mechanical strain is applied. Finally, we demonstrate the feasibility of a flexible heart rate monitor, which integrates a cracked Pt nanoparticle-based strain gauge.

Compact and Low-Cost Fluorescence Based Flow-Through Analyzer for Early-Stage Classification of Potentially Toxic Algae and in Situ Semiquantification.

The occurrence and intensity of (harmful) algal blooms (HABs) have increased through the years due to rapidly changing environmental conditions. At the same time, the demand for low-cost instrumentation has increased substantially, enabling the real-time monitoring and early-stage detection of HABs. To meet this challenge, we have developed a compact multi-wavelength fluorometer for less than 400 USD. This is possible by using readily available and low-cost optical and electronic components. Its modular design results in a highly versatile and flexible monitoring tool. The algae detection module enables a continuous identification and control of relevant algal groups based on their spectral characteristics with a detection limit of 10 cells per liter. Besides its usage as a benchtop module in the laboratory, the algae module has been integrated into submersible housings and applied in coastal environments. During its first in situ application in the Port of Genoa, seawater samples of mixed algal composition were used to demonstrate the successful discrimination of cyanobacteria and dinophytes as well-known toxin producing classes. Fabrication, operation, and performance as well as its first in situ application are addressed.

Multi-domain SDN controller federation in hybrid FiWi-MANET networks

Traditionally, mobile ad hoc networks (MANET) and hybrid optical-wireless networks, also known as fiber-wireless (FiWi), have been considered disjointly and independently, with no synergic management solutions. The former has primarily focused on dispatching packets among mobile nodes in infrastructure-less and very dynamic environments, the latter on offering high-bandwidth and low-latency access to cellular-equipped mobile nodes. The recent advancements and penetration of software-defined networking (SDN) techniques have stimulated the adoption of SDN-based flexible monitoring and control also for the MANET and FiWi domains. In this perspective, the paper originally proposes a model and an architecture that loosely federate MANET and FiWi domains based on the interaction of MANET and FiWi controllers: the primary idea is that our MANET and FiWi federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of packet management over hybrid FiWi-MANET networks. Our model is applied to several relevant use cases to practically point out the benefits of the proposal in terms of both load balancing and fairness improvements.

Initiating an Online Reputation Monitoring System with Open Source Analytics Tools

Online reputation is an invaluable asset for modern organizations as it can help in business performance especially in sales and profit. However, if we are not aware of our reputation, it is difficult to maintain it. Thus, social media analytics is a new tool that can provide online reputation monitoring in various ways such as sentiment analysis. As a result, numerous large-scale organizations have implemented Online Reputation Monitoring (ORM) systems. However, this solution is not supposed to be exclusively for high-income organizations, as many organizations regardless sizes and types are now online. This research attempts to propose an affordable and reliable ORM system using combination of open source analytics tools for both novice practitioners and academicians. We also evaluate its prediction accuracy and we discovered that the system provides acceptable predictions (sixty percent accuracy) and demonstrate a tally prediction of major polarity by human annotation. The proposed system can help in supporting business decisions with flexible monitoring strategies especially for organization that want to initiate and administrate ORM themselves at low cost.

Social equity and urban nature conservation

AbstractNature conservation and social equity issues have been approached in a myriad of ways by conservation, humanitarian, and development practitioners. The rapid and shifting urbanization of the globe makes the interaction of these issues paramount and it is imperative to articulate pathways to harmonizing these relationships readily followed by conservation practitioners. We describe the processes and compare the resulting social equity and conservation objectives of two initiatives purposefully integrating these approaches. A private nonprofit seeking to develop an urban conservation program in the Atlanta metropolitan area purposefully engaged residents from surrounding communities and self‐identified local and sector leaders to identify communities where social equity and conservation objectives could be created together. A public agency, built on a century‐long history of environmental stewardship for migratory birds and pollinators, integrated 20 years of participatory action research to engage the surrounding communities using methods suggested and developed by the communities themselves. In both cases, community‐based research approaches have helped establish cocreated objectives and flexible monitoring and evaluation baselines. Both initiatives found a need to appropriately resource and train staff to remain open to learning and evolving new objectives as additional perspectives emerge and the impact on conservation and equity objectives is assessed.

Routing Algorithm with Virtual Topology Toward to Huge Numbers of LEO Mobile Satellite Network Based on SDN

SDN network is a dynamic, controllable, cost-effective and adaptable system. It is suitable for communication networks with high bandwidth and high dynamic characteristics. Therefore, combining SDN ideas with the new generation of LEO satellite networks can achieve more flexible monitoring and management of the network, and can make the network expansion more convenient. Joint the Depth-First-Search (DFS) idea and Dijkstra algorithm for the huge numbers of LEO mobile satellite network based on SDN is proposed to improve the computational efficiency and the reliability of calculation result. Moreover, the communication performance of space-based network based on SDN and traditional space-based network is compared and analyzed. The simulation results show that the huge numbers of LEO mobile satellite network based on SDN breaks through the performance limitations of the traditional network architecture, and it can achieve better performance of the network.

A Scalable and Flexible Monitoring System Framework for Supercomputers

Mankind’s demand for more powerful computing capabilities is never met, which has led to the continuous improvement of supercomputers’ performance. A more powerful supercomputer tends to have a larger system scale, which brings serious challenges to the system management, within which how to monitor the system’s state is a critical problem. To address this problem, a scalable and flexible monitoring system framework for supercomputers is brought forward in this paper which can monitor supercomputers with tens of thousands of nodes effectively and efficiently. In this paper, we firstly give an overview of the framework and then focus on the Super Computer System Description Language (SCSDL) which is key to the framework. In the end, we explain some techniques about implementing the framework, and the client GUIs of a job monitoring system and an error monitoring system for Tianhe-2 based on this framework are given, from which we can see that the framework is well scalable and flexible to monitor Tianhe-2 which has 16,000 nodes effectively and efficiently.

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe.

BackgroundThe wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries.ObjectiveIn this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system.MethodsInfluenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone.ResultsIn summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time.ConclusionsResults from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.

Assessment of relationship between rainfall and Escherichia coli in clams (Chamelea gallina) using the Bayes Factor.

Consumption of bivalve shellfish harvested from water contaminated with sewage pollution presents a risk of human infections and targeting control measures require a good understanding of environmental factors influencing the transport and the fate of faecal contaminants within the hydrological catchments. Although there has been extensive development of regression models, the point of this paper, focused on the relationship between rainfall events and concentrations of Escherichia coli monitored in clams, was the use of a Bayesian approach, by the Bayes Factor. The study was conducted on clams harvested from the south coast of Marche Region (Italy), a coastal area impacted by continuous treated effluents, intermittent rainfalldependent untreated sewage spillage - as a consequence of stormwater overflowing - and rivers with an ephemeral flow regime. The work compared the different interpretation criteria of Bayes Factor, confirmed that E. coli concentrations in clams from the studied area varied in correlation with rainfall events, and demonstrated the effectiveness of Bayes Factor in the assessment of shellfish quality in coastal marine waters. However, it suggested that further investigations would be warranted to determine which environmental factors provide the better basis for accurate and timely predictions. Furthermore the gathered data could be useful, to the local authorities of Marche Region, in the definition of flexible monitoring programmes, taking into account the atmospheric events that could affect the correct functioning of sewage managing systems and the flow of tributary rivers.