Showing papers on "Sensor web published in 2017"

On Theoretical Modeling of Sensor Cloud: A Paradigm Shift From Wireless Sensor Network

Abstract: This paper focuses on the theoretical modeling of sensor cloud, which is one of the first attempts in this direction. We endeavor to theoretically characterize virtualization, which is a fundamental mechanism for operations within the sensor-cloud architecture. Existing related research works on sensor cloud have primarily focused on the ideology and the challenges that wireless sensor network (WSN)-based applications typically encounter. However, none of the works has addressed theoretical characterization and analysis, which can be used for building models for solving different problems to be encountered in using sensor cloud. We present a mathematical formulation of sensor cloud, which is very important for studying the behavior of WSN-based applications in the sensor-cloud platform. We also suggested a paradigm shift of technology from traditional WSNs to sensor-cloud architecture. A detailed analysis is made based on the performance metrics, i.e., energy consumption, fault tolerance, and lifetime of a sensor node. A thorough evaluation of the cost effectiveness of sensor cloud is also done by examining the cash inflow and outflow characteristics from the perspective of every actor of the sensor cloud. Analytical results show that the sensor-cloud architecture outperforms a traditional WSN, by increasing the sensor lifetime by 3.25% and decreasing the energy consumption by 36.68%. We also observe that the technology shift to sensor cloud reduces the expenditure of an end user by 14.72%, on average.

Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.

Abstract: Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

A Wearable Wireless Sensor Network for Indoor Smart Environment Monitoring in Safety Applications

Abstract: This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

Environment monitoring system for agricultural application based on wireless sensor network

Abstract: This paper proposes an Internet of Thing system architecture based on Wireless Sensor Network (WSN) for agricultural applications. The system consists of sensor nodes and a gateway, which allows a user to monitor environmental data for agriculture using a web browser. The sensor node is a microcontroller based Arduino including wireless module and connected sensors such as temperature, relative humidity, luminosity, air pressure and other sensors. A WiFi interface is deployed to exchange the environmental information from sensor nodes to the gateway running Linux. The gateway manages and transfers data to a Cloud where data were stored and visualized as graphs.

Development of ambient environmental monitoring system through wireless sensor network (WSN) using NodeMCU and “WSN monitoring”

Abstract: In this paper we have developed a system for web based environment monitoring using the WSN Technology. WSN sensor nodes transmit data to the cloud-based database via Web API request. Measured data can be monitored by the user anywhere from internet by using the Web Application which one is also compatible for mobile phones. If the data measured by sensor node exceeds the configured value range in Web Application, Web Application sends a warning e-mail to users for improving environmental conditions.

A Study of Machine Learning in Wireless Sensor Network

Abstract: Within this Paper, a concept of machine learning strategies suggested. In this investigation to address the design issues in WSNs is introduced. As can be viewed within this paper, countless endeavors have induced up to now; several layout issues in wireless sensor networks have been remedied employing numerous machine learning strategies. Utilizing machine learning based algorithms in WSNs need to deem numerous constraints, for instance, minimal sources of the network application that really needs distinct events to be tracked as well as other operational and non-operational aspects. Index Terms – Wireless Sensor Network, Machine Learning, Supervised Machine Learning, Unsupervised Machine Learning.

Automated Moving Object Classification in Wireless Multimedia Sensor Networks

Abstract: The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.

A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

Abstract: Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

Middleware for Plug and Play Integration of Heterogeneous Sensor Resources into the Sensor Web

Abstract: The study of global phenomena requires the combination of a considerable amount of data coming from different sources, acquired by different observation platforms and managed by institutions working in different scientific fields. Merging this data to provide extensive and complete data sets to monitor the long-term, global changes of our oceans is a major challenge. The data acquisition and data archival procedures usually vary significantly depending on the acquisition platform. This lack of standardization ultimately leads to information silos, preventing the data to be effectively shared across different scientific communities. In the past years, important steps have been taken in order to improve both standardization and interoperability, such as the Open Geospatial Consortium’s Sensor Web Enablement (SWE) framework. Within this framework, standardized models and interfaces to archive, access and visualize the data from heterogeneous sensor resources have been proposed. However, due to the wide variety of software and hardware architectures presented by marine sensors and marine observation platforms, there is still a lack of uniform procedures to integrate sensors into existing SWE-based data infrastructures. In this work, a framework aimed to enable sensor plug and play integration into existing SWE-based data infrastructures is presented. First, an analysis of the operations required to automatically identify, configure and operate a sensor are analysed. Then, the metadata required for these operations is structured in a standard way. Afterwards, a modular, plug and play, SWE-based acquisition chain is proposed. Finally different use cases for this framework are presented.

Internet of Things challenges

Abstract: The last years have been characterized by impressive growth of the Internet, and consequently by the increased number of users. This growth has been following the evolution of the Web, in the begin the web 1.0 known as web of information connections until the present day with the Web 4.0, the web of intelligence connections, and the fast development of wireless communication technologies, embedded sensors, real-time localization and wireless sensor networks (WSN), leading to the Internet of Things (IoT). IoT opens an unprecedented window of opportunity for organizations, creating new sources of value for the business, for those who are betting on improving their processes agility and data capabilities.

Intelligent sensor network

Abstract: A sensor network with multiple wireless communication channels and multiple sensors for surveillance is disclosed. The network may enable object detection, recognition, and tracking in a manner that balances low-power monitoring and on-demand high-speed data transferring.

Using big data analytics and IoT principles to keep an eye on underground infrastructure

Abstract: A Concept Development Study by the Open Geospatial Consortium (OGC) has highlighted the importance of high-quality feature data for underground urban infrastructure (UGI). Analysis of large survey datasets, including both visual and non-visual methods, is essential for creating and maintaining UGI geodata. Connecting hidden features with diverse, high-velocity sensing streams and realistic predictive models that effectively characterize them is key to lower construction costs, efficient infrastructure operation, sound disaster preparedness, and new smart city services. IoT principles that combine OGC geodata and Sensor Web observation standards may offer the best chance for working towards functional “digital twins” of such hidden infrastructure that are both cost effective and scalable with the increasing complexity and instrumentation of the underground built environment. Technical and policy challenges remain, however, before this can be achieved.

Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks

Abstract: Energy efficiency has always been a hot issue in wireless sensor networks. A lot of energy-efficient algorithms have been proposed to reduce energy consumption in traditional wireless sensor networks. With the emergence of software-defined networking, researchers have demonstrated the feasibility of software-defined networking over traditional wireless sensor networks. Thus, energy-efficient algorithms in software-defined wireless sensor networks have been studied. In this article, we propose an energy-efficient algorithm based on multi-energy-space in software-defined wireless sensor networks. First, we propose a novel architecture of software-defined wireless sensor networks according to current research on software-defined wireless sensor networks. Then, we introduce the concept of multi-energy-space which is based on the residual energy. Based on the novel architecture of software-defined wireless sensor networks and the concept of multi-energy-space, we give a detailed introduction of the main idea o...

An analytic Study of the Key Factors Influencing the Design and Routing Techniques of a Wireless Sensor Network

Abstract: A wireless sensor network contains various nodes having certain sensing, processing & communication capabilities. Actually they are multifunctional battery operated nodes called motes. These motes are small in size & battery constrained. They are operated by a power source. A wireless sensor network consists of a huge number of tiny sensor nodes which are deployed either randomly or according to some predefined distribution. The sensors nodes in a sensor network are cooperative among themselves having self-organizing ability. This ensures that a wireless network serves a wide variety of applications. Few of them are weather monitoring, health, security & military etc. As their applications are wide, this requires that sensors in a sensor network must play their role very efficiently. But, as discussed above, the sensor nodes have energy limitation. This limitation leads failure of nodes after certain round of communication. So, a sensor network suffers with sensors having energy limitations. Beside this, sensor nodes in a sensor network must fulfill connectivity & coverage requirements. In this paper, we have discussed various issues affecting the design of a wireless sensor network. This provides the readers various research issues in designing a wireless sensor network.

Energy-aware dynamic resource allocation in virtual sensor networks

Abstract: Sensor network virtualization enables the possibility of sharing common physical resources to multiple stakeholder applications. This paper focuses on addressing the dynamic adaptation of already assigned virtual sensor network resources to respond to time varying application demands. We propose an optimization framework that dynamically allocate applications into sensor nodes while accounting for the characteristics and limitations of the wireless sensor environment. It takes also into account the additional energy consumption related to activating new nodes and/or moving already active applications. Different objective functions related to the available energy in the nodes are analyzed. The proposed framework is evaluated by simulation considering realistic parameters from actual sensor nodes and deployed applications to assess the efficiency of the proposals.

GeoJModelBuilder: an open source geoprocessing workflow tool

Abstract: Scientific workflows have been commonly used in geospatial data analysis and Cyberinfrastructure. They allow distributed geoprocessing algorithms, models, data, and sensors to be chained together to support geospatial data analysis, and environmental monitoring, and integrated environmental modelling. This paper presents an open source geoprocessing workflow tool, GeoJModelBuilder. It leverages open standards, Sensor Web, geoprocessing commands and services, OpenMI-compliant models together. The implementation provides a flexible, reusable, interoperable, and user-friendly way for geoprocessing in an open environment.

SMART CITIES INTELLIGENCE SYSTEM (SMACiSYS) INTEGRATING SENSOR WEB WITH SPATIAL DATA INFRASTRUCTURES (SENSDI)

Abstract: The paper endeavours to enhance the Sensor Web with crucial geospatial analysis capabilities through integration with Spatial Data Infrastructure The objective is development of automated smart cities intelligence system (SMACiSYS) with sensor-web access (SENSDI) utilizing geomatics for sustainable societies There has been a need to develop automated integrated system to categorize events and issue information that reaches users directly At present, no web-enabled information system exists which can disseminate messages after events evaluation in real time Research work formalizes a notion of an integrated, independent, generalized, and automated geo-event analysing system making use of geo-spatial data under popular usage platform Integrating Sensor Web With Spatial Data Infrastructures (SENSDI) aims to extend SDIs with sensor web enablement, converging geospatial and built infrastructure, and implement test cases with sensor data and SDI The other benefit, conversely, is the expansion of spatial data infrastructure to utilize sensor web, dynamically and in real time for smart applications that smarter cities demand nowadays Hence, SENSDI augments existing smart cities platforms utilizing sensor web and spatial information achieved by coupling pairs of otherwise disjoint interfaces and APIs formulated by Open Geospatial Consortium (OGC) keeping entire platform open access and open source SENSDI is based on Geonode, QGIS and Java, that bind most of the functionalities of Internet, sensor web and nowadays Internet of Things superseding Internet of Sensors as well In a nutshell, the project delivers a generalized real-time accessible and analysable platform for sensing the environment and mapping the captured information for optimal decision-making and societal benefit

Universal parser for wireless sensor networks in industrial cyber physical production systems

Abstract: This work was developed in the context of European funded Project SelSus. Industrial clouds are heavily sensor based and Cloud Manufacturing Service frameworks are mostly grounded in the adoption of Internet of Things and Wireless Sensor Networks technologies. The SelSus framework combines both an Industrial Sensor Cloud and a Cyber Physical Production System. The Industrial Sensor Cloud supports the Cyber Physical Production System, by providing computational power, as well as internal coordination and control, and external access to realize intelligent monitoring and control. The SelSus framework combines embedded systems, networks, sensors and actuators and control algorithms in a seamless manner. Our goal is to have a Flexible Sensor Integration solution that allows rapid graphical development of interpreters of raw data packets in the Cloud and its deployment for embedded execution at the Wireless Sensor Network gateway level for automatic data acquisition. This paper describes such a technology and demonstrates its feasibility, where a match between a graphically developed interpreter and the received messages from the Wireless Sensor Network in US-ASCII is made, and the integration of such sensors is made into the system.

Standards-based Internet of Things sub-GHz environmental sensor networks

Abstract: In recent years there has been shift in the use of wireless sensor networks from standalone systems that use bespoke methods of communication and data transfer to systems that use Internet standards and can interact more directly with the Internet. This has allowed wireless sensor networks to become a key enabler of the Internet of Things; however, the same is not true for environmental sensor networks as the focus of most existing research into Internet of Things wireless sensor networks has been on 2.4 GHz designs for indoor, urban and agricultural applications. In these applications, power, Internet connectivity and physical access are less of a challenge when compared to a typical environmental sensor network. Environmental sensor networks are used for monitoring natural processes and are generally deployed in harsh, remote environments where these factors are more of a concern. Sub-GHz radios are commonly used for communication due to their increased range and desirable propagation characteristics. Unlike wireless sensor networks, environmental sensor networks have been slow to adopt Internet standards and have continued to rely on bespoke methods of communication and data transfer, keeping their usability low. This has impeded the adoption of environmental sensor networks for earth sciences research. This thesis investigates whether the Internet standards that have helped to make wireless sensor network an important part of the Internet of Things can be applied to sub-GHz environmental sensor networks. It is demonstrated that 6LoWPAN can successfully be used with an 868 MHz network in a series of real-world deployments in the Highlands of Scotland that collected usable earth science data and facilitated research in other fields. Additionally, the suitability of these standards for real-world networks is assessed in terms of energy, throughput and latency performance and compared to a theoretical 2.4 GHz network. An publicly available open source Contiki radio driver for the CC1120 was developed as part of this work. Additionally, timing parameters for using ContikiMAC with 868 MHz radios were determines and shared with researchers at other institutions, facilitating further research into sub-GHz IoT ESNs by other researchers.

Threats to security of Wireless Sensor Networks

Abstract: Wireless Sensor Networks provide an inexpensive and power efficient solution to a majority of real world problems. This solution, however, is provided at the cost of computing ability. Due to their perks, Wireless Sensor Networks have a bright future. However, Wireless Sensor Networks are prone to security issues and attacks. Providing effective solutions to these problems is a requirement in order to ensure that Wireless Sensor Networks continue to pave way for future innovations. This paper introduces the concept of Wireless Sensor Networks, while providing a brief overview of its origins and applications. The paper also discusses the security goals, threats, attacks and constraints associated with Wireless Sensor Networks.

Survey on Quality of Observation within Sensor Web Systems

Abstract: The Sensor Web vision refers to the addition of a middleware layer between sensors and applications. To bridge the gap between these two layers, Sensor Web systems must deal with heterogeneous sources, which produce heterogeneous observations of disparate quality. Managing such diversity at the application level can be complex and requires high levels of expertise from application developers. Moreover, as an information-centric system, any Sensor Web should provide support for Quality of Observation (QoO) requirements. In practice, however, only few Sensor Webs provide satisfying QoO support and are able to deliver high-quality observations to end consumers in a specific manner. This survey aims to study why and how observation quality should be addressed in Sensor Webs. It proposes three original contributions. First, it provides important insights into quality dimensions and proposes to use the QoO notion to deal with information quality within Sensor Webs. Second, it proposes a QoO-oriented review of 29 Sensor Web solutions developed between 2003 and 2016, as well as a custom taxonomy to characterise some of their features from a QoO perspective. Finally, it draws four major requirements required to build future adaptive and QoO-aware Sensor Web solutions.

Energy efficient data prediction model for the sensor cloud environment

Abstract: The sensors are used for many applications in the recent time. The sensors generally connect with each other wirelessly to form a Wireless Sensor Network (WSN). Cloud computing is an emerging technology where the end users pay and access the services without worried about the infrastructure. Sensor cloud combines sensor network with the cloud computing in which the end users can access to the sensor network through the cloud computing. Sensor cloud should be energy efficient as the battery life of the sensor is finite and huge amount of energy is consumed in the cloud computing environment to provide services to the end users. The users request to access the sensor through the cloud system redirects every time to the sensor network, which causes more transmission in the sensor network as a result more energy is consumed. In this paper, we have compared mainly the accuracy and time consumed by various prediction schemes using some activation functions. From our analysis, we found that the Rprop-algorithm using logistic activation function is suitable as it provides nearly 97.2 percentage accuracy within an admissible delay of 13 seconds. Our proposed sensor cloud model integrates Rprop-prediction scheme using the logistic activation function in cloud system which predicts future sensor data, such that users request are replied at cloud level which saves energy as number of transmissions are reduced in the sensor network.

NSensor – Wireless Sensor Network for Environmental Monitoring

Abstract: This paper reports the development and integration of a wireless sensor network for environmental monitoring. The main goals of this system include modularity, low power consumption and ease of expansion. The system includes three main elements: sensor nodes, gateways and a server. Each sensor node can only connect to a gateway, resulting in a star network layout. Data collected from the different sensor nodes is stored in a database within the server. A web-based user interface for this system was developed and made available online.

Wireless Smart Sensor Network System Using SmartBridge Sensor Nodes for Structural Health Monitoring of Existing Concrete Bridges

Abstract: There are over 8000 bridges in the Philippines today according to the Department of Public Works and Highways (DPWH). Currently, visual inspection is the most common practice in monitoring the structural integrity of bridges. However, visual inspections have proven to be insufficient in determining the actual health or condition of a bridge. Structural Health Monitoring (SHM) aims to give, in real-time, a diagnosis of the actual condition of the bridge. In this study, SmartBridge Sensor Nodes were installed on an existing concrete bridge with American Association of State Highway and Transportation Officials (AASHTO) Type IV Girders to gather vibration of the elements of the bridge. Also, standards on the effective installation of SmartBridge Sensor Nodes, such as location and orientation was determined. Acceleration readings from the sensor were then uploaded to a server, wherein they are monitored against certain thresholds, from which, the health of the bridge will be derived. Final output will be a portal or webpage wherein the information, health, and acceleration readings of the bridge will be available for viewing. With levels of access set for different types of users, the main users will have access to download data and reports. Data transmission and webpage access are available online, making the SHM system wireless.

2D coverage analysis of sensor networks with random node deployment

Abstract: In last few decades, as a result of the advances in microelectromechanical systems, Wireless Sensor Networks (WSNs) have gained a considerable attention due to their low-cost, low-power and small-scale sensor nodes which are used to integrate sensing, processing, communicating capabilities to solve many different real world problems. The placement of sensor nodes is a very important step to cover the theater of these application areas. Increasing the coverage of WSN system is one of the important research interests to determine the quality of service of the system. The location of sensor nodes can be determined by humans to increase the coverage area. However, in the remote or hostile environments, the random deployment of sensor nodes is needed to be used. In this paper, the different random deployment techniques have been studied, and the experimental results are obtained have been shared to show the effectiveness of these techniques. Finally, the alternative approaches are mentioned to guide the researchers, as well.

An interoperable approach for Sensor Web provenance

Abstract: The Sensor Web is evolving into a complex information space, where large volumes of sensor observation data are often consumed by complex applications. Provenance has become an important issue in the Sensor Web, since it allows applications to answer “what”, “when”, “where”, “who”, “why”, and “how” queries related to observations and consumption processes, which helps determine the usability and reliability of data products. This paper investigates characteristics and requirements of provenance in the Sensor Web and proposes an interoperable approach to building a provenance model for the Sensor Web. Our provenance model extends the W3C PROV Data Model with Sensor Web domain vocabularies. It is developed using Semantic Web technologies and thus allows provenance information of sensor observations to be exposed in the Web of Data using the Linked Data approach. A use case illustrates the applicability of the approach.