Sensor Web Research Articles

Linked Data, Big Data, and the 4th Paradigm

Around 2006, the inception of Linked Data [2] has led to a realignment of the Semantic Web vision and the realization that data is not merely a way to evaluate our theoretical considerations, but a key research enabler in its own right that inspires novel theoretical and foundational research questions. Since then, Linked Data is growing rapidly and is altering research, governments, and industry. Simply put, Linked Data takes the World Wide Web’s ideas of global identifiers and links and applies them to (raw) data, not just documents. Moreover, and regularly highlighted by Tim Berners-Lee, Anybody can say Anything about Any topic (AAA)1 [1], which leads to a multi-thematic, multi-perspective, and multi-medial global data graph. More recently, Big Data has made its appearance in the shared mindset of researchers, practitioners, and funding agencies, driven by the awareness that concerted efforts are needed to address 21st century data collection, analysis, management, ownership, and privacy issues. While there is no generally agreed understanding of what exactly is (or more importantly, what is not) Big Data, an increasing number of V’s has been used to characterize different dimensions and challenges of Big Data: volume, velocity, variety, value, and veracity. Interestingly, different (scientific) disciplines highlight certain dimensions and neglect others. For instance, super computing seems to be mostly interested in the volume dimension while researchers working on sensor webs and the internet of things seem to push on the velocity front. The social sciences and humanities, in contrast, are more interested in value and veracity. As argued before [13,17], the variety dimensions seems to be the most intriguing one for the Semantic Web and the one where we can contribute-

Design and Implementation of Geospatial Sensor Web Information Public Service Platform

With the development of earth observation technologies, sensor type and quantity increase massively.In order to manage information and service resources related to Earth Observation Sensor Web efficiently, allow users access and apply these resources comprehensively and accurately, based on Sensor Web information model and service interface specifications, this paper designs and implements geospatial sensor web Information Public Service Platform, namely GeoSensor. GeoSensor is based on a service-oriented architecture, calls and combines sensor registration service, sensor observation service, real-time mapping service, satellite location-based service and other services, gets real-time sensor information, sensor observational data, data product and other information resources and demonstrates these information resources in the Map World with graphics, text, tables, and video vividly. GeoSensor mainly consists of four major functional modules:(i) Sensor Retrieval Module which is mainly used for retrieving motion sensors, in-situ sensors and remote sensors according to the specified filter criteria, such as time, space, subject and other conditions;(ii) Sensor Observational Data Retrieval Module is mainly used according to the specified filter conditions, access to various types of sensor observation data, and show these observational data in Map World in different ways;(iii) Sensor Control Module is mainly used to control in-situ sensors and video sensors, and feedback the result of sensor control based on these changes of the sensor observational data or the access method of sensor observational data; And(iv) Thematic Map Service is to use sensor observation data to generate thematic maps, and the data products generated by this service can reflect the overall situation within a specific area. GeoSensor achieves online search, instant access, network control and real-time mapping and other functions for these resources. In the future, a more powerful sensor web information public service platform with semantics will be build, which could be used in smart city.

A fuzzy control framework for wireless sensor networks

We present a novel framework that can be used to dynamically control the operation of sensors embedded in a Wireless Sensor Network (WSN). Fuzzy logic incorporating temporal reasoning is used as the basis of our framework, permitting WSNs to automatically adapt to their changing environment. This makes WSNs more responsive and potentially more energy efficient. A fuzzy rule based, object–oriented programming language for WSNs called fuzzy Sensor Web Language (fuzzy SWL) is implemented as the front end of our framework. A proof–of–concept field test with two rules incorporating air temperature, rainfall, and water level demonstrates the feasibility of our fuzzy control approach for environmental monitoring. A novel aspect of this research is the addition of time factors in fuzzy rules. Time factors permit the fuzzy control system to effectively adapt to changing environmental conditions.

Dynamic Evaluation and Visualisation of the Quality and Reliability of Sensor Data Sources

Before using remote data sources, or those from external organisations, it is important to establish if the source is fit for purpose. We have developed an approach to automatic sensor data annotation and visualisation that evaluates overall sensor network performance and data quality. The CSIRO’s South Esk hydrological sensor web combines data related to water management from five different organisations, which provides a suitable platform to explore the issues of reliability and uncertainty. An environmental gridded surface is generated based on the observations and evaluations of quality and reliability of the sensor node provider.

A Task Ontology Driven Approach for Live Geoprocessing in a Service‐Oriented Environment

AbstractIn a service‐oriented environment, Web geoprocessing services can provide geoprocessing functions for a variety of applications including Sensor Web. Connecting Sensor Web and geoprocessing services together shows great potentail to support live geoprocessing using real‐time data inputs. This article proposes a task ontology driven approach to live geoprocessing. The task in the ontology contains five aspects: task type, task priority, task constraints, task model, and task process. The use of the task ontology in driving live geoprocessing includes the following steps: (1) Task model generation, which generates a concrete process model to fulfill user demands; (2) Process model instantiation, which transforms the process model into an executable workflow; (3) Workflow execution: the workflow engine executes the workflow to generate value‐added data products using Sensor Web data as inputs. The approach not only helps create semantically correct connections between Sensor Web and Web geoprocessing services, but also provides sharable problem solving knowledge using process models. A prototype system, which leverages Web 2.0, Sensor Web, Semantic Web, and geoprocessing services, is developed to demonstrate the applicability of the approach.

Metadata Harvesting and Registration in a Geospatial Sensor Web Registry

AbstractA Sensor Web registry acts as a broker in a service‐oriented environment to publish and discover Sensor Web resources (e.g. sensors, sensor services, observations, and alerts). The Catalogue Service for the Web (CSW) developed by the Open Geospatial Consortium (OGC) defines a standard interface and protocol for publishing and discovering geospatial resources. This article adopts the CSW for the development of a Sensor Web registry. Metadata for Sensor Web resources are registered into the catalogue information model – the ebXML Registry Information Model (ebRIM). In the Sensor Web environment, sensor observations can be available in real‐time or near‐real‐time, and thus metadata registered in CSW need to be updated frequently. This article proposes an incremental harvesting approach, which can harvest the updated metadata efficiently. A prototypical implementation is provided to demonstrate the applicability of the approach.

Towards Data and Sensor Planning Service for Coupling Earth Science Models and Earth Observations

How to obtain sensor observation data easily and quickly is one of the challenging research areas in the Earth science community. Data and Sensor Planning Service aims to generate requirements on Earth observations data from which the geophysical products needed by Earth science models can derive. Then, the service discovers relevant data sources which meet these requirements, schedules data acquisition by ordering and retrieving data from these sources, and processes and returns the customized data which will be used in the Earth science models. In this general framework, Sensor Web Enablement specifications of Open Geospatial Consortium are implemented and integrated with other open Web geospatial data services seamlessly to access real or virtual Earth observation sensors. Additionally, an Ajax-enabled browser client is built to facilitate the standard sensor Web operations, user account management along with data acquisition. The prototype system is demonstrated to retrieve near real-time satellite observation data from Comprehensive Large Array-data Stewardship System through standard Web services, and also is applied in the bird migration model which uses climate data, vegetation data, as well as other remotely sensed and in-situ observation data to determine the bird migration routes and identify the possible resting areas.

A Watershed-Based Debris Flow Early Warning System Using Sensor Web Enabling Techniques in Heterogeneous Environments

Debris flow disasters have increased in Taiwan due to various environmental factors. These disasters often bring a lot of rock and mud, causing a threat to the lives and properties of residents in the affected areas. The weather is changeable due to more and more extreme rainfall events. A monitoring system is needed to provide early-warning of debris flow disasters to reduce the loss of life and property. The number of installed precipitation stations is not adequate for the current early-warning system. Rainfall patterns are greatly affected by the variation in the topography. Therefore, the current system cannot fully integrate basin-wide rainfall data and lacks information on spatial dependency between rainfall stations. This paper proposes a watershed-based debris flow early-warning system that applies the OGC SWE standards to design its architecture. The standardized data exchange mechanism is used to integrate and share heterogeneous monitoring resources. A hierarchical architecture is proposed to build a wide range of precipitation stations. The system presents high density debris-flow-prone area monitoring. We propose dependency aggregation and SWE integration schemes that enable the system to collect data from upriver under dependency relationship of debris-flow-prone streams and achieve automated early-warning of debris flows. We use the SWE open source provided by 52North to implement the proposed watershed-based debris flow early-warning system. We develop a simulator using real rainfall data in Taiwan to compare to the current system. The experimental results demonstrate that our system can improve the sensing data problem and efficiently advance the warnings issue time.

Where and When Should Sensors Move? Sampling Using the Expected Value of Information

In case of an environmental accident, initially available data are often insufficient for properly managing the situation. In this paper, new sensor observations are iteratively added to an initial sample by maximising the global expected value of information of the points for decision making. This is equivalent to minimizing the aggregated expected misclassification costs over the study area. The method considers measurement error and different costs for class omissions and false class commissions. Constraints imposed by a mobile sensor web are accounted for using cost distances to decide which sensor should move to the next sample location. The method is demonstrated using synthetic examples of static and dynamic phenomena. This allowed computation of the true misclassification costs and comparison with other sampling approaches. The probability of local contamination levels being above a given critical threshold were computed by indicator kriging. In the case of multiple sensors being relocated simultaneously, a genetic algorithm was used to find sets of suitable new measurement locations. Otherwise, all grid nodes were searched exhaustively, which is computationally demanding. In terms of true misclassification costs, the method outperformed random sampling and sampling based on minimisation of the kriging variance.

Integration of hydrological observations into a Spatial Data Infrastructure under a Sensor Web environment

Various sensors connected to the World Wide Web are used to obtain real-time hydrological observations. Thus, real-time management and utilization of such distributed in situ observations in the cyber-physical environment becomes possible. A Sensor Observation Service (SOS) chaining Web Feature Service (WFS) method is proposed to integrate geographical reference observation data collected by a hydrological Sensor Web into a virtual globe. This method hides the complexity of a series of information and service models in the Sensor Web realm to enable the integration of heterogeneous distributed hydrological data sources into a Spatial Data Infrastructure (SDI). The core components – a dynamic schema transformer and automatic information extractor – were designed and implemented. The SOS schema is matched to WFS schema that uses the schema transformer dynamically. The information extractor extracts and serves features automatically, conforming to standard SOS operations for observation retrieval and insertion. Feasibility experiments conducted on the Jinsha River tested this proposed method. Results show that the proposed approach allows the integration of SOS servers into legacy applications that have a higher degree of availability within many SDIs. However, this is accompanied with the drawback that only a limited part of the SOS functionality is available to clients.

Bridging the Semantic Sensor Web and Multimodal Human-Machine Interaction Using SCXML

This paper presents a novel approach to combine, process and enrich data from heterogeneous sensor networks, and, further, to semantically annotate the observations of the sensed world thus obtained and publish them on the future Semantic Sensor Web. The processing and systematic annotation of sensor data of diverse nature obtained from an ever growing number of different sources that are beginning to shape the Sensor Web is a challenging endeavour. Nevertheless, a similar challenge is inherent to the activity of Human-Machine Interface designers. In this field the SCXML language, based on the concept of Harel statecharts, is being proposed by the W3C as a central element in the design of multimodal interaction managers, which have to deal with information in different communication modalities, integrating and interpreting the user’s input, and coordinating the output among them. We propose extending the use of SCXML to deal also with sensor information, as this language has the capability to combine and process this information as it does with interaction information. SCXML can also coordinate external tools (based on RDF, OGC-SWE’s O&M and OWL) to generate semantic annotations of the knowledge obtained, shareable across applications. This approach can pave the way to develop rich context-aware applications. We illustrate the discussion with a smart-car scenario that we have developed, and present the main implementation details. Keywords: Sensor web, semantic sensor web, human-machine interaction, SCXML, sensor processing, information enrichment, semantic annotation, RDF, Sensor and Actuator Networks (SANs), Internet-of-Things (IoT)

Near real-time geoprocessing on the grid: A scalable approach to road traffic monitoring

The geospatial sensor web is set to revolutionise real-time geospatial applications by making up-to-date spatially and temporally referenced data relating to real-world phenomena ubiquitously available. The uptake of sensor web technologies is largely being driven by the recent introduction of the OpenGIS Sensor Web Enablement framework, a standardisation initiative that defines a set of web service interfaces and encodings to task and query geospatial sensors in near real time. However, live geospatial sensors are capable of producing vast quantities of data over a short time period, which presents a large, fluctuating and ongoing processing requirement that is difficult to adequately provide with the necessary computational resources. Grid computing appears to offer a promising solution to this problem but its usage thus far has primarily been restricted to processing static as opposed to real-time data sets. A new approach is presented in this work whereby geospatial data streams are processed on grid computing resources. This is achieved by submitting ongoing processing jobs to the grid that continually poll sensor data repositories using relevant OpenGIS standards. To evaluate this approach a road-traffic monitoring application was developed to process streams of GPS observations from a fleet of vehicles. Specifically, a Bayesian map-matching algorithm is performed that matches each GPS observation to a link on the road network. The results show that over 90% of observations were matched correctly and that the adopted approach is capable of achieving timely results for a linear time geoprocessing operation performed every 60 seconds. However, testing in a production grid environment highlighted some scalability and efficiency problems. Open Geospatial Consortium (OGC) data services were found to present an IO bottleneck and the adopted job submission method was found to be inefficient. Consequently, a number of recommendations are made regarding the grid job-scheduling mechanism, shortcomings in the OGC Web Processing Service specification and IO bottlenecks in OGC data services.

Design of Real-time Communication Adapter for Different Protocol Sensors in Sensor Web

A real-time communication adapter named SensorAdapter is designed to communicate between different protocols sensors and data service layer in Sensor Web. The adapter is extended and restructured based on SensorBus, an open source project raised by a German company called 52north. By structuring the receiving module and extending the proxies of sensors according to the communication protocols the sensors use, the adapter can receive sensing information detected by different protocols sensors simultaneously. The receiving module identifies a sensor and finds its corresponding proxy in SensorAdapter by sensor ID (SensorID), and then packages the sensing information to XMPP messages and sends them to XMPPServer by invoking the methods in its proxy. At last, an example of SOS is achieved to verify the effect of the adapter. DOI: http://dx.doi.org/10.11591/telkomnika.v10i5.1357

WYSIWYG GEOPROCESSING: COUPLING SENSOR WEB AND GEOPROCESSING SERVICES IN VIRTUAL GLOBES

Abstract. We propose to advance the scientific understanding and applications of geospatial data by coupling Sensor Web and Geoprocessing Services in Virtual Globes for higher-education teaching and research. The vision is the concept of "What You See is What You Get" geoprocessing, shortly known as WYSIWYG geoprocessing. Virtual Globes offer tremendous opportunities, such as providing a learning tool to help educational users and researchers digest global-scale geospatial information about the world, and acting as WYSIWYG platforms, where domain experts can see what their fingertips act in an interactive three-dimensional virtual environment. In the meantime, Sensor Web and Web Service technologies make a large amount of Earth observing sensors and geoprocessing functionalities easily accessible to educational users and researchers like their local resources. Coupling Sensor Web and geoprocessing Services in Virtual Globes will bring a virtual learning and research environment to the desktops of students and professors, empowering them with WYSIWYG geoprocessing capabilities. The implementation combines the visualization and communication power of Virtual Globes with the on-demand data collection and analysis functionalities of Sensor Web and geoprocessing services, to help students and researchers investigate various scientific problems in an environment with natural and intuitive user experiences. The work will contribute to the scientific and educational activities of geoinformatic communities in that they will have a platform that are easily accessible and help themselves perceive world space and perform live geoscientific processes.

Combining Cloud and sensors in a smart city environment

Abstract In the current worldwide ICT scenario, a constantly growing number of ever more powerful devices (smartphones, sensors, household appliances, RFID devices, etc.) join the Internet, significantly impacting the global traffic volume (data sharing, voice, multimedia, etc.) and foreshadowing a world of (more or less) smart devices, or “things” in the Internet of Things (IoT) perspective. Heterogeneous resources can be aggregated and abstracted according to tailored thing-like semantics, thus enabling Things as a Service paradigm, or better a “Cloud of Things”. In the Future Internet initiatives, sensor networks will assume even more of a crucial role, especially for making smarter cities. Smarter sensors will be the peripheral elements of a complex future ICT world. However, due to differences in the “appliances” being sensed, smart sensors are very heterogeneous in terms of communication technologies, sensing features and elaboration capabilities. This article intends to contribute to the design of a pervasive infrastructure where new generation services interact with the surrounding environment, thus creating new opportunities for contextualization and geo-awareness. The architecture proposal is based on Sensor Web Enablement standard specifications and makes use of the Contiki Operating System for accomplishing the IoT. Smart cities are assumed as the reference scenario.

SERVICE ORIENTED ARCHITECTURE FOR WIRELESS SENSOR NETWORKS IN AGRICULTURE

Abstract. Rapid advances in Wireless Sensor Network (WSN) for agricultural applications has provided a platform for better decision making for crop planning and management, particularly in precision agriculture aspects. Due to the ever-increasing spread of WSNs there is a need for standards, i.e. a set of specifications and encodings to bring multiple sensor networks on common platform. Distributed sensor systems when brought together can facilitate better decision making in agricultural domain. The Open Geospatial Consortium (OGC) through Sensor Web Enablement (SWE) provides guidelines for semantic and syntactic standardization of sensor networks. In this work two distributed sensing systems (Agrisens and FieldServer) were selected to implement OGC SWE standards through a Service Oriented Architecture (SOA) approach. Online interoperable data processing was developed through SWE components such as Sensor Model Language (SensorML) and Sensor Observation Service (SOS). An integrated web client was developed to visualize the sensor observations and measurements that enables the retrieval of crop water resources availability and requirements in a systematic manner for both the sensing devices. Further, the client has also the ability to operate in an interoperable manner with any other OGC standardized WSN systems. The study of WSN systems has shown that there is need to augment the operations / processing capabilities of SOS in order to understand about collected sensor data and implement the modelling services. Also, the very low cost availability of WSN systems in future, it is possible to implement the OGC standardized SWE framework for agricultural applications with open source software tools.

A HYBRID PULL-PUSH SYSTEM FOR NEAR REAL-TIME NOTIFICATIONS ON SENSOR WEB

Abstract. World-wide sensor web generates tremendous amount of sensor data stream allowing people to observe events that were previously unobservable. Sensor web has been wildly applied in many monitoring systems; some of them are extremely time-sensitive, e.g., disaster management systems. However, with the growing amount of sensor data, the traditional request/response communication model becomes inefficient as it is based on point-to-point pulling interactions between users and data providers. In order to address this issue, publish/subscribe communication model has been proposed and applied in many applications, e.g., web blogging. The publish/subscribe model utilizes an intermediary broker on matching predefined queries with the data pushed to the broker. However, we argue that the publish/subscribe model is hard to be directly applied to sensor web due to the fact that most sensor web services are based on pulling interaction model only. For instance, more and more sensor data providers are publishing their sensor data with the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS) standards, and the OGC SOS services are based on the request/response model. Therefore, in order to address this issue, we propose a hybrid pull-push system to retrieve sensor web data in a timely manner. The preliminary experimental results indicate that the proposed system is able to fetch near real time sensor streams from pull-based sensor web services.

SENSOR WEB SERVICES FOR EARLY FLOOD WARNINGS BASED ON SOIL MOISTURE PROFILES

Abstract. As result of improved computing and communication capabilities, the use of sensors and sensor networks for environmental monitoring has gained considerable importance in the recent years. For an interoperable integration of sensor data like sensor descriptions, sensor measurements and alarm events, the Open Geospatial Consortium (OGC) started the Sensor Web Enablement (SWE) initiative and proposed several specifications in respect to a geospatial sensor web. First implementations of SWE software frameworks are available. In this paper, we present the results of the recent WEBBOS project. Its objective was to build up a system for early flood warnings by measuring soil moisture profiles. The use of soil moisture profiles is motivated by the fact that traditional approaches like the observation of water gauges are suitable for the prediction of large-river flooding but not for smaller drainage areas. We describe the architecture of our system and how it is built up by using existing software components to a large extent. Our special focus is on the incorporation of 3D soil moisture profiles into the SWE data model, on the integration of the new OGC Sensor Event Service, and on the development of a flexible web client for mapping and other visualization purposes.

Precise Detection Technology

This paper mainly studies the application in the assembly line production by precision instruments and sensors, proposed the use of sensor technology and WEB technology to control lines on the transmission system. It can enhance the production of the compatibility between devices by real-time monitoring, so that each process can be more perfect articulation and reach to reduce the production cost for the entire production line monitoring.

GIScience Research at the Thirty‐second Annual Esri International User Conference

GIScience Research at the Thirty‐second Annual Esri International User Conference