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Integrating Statistical Machine Learning in a semantic sensor web for Proactive Monitoring and Control

sensorS 2017年第4期17卷 807-807页

作者： Adeleke, Jude Adekunle Moodley, Deshendran Rens, Gavin Adewumi, Aderemi Oluyinka Univ KwaZulu Natal Sch Math Stat & Comp Sci Westville CampusUniv Rd ZA-3629 Durban South Africa CSIR Meraka Ctr Artificial Intelligence Res CAIR Meiring Naude Rd ZA-0001 Pretoria South Africa Univ Cape Town Dept Comp Sci 18 Univ Ave ZA-7701 Rondebosch South Africa Natl Space Res & Dev Agcy Obasanjo Space Ctr Airport Rd Abuja 900107 Nigeria

Proactive monitoring and control of our natural and built environments is important in various application scenarios. semantic sensor web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a semantic sensor web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM2.5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM2.5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of semantic sensor web.

关键词： proactive semantic sensor web stream reasoning situation prediction machine learning sliding window multilayer perceptron

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Development of semantic sensor web For Monitoring Environment Conditions

Development of Semantic Sensor Web For Monitoring Environmen...

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International Seminar on Intelligent Technology and Its Applications (ISITIA) - Recent Trends in Intelligent Computational Technologies for Sustainable Energy

作者： Al Rasyid, M. Udin Harun Sayfudin, Achmad Basofi, Arif Sudarsono, Amang PENS Surabaya Indonesia

ISBN: (纸本)9781509017096

The semantic sensor web (SSW) is a combination of sensor networks, web services, database and semantic web technologies. The SSW describes sensor data with spatial, temporal, and thematic semantic metadata. One of the challenges for sensor web application is the integration and fusion of data coming from autonomously deployed sensor network. Gas sensor technology is one of the wireless sensor network (WSN), which has a wide range of sensors that can be used to monitor the concentration of gas in a region. This paper implements SSW with existing gas sensor to perform readings from the environment, store it into a database and provide services application program interface (API) data. sensor data used in this study are temperature, CO, CO2 and Humidity sensor. The method we use is to build a semantic web to connect the sensor data that is spread by harnessing service API on the sensor semantic web servers interconnected. Furthermore, the data retrieved from the sensors will be represented in the form of ontology with RDF/OWL typeand stored into RDF Repository (OPENRDF-SESAME) in order to be processed and published to the semantic web service. SPARQL library and curl serves to bridge the gap between service and Apache Tomcat. Existing data in the RDF Triple Store file will be displayed to the user to utilize the service using standard API RESTFUL. Then the existing data in the RDF database is displayed in a JSON data format.

关键词： Wireless sensor Network semantic web web Service Gas sensor semantic sensor web

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A Ubiquitous sensor Network Platform for Integrating Smart Devices into the semantic sensor web

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sensorS 2014年第6期14卷 10725-10752页

作者： Diaz Pardo de Vera, David Sigueenza Izquierdo, Alvaro Bernat Vercher, Jesus Hernandez Gomez, Luis Alfonso Univ Politecn Madrid GAPS SSR ETSI Telecomunicac E-28040 Madrid Spain Telefon I D Madrid 28050 Spain

Ongoing sensor web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous sensor Network (USN) Platform that embeds several OGC (R) sensor web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to semantic sensor web principles and technologies, so that smart devices can access sensor web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the semantic sensor web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs.

关键词： sensor web semantic sensor web smart devices Telco Platform Ubiquitous sensor Networks next-generation networks

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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm

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INTERNET TECHNOLOGY LETTERS 2024年第4期7卷

作者： Haroon, P. S. Abdul Lateef Patil, Sujata N. Divakarachari, Parameshachari Bidare Falkowski-Gilski, Przemyslaw Rafeeq, M. D. Ballari Inst Technol & Management Dept Elect & Commun Engn Ballari India Thomas Jefferson Univ Radiat Oncol Dept Pathol Lab Philadelphia PA USA Nitte Meenakshi Inst Technol Dept Elect & Commun Engn Bengaluru 560064 India Gdansk Univ Technol Fac Elect Telecommun & Informat Gdansk Poland CMR Engn Coll Dept Comp Sci & Engn Kandlakoya India

It is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer to ontology matching problems. This research focuses on a method for optimizing ontology alignment that employs BSO. A novel method for effectively controlling memory use and striking a balance between algorithm exploration and exploitation is proposed: the Simulated Annealing-based Beetle Swarm Optimisation Algorithm (SA-BSO). Utilizing Gray code for solution encoding, two compact operators for exploitation and exploration, and Probability Vectors (PVs) for swarming choosing exploitation and exploration, SA-BSO combines simulated annealing with the beetle search process. Through inter-swarm communication in every generation, SA-BSO improves search efficiency in addressing sensor ontology matching. Three pairs of real sensor ontologies and the Conference track were used in the study to assess SA-BSO's efficacy. Statistics show that SA-BSO-based ontology matching successfully aligns sensor ontologies and other general ontologies, particularly in conference planning scenarios.

关键词： beetle swarm optimization ontology probability vectors semantic sensor web simulated annealing

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Towards a semantic sensor spectral data framework: a case for in-situ water spectroradiometry 7

Towards a semantic sensor spectral data framework: a case fo...

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2024 Congress of Argentina

作者： Roda, Fernando Zader, Pablo Tropper, Ivanna Nemina, Francisco Rubio, Jorge Scavuzzo, Marcelo Ferral, Anabella CONICET CONAE Inst Mario Gulich CIFASIS Cordoba Argentina CONAE Inst Mario Gulich Cordoba Argentina CONAE GVT Caba Argentina CONAE Inst Mario Gulich Caba Argentina Consejo Nacl Invest Cient & Tecn Inst Mario Gulich Cordoba Argentina

ISBN: (纸本)9798350365948;9798350365931

Spectral data are crucial for optical remote sensing, serving to calibrate and validate satellite data, as well as to generate models for biophysical and geophysical variables. This data, essential for the growing field of hyperspectral geospatial data from sensors like PRISMA, enMAP, and PACE, can be sourced from in-situ measurements, laboratory data, and radiative transfer models. However, without a systematic way for data annotation and sharing, the valuable data generated by different observation missions remain isolated in data silos with few chances to be reused by others stakeholders. In this paper, we present an application ontology for managing observation data considering the full pipeline of the underlying measurement campaigns. The ontology is proposed as a key part of a semantic sensor web (SSW) platform for FAIR-complaint data sharing. The proposal is based on the semantic sensor Network (SSN) ontology and meets World Wide web Consortium (W3C) and Open Geospatial Consortium (OGC) standards like sensorML, O&M or GeoSPARQL. The presented approach is envisioned to support others observational projects beyond water quality, encompassing vegetation, minerals, and snow, among others, for various spectral data sources.

关键词： Spectral data semantic sensor web SSN Radiometry Applied Ontology

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Ontology Alignment Architecture for semantic sensor web Integration

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sensorS 2013年第9期13卷 12581-12604页

作者： Fernandez, Susel Marsa-Maestre, Ivan Velasco, Juan R. Alarcos, Bernardo Univ Alcala Dept Comp Engn Super Polytech Sch Madrid 28805 Spain

sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic web technologies are becoming closely related with sensor networks. The linking of elements from semantic web technologies with sensor networks has been called semantic sensor web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the semantic sensor web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

关键词： semantic sensor web ontology alignment fuzzy logic

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Integration of semantics Into sensor Data for the IoT: A Systematic Literature Review

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INTERNATIONAL JOURNAL ON semantic web AND INFORMATION SYSTEMS 2020年第4期16卷 1-25页

作者： Sejdiu, Besmir Ismaili, Florije Ahmedi, Lule South East European Univ Fac Contemporary Sci & Technol Tetovo North Macedonia Univ Prishtina Fac Elect & Comp Engn Pristina Kosovo

The internet of things (IoT) as an evolving technology represents an active scientific research field in recognizing research challenges associated with its application in various domains, ranging from consumer convenience, smart energy, and resource saving to IoT enterprises. sensors are crucial components of IoT that relay the collected data in the form of the data stream for further processing. Interoperability of various connected digital resources is a key challenge in IoT environments. The enrichment of raw sensor data with semantic annotations using concept definitions from ontologies enables more expressive data representation that supports knowledge discovery. In this paper, a systematic review of integration of semantics into sensor data for the IoT is provided. The conducted review is focused on analyzing the main solutions of adding semantic annotations to the sensor data, standards that enable all types of sensor data via the web, existing models of stream data annotation, and the IoT trend domains that use semantics.

关键词： Data Stream Annotation Internet of Things (IoT) semantic Annotation semantic sensor web sensor web Standards Systematic Literature Review

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Enabling Query Technologies for the semantic sensor web

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INTERNATIONAL JOURNAL ON semantic web AND INFORMATION SYSTEMS 2012年第1期8卷 43-63页

作者： Calbimonte, Jean-Paul Jeung, Hoyoung Corcho, Oscar Aberer, Karl Univ Politecn Madrid Fac Informat Dept Artificial Intelligence E-28040 Madrid Spain Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland

sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this data, for other purposes than those for which they were originally set up. The authors propose an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. In this article, the authors describe the theoretical foundations and technologies that enable exposing semantically enriched sensor metadata, and querying sensor observations through SPARQL extensions, using query rewriting and data translation techniques according to mapping languages, and managing both pull and push delivery modes.

关键词： Query Processing semantic sensor web semantic web sensor Networks sensor Technologies

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A Core Ontological Model for semantic sensor web Infrastructures

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INTERNATIONAL JOURNAL ON semantic web AND INFORMATION SYSTEMS 2012年第1期8卷 22-42页

作者： Garcia-Castro, Raul Corcho, Oscar Hill, Chris Univ Politecn Madrid Ontol Engn Grp E-28040 Madrid Spain Univ Politecn Madrid Fac Informat Dept Inteligencia Artificial E-28040 Madrid Spain Univ Southampton GeoData Inst Interdisciplinary Res Grp Southampton SO9 5NH Hants England

semantic sensor web infrastructures use ontology-based models to represent the data that they manage;however, up to now, these ontological models do not allow representing all the characteristics of distributed, heterogeneous, and web-accessible sensor data. This paper describes a core ontological model for semantic sensor web infrastructures that covers these characteristics and that has been built with a focus on reusability. This ontological model is composed of different modules that deal, on the one hand, with infrastructure data and, on the other hand, with data from a specific domain, that is, the coastal flood emergency planning domain. The paper also presents a set of guidelines, followed during the ontological model development, to satisfy a common set of requirements related to modelling domain-specific features of interest and properties. In addition, the paper includes the results obtained after an exhaustive evaluation of the developed ontologies along different aspects (i.e., vocabulary, syntax, structure, semantics, representation, and context).

关键词： Flood Emergency Planning Ontology Ontology Evaluation semantic sensor Network Ontology semantic sensor web sensor

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Sharing Human-Generated Observations by Integrating HMI and the semantic sensor web

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sensorS 2012年第5期12卷 6307-6330页

作者： Sigueenza, Alvaro Diaz-Pardo, David Bernat, Jesus Vancea, Vasile Luis Blanco, Jose Conejero, David Hernandez Gomez, Luis Univ Complutense Madrid ETSI Telecomunicac E-28040 Madrid Spain Telefon Invest & Desarrollo Madrid 28050 Spain

Current "Internet of Things" concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and semantic sensor web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and sensor web initiatives: the W3C's Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) sensor web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers' observations about the traffic or their environment are shared across the semantic sensor web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, sensor web and semantic web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound.

关键词： connected objects connected cars human-generated observations Human-Machine Interaction sensor web semantic sensor web

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