“…SWE-based middleware, on the other hand, establishes transparent communication between sensors and Web applications and incorporates a set of standard activities to discover, exchange, and process sensor data [ 46 ]. Several applications rely on standards such as SWE and device profile for Web Services to integrate sensors, but they fail to manage the context involved in publishing data to the Web in near real-time [ 18 , 47 , 48 , 49 , 50 , 51 ]. To mitigate this challenge, the message bus architecture Sensor Bus comprises a common communication infrastructure, a set of adaptable interfaces and a well-defined protocol and provides semantically-enabled sensor plug-and-play via an automatic mediation between semantic sensors and SWE standards [ 52 , 53 , 54 , 55 , 56 ].…”
The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications.
“…SWE-based middleware, on the other hand, establishes transparent communication between sensors and Web applications and incorporates a set of standard activities to discover, exchange, and process sensor data [ 46 ]. Several applications rely on standards such as SWE and device profile for Web Services to integrate sensors, but they fail to manage the context involved in publishing data to the Web in near real-time [ 18 , 47 , 48 , 49 , 50 , 51 ]. To mitigate this challenge, the message bus architecture Sensor Bus comprises a common communication infrastructure, a set of adaptable interfaces and a well-defined protocol and provides semantically-enabled sensor plug-and-play via an automatic mediation between semantic sensors and SWE standards [ 52 , 53 , 54 , 55 , 56 ].…”
The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications.
“…Nowadays solutions for embedded networks are typically tailored to specific use cases that come equipped with proprietary application protocols. Typically, to overcome the issues of interoperability between technologies and protocols, gateway architectures and device abstraction layers are developed [23]. This is not a practical solution on the long term for the following reasons: Firstly, the development of individual solutions for every single embedded network is too costly and time consuming.…”
Embedded network programming remains a highly complex task for developers since unique characteristics of such networks have to be faced: one of them is the communication between a diversity of resource constraint nodes. Another one is the infrastructure dynamics. The widely-used standardized Web service technologies would perfectly meet such unique characteristics and ease the development of applications. Such technologies that enable, e.g., requesting or subscribing service data, however, process usually plain XML documents which are not suitable for small embedded devices with very limited resources. This is due to XML's verbosity, its bandwidth usage, and its associated processing overhead. The paper addresses these issues and describes an innovative and optimized source code generation technique by means of W3C's Efficient XML Interchange (EXI) format for developing XML-based Web services for the embedded domain. This offers developers a seamless use of the wide-spread service protocols in the embedded domain as well. Evaluation results based on the dataset from the ISO/IEC standardization of the vehicle to grid communication interface (V2G CI) prove the applicability of the generated XMLbased Web services of restricted devices in terms of message size, performance, and code footprint.
“…Although several applications use service interfaces such as SWE standards and/or Devices Profile for Web Services (DPWS) to integrate dynamically sensors and applications, they still did not consider the high complexity involving Sensor Web (WANG et al, 2007;ZEEB et al, 2009;ABANGAR et al, 2010;PANANGADAN et al, 2012;HUANG, 2013).…”
This thesis is firstly dedicated to God that helps me in my way to this journey. To my parents, sister and all my family members, with their great affection and support, since they do not spare any effort to ensure that I got to this stage of my life. To all my friends and colleagues for the constant encouragement and support. And to all my professional colleagues, who were important in my academic life. with his valuable advice and giving me the opportunity to develop this project. I am very grateful to my supervisors, the Ph.D. candidates, MSc. Flávio Eduardo Aoki Horita and MSc. Livia Castro Degrossi, for guiding me to better results. I am sincerely thankful to all my colleagues of the AGORA Group 1 , for contributing with their feedbacks, time and efforts in order to improve the results of the project.
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