Showing papers on "Sensor web published in 2020"

A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks

Abstract: Internet of Things (IoT) has advanced its pervasiveness across the globe for the development of smart networks. It is aimed to deploy network edge that enables smart services and computation for the IoT devices. In addition, this deployment would not only improve the user experience but also provide service resiliency in case of any catastrophes. In IoT applications, the edge computing exploits distributed architecture and closeness of end-users to provide faster response and better quality of service. However, the security concern is majorly addressed to resist the vulnerability of attacks (VoA). Existing methodologies deal only with static wireless sensor web to deduce the intrusions in which the sensor nodes are deployed in a uniform manner to retain the constancy. Since the sensor nodes are constantly being in question through different transmission regions with several levels of velocities, selection of sensor monitoring nodes or guard nodes has become a challenging job in recent research. In addition, the adversaries are also moving from one location to another to explore its specific chores around the network. Thus, to provide flexible security, we propose a secure routing and monitoring protocol with multi-variant tuples using Two-Fish (TF) symmetric key approach to discover and prevent the adversaries in the global sensor network. The proposed approach is designed on the basis of the Authentication and Encryption Model (ATE). Using Eligibility Weight Function (EWF), the sensor guard nodes are selected and it is hidden with the help of complex symmetric key approach. A secure hybrid routing protocol is chosen to be built by inheriting the properties of both Multipath Optimized Link State Routing (OLSR) and Ad hoc On-Demand Multipath Distance Vector (AOMDV) protocols. The result of the proposed approach is shown that it has a high percentage of monitoring nodes in comparison with the existing routing schemes. Moreover, the proposed routing mechanism is resilient to multiple mobile adversaries; and hence it ensures multipath delivery.

An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards-Case Study: Workplace Reopening.

Abstract: To safely protect workplaces and the workforce during and after the COVID-19 pandemic, a scalable integrated sensing solution is required in order to offer real-time situational awareness and early warnings for decision-makers. However, an information-based solution for industry reopening is ineffective when the necessary operational information is locked up in disparate real-time data silos. There is a lot of ongoing effort to combat the COVID-19 pandemic using different combinations of low-cost, location-based contact tracing, and sensing technologies. These ad hoc Internet of Things (IoT) solutions for COVID-19 were developed using different data models and protocols without an interoperable way to interconnect these heterogeneous systems and exchange data on people and place interactions. This research aims to design and develop an interoperable Internet of COVID-19 Things (IoCT) architecture that is able to exchange, aggregate, and reuse disparate IoT sensor data sources in order for informed decisions to be made after understanding the real-time risks in workplaces based on person-to-place interactions. The IoCT architecture is based on the Sensor Web paradigm that connects various Things, Sensors, and Datastreams with an indoor geospatial data model. This paper presents a study of what, to the best of our knowledge, is the first real-world integrated implementation of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) and IndoorGML standards to calculate the risk of COVID-19 online using a workplace reopening case study. The proposed IoCT offers a new open standard-based information model, architecture, methodologies, and software tools that enable the interoperability of disparate COVID-19 monitoring systems with finer spatial-temporal granularity. A workplace cleaning use case was developed in order to demonstrate the capabilities of this proposed IoCT architecture. The implemented IoCT architecture included proximity-based contact tracing, people density sensors, a COVID-19 risky behavior monitoring system, and the contextual building geospatial data.

Geospatial Sensor Web Adaptor for Integrating Diverse Internet of Things Protocols Within Smart City

Abstract: . In recent years, the multi-scale comprehensive perception is central to smart city development. We propose an "adaptor" for geospatial sensor web as an integrated sensory system that can integrate access to geodetic equipment based on the Internet of Things technology with multiple platforms and protocols. At the same time, the acquisition, fusion, and processing of sensory resources can perform. The geospatial adaptor can access and process sensors of different IoT protocols to different conditions simultaneously. Grace to this geospatial adaptor, a considerable number of the sensor based on IoT in the community, can achieve distributed access, ensuring the better robustness of the geospatial sensor web. This paper describes the system architecture of the geospatial sensor web adapter. Furthermore, from the perspective of protocol access, it introduces the access capabilities of geospatial sensor web adapter to the standard IoT interface protocols. By comparing the geospatial sensor web adapter with traditional observation methods by experiments and acquisition of test data. The results show that the geospatial sensor web adapter can achieve powerful access capabilities and network stability, and it is a better solution for heterogeneous sensing platform access in smart cities.