A Semantic IoT Early Warning System for Natural Environment Crisis Management

Abstract

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model. We use lightweight semantics for metadata to enhance rich sensor data acquisition. We use heavyweight semantics for top level W3C Web Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a deployed EWS infrastructure.

Migrating Live Streaming Applications onto Clouds: Challenges and a CloudStorm Solution

“…The actual nature of individual response-time constraints varies. For example, often time constraints are imposed on the acquisition, processing and publishing of real-time observations, not least in scenarios such as weather prediction or disaster early warning [8]. The ability to handle such scenarios is predicated on the time needed for customization of the runtime environment and the scheduling of workflows [9] [10], while the steering of applications during complex experiments is also temporally bounded [11].…”

“…It is able to provision a networked infrastructure, recover from sudden failures quickly, and scale across data centers or clouds automatically [19]. This framework is able to set up a networked virtual Cloud across even public clouds, which do not explicitly support network topology, like EC2 7 or EGI 8 . Finally, the deployment agent of CloudsStorm uses the description to arrange application components in the virtual infrastructure.…”

Sistem Peringatan Dini Banjir Secara Real-Time Berbasis Web Menggunakan Arduino dan Ethernet

“…Selain penggunaan modem atau teknologi GSM maka telah dilakukan juga penggunaan teknologi informasi bencana berbasis internet. Hal ini terlihat bahwa banyak penelitian yang mengarah pada penggunaan internet sebagai sumber informasi terintegrasi dengan sistem peringatan dini bencana menggunakan model yang disebut dengan Internet of Things (IoTs) (Poslad et al 2015). Penggunaan teknologi internet yang diintegrasikan dengan teknologi embedded system dapat dilihat penelitian yang dilakukan oleh (Rahman et al 2017) yaitu sistem tracking kendaraan berbasis Google Maps dan mikrokontroler Arduino (Rahman et al 2017).…”

Providing Interoperability for Autonomic Control of Connected Devices

“…Existing work such as [8] tackles this problem by proposing enrichment techniques to transform raw data into knowledge conform to the W3C recommendations. Once enriched, collected data becomes exploitable and can be abstracted into higher-level knowledge as in [9], which is useful in our case of symptom computing in the MAPE-K loop.…”