Context-driven Policies Enforcement for Edge-based IoT Data Sharing-as-a-Service

Sharing real-time data originating from connected devices is crucial to real-world intelligent Internet of Things (IoT) applications, i.e., based on artificial intelligence/machine learning (AI/ML). Such IoT data sharing involves multiple parties for different purposes and is usually based on data contracts that might depend on the dynamic change of IoT data variety and velocity. It is still an open challenge to support multiple parties (aka tenants) with these dynamic contracts based on the data value for their specific contextual purposes.This work addresses these challenges by introducing a novel dynamic context-based policy enforcement framework to support IoT data sharing (on-Edge) based on dynamic contracts. Our enforcement framework allows IoT Data Hub owners to define extensible rules and metrics to govern the tenants in accessing the shared data on the Edge based on policies defined with static and dynamic contexts. We have developed a proof-of-concept prototype for sharing sensitive data such as surveillance camera videos to illustrate our proposed framework. The experimental results demonstrated that our framework could soundly and timely enforce context-based policies at runtime with moderate overhead. Moreover, the context and policy changes are correctly reflected in the system in nearly real-time.acceptedVersio

Design and evaluation of a scalable Internet of Things backend for smart ports

Internet of Things (IoT) technologies, when adequately integrated, cater for logistics optimisation and operations' environmental impact monitoring, both key aspects for today's EU ports management. This article presents Obelisk, a scalable and multi-tenant cloud-based IoT integration platform used in the EU H2020 PortForward project. The landscape of IoT protocols being particularly fragmented, the first role of Obelisk is to provide uniform access to data originating from a myriad of devices and protocols. Interoperability is achieved through adapters that provide flexibility and evolvability in protocol and format mapping. Additionally, due to ports operating in a hub model with various interacting actors, a second role of Obelisk is to secure access to data. This is achieved through encryption and isolation for data transport and processing, respectively, while user access control is ensured through authentication and authorisation standards. Finally, as ports IoTisation will further evolve, a third need for Obelisk is to scale with the data volumes it must ingest and process. Platform scalability is achieved by means of a reactive micro-services based design. Those three essential characteristics are detailed in this article with a specific focus on how to achieve IoT data platform scalability. By means of an air quality monitoring use-case deployed in the city of Antwerp, the scalability of the platform is evaluated. The evaluation shows that the proposed reactive micro-service based design allows for horizontal scaling of the platform as well as for logarithmic time complexity of its service time

Implementasi Elastic Stack Pada Sistem Pendeteksi Tingkat Stres Menggunakan Sensor GSR dan DS18B20 Berbasis Raspberry Pi

Kesehatan tubuh mencakup kesehatan fisik dan mental. Salah satu faktor penentu kesehatan mental adalah stres. Selama ini, telah tersedia alat pendeteksi stres dengan memanfaatkan indikator fisiologis akibat reaksi yang muncul dari symphatetic nervous system, namun alat cenderung mahal dan masih bekerja secara terpisah. Dalam penelitian ini, dibuat dua buah prototipe pendeteksi tingkat stres menggunakan Galvanic Skin Response, DS18B20, dan Raspberry Pi. Skenario sistem dirancang untuk dua orang pasien dari dua rumah sakit berbeda yang ditangani oleh satu orang tenaga medis. Untuk memastikan reliabilitas jaringan dalam transmisi data, mempertimbangkan pengolahan database dan visualisasi pengguna, implementasi Elastic Stack dilakukan pada sistem. Data dikirimkan dari Raspberry Pi sebagai client menggunakan Beat dan ditampung ke dalam Logstash sebelum dimasukkan ke dalam database (Elasticsearch). Hasil pengolahan data divisualisasikan menggunakan Kibana dashboard. Dalam penelitian, kalibrasi sensor GSR menunjukkan percentage difference sebesar 0,79% dan sensor DS18B20 sebesar 0,095%. Rata-rata delay dalam proses transmisi data berlangsung sekitar 3-4 detik. Hal ini terjadi karena Filebeat akan menyesuaikan kecepatan pengiriman data agar tidak membebani server. Mekanisme harvester dan prospector pada Filebeat juga memastikan semua data terkirim dan tersimpan dalam registry file, sehingga sistem akan melakukan pengiriman kembali sekalipun server down. Secara kesuluruhan, hasil pengujian QoS menggunakan standar TIPHON menunjukkan bahwa transmisi data dari Beat menuju Logstash berkategori memuaska

Architecture for intensive care data processing and visualization in real-time

Clinical data is growing every day. Ergo, to treat, store and publish such data is an emergent task. Furthermore, analysing data in real-time using streaming and processing technologies and methods, in order to obtain quality data, prepared to support decision making is of extreme value. Big Data emerged with the introduction of real-time processing, thus revolutionizing traditional technologies and techniques through the ability to deal with the volume, speed and variety of data. Countless studies have been proposed in the healthcare domain in search of solutions that allow the flow of data in real-time. However, the work presented hereby is distinguished by allowing the collection, processing, storage and analysis of Intensive Care Units (ICU) data, both collected in real-time from bedside monitors but also stored in a historical repository. The architecture proposed makes use of current technologies, like Nextgen Connector as message supplier and integrator, Elasticsearch as a search index, Kibana for viewing stored data and Grafana for real-time streaming. This article is part of the ICDS4IM project - Intelligent Clinical Decision Support in Intensive Care Medicine to support the experimentation of data processing techniques and technologies, based in HL7 format and collected in real-time so that it can be made available through Health Information Systems across the healthcare institutions.The work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: DSAIPA/DS/0084/2018

Log Event Management Server Menggunakan Elastic Search Logstash Kibana (ELK Stack)

This study aims to build an Event Management Server Log using ELK Stack (Elastic searchLogstash Kibana) which can make it easier to read and analyze log services on the server. TheEvent Management Server log in this study uses CentOS 7 as the Central Server and CentOS7 as a client-server with ssh services installed. This research consists of five stages. The stagesare analysis, network design, server configuration, client configuration, and testing. Theexperimental results show that all ssh log services that occur on the client-server sent inrealtime to the central server. Even though the contents of the log file on the client-server hasdeleted. In This study, in addition to sending logs, it can also display a percentage of successreferences

City Hub:a cloud based IoT platform for Smart Cities

Cloud based Smart City hubs are an attractive approach to addressing some of the complex issues faced when deploying PaaS infrastructure for Smart Cities. In this paper we introduce the general notion of IoT hubs and then discusses our work to generalize our IoT hub as a Smart City PaaS. Two key issues are identified, support for hybrid public/private cloud and interoperability. We briefly describe our approach to these issues and discuss our experiences deploying two cloud-based Smart City hubs, one in the UK and the other in Canada

Uso de X-Road para implementar datos abiertos en sistemas eléctricos y promover la integración con estrategias de ciudad inteligente y gobierno abierto

The electrical industry is undergoing a deep digital transformation towards the consolidation of smart grids, which requires a high demand of data and information systems involved in the processes. Open data initiatives, which have been focused on open governance to a great extent, generate positive impacts on society and the economy in terms of easy access to public resources, agility, and transparency. These initiatives can also be adopted in the electrical industry (i.e., power, electrical, and energy systems) for customer engagement, collaboration with other industries, and reaching consensus. This study proposes the implementation of an open data solution for the electrical industry through the deployment of a data hub that offers digital services for smart city applications and the integration of the X-Road system to improve the security and interoperability of open data. This initiative aims to promote a wider adoption of open data in the electrical industry and prepare the latter for fully connected and collaborative digital ecosystems in smart cities, industries, and governments. This study also proposes an open data architecture for the interoperability of the electrical industry with other digital industries (through a Smart City Hub and the adoption of 5G technology), and it reports some relevant results and major findings in this regard. This paper highlights the benefits of promoting open data and technological strategies for digitized electrical systems while considering humans an essential factor. Finally, it discusses the pros and cons of the integration of X-Road with the electrical industry under the concept of smart grids for data exchange and potential applications.La industria eléctrica está experimentando una profunda transformación digital hacia la consolidación de redes inteligentes, que necesita una alta demanda de datos y sistemas de información involucrados en los procesos. Las iniciativas de datos abiertos, que en mayor medida han sido empleadas para iniciativas de gobierno abierto, generan impactos positivos en la sociedad y la economía en cuanto al fácil acceso a los recursos públicos, la agilidad y la transparencia. Estas iniciativas también se pueden adoptar en la industria eléctrica para sistemas de potencia, eléctricos y de energía para su uso en la participación de los clientes, la colaboración y la mejora de consenso en industrias. Esta investigación propone la implementación de una solución de datos abiertos para la industria eléctrica mediante el despliegue de un Hub que ofrece servicios digitales para aplicaciones de ciudad inteligente y la integración del sistema X-Road para mejorar la seguridad e interoperabilidad de los datos abiertos. Esta iniciativa pretende una adopción más amplia de datos abiertos en la industria eléctrica y su preparación para ecosistemas digitales totalmente conectados y colaborativos en ciudades inteligentes, industrias y gobierno. Se muestran algunos resultados relevantes y hallazgos importantes de este trabajo acerca de una arquitectura de datos abiertos para la interoperabilidad del sector eléctrico con otras industrias digitales a través de un Smart City Hub y la adopción tecnológica de 5G, exponiendo los beneficios de promover los datos abiertos y estrategias tecnológicas para sistemas eléctricos digitalizados mientras se considera el humano como factor esencial. Se discuten los pros y los contras de la integración de X-Road con la industria eléctrica dentro del concepto de redes inteligentes para el intercambio de datos y aplicaciones potenciales

DESAIN DAN IMPLEMENTASI LOG EVENT MANAGEMENT SERVER MENGGUNAKAN ELASTICSEARCH LOGSTASH KIBANA (ELK STACK)

Penggunaan server yang harus berjalan selama 24 jam dan services yang berjalan pada server tersebut pasti menghasilkan sebuah log yang cukup banyak. Hal ini mengharuskan seorang sistem administrator dalam pengecekannya masih harus berinteraksi langsung dengan server tersebut. Dalam penelitian ini bermaksud untuk melakukan suatu perancangan untuk membangun Log Event Management Server menggunakan ELK Stack (Elasticsearch Logstash Kibana) yang dapat memudahkan dalam membaca sekaligus menganalis log services pada server. Implementasi Log Event Management Server dalam penelitian kali ini menggunakan CentOS 7 Server, dan Ubuntu 14.04 sebagai server client dengan SSH services yang terpasang. Dari hasil pengujian ELK Stack sebagai Log Event Management yang telah dibangun dengan tingkat keberhasilan 100% menunjukan bahwa semua log services SSH yang terjadi pada server client dapat dikirimkan secara realtime ke server utama ELK Stack sekalipun isi file log pada server client tersebut dihapus