Smart hospital emergency system via mobile-based requesting services

In recent years, the UK’s emergency call and response has shown elements of great strain as of today. The strain on emergency call systems estimated by a 9 million calls (including both landline and mobile) made in 2014 alone. Coupled with an increasing population and cuts in government funding, this has resulted in lower percentages of emergency response vehicles at hand and longer response times. In this paper, we highlight the main challenges of emergency services and overview of previous solutions. In addition, we propose a new system call Smart Hospital Emergency System (SHES). The main aim of SHES is to save lives through improving communications between patient and emergency services. Utilising the latest of technologies and algorithms within SHES is aiming to increase emergency communication throughput, while reducing emergency call systems issues and making the process of emergency response more efficient. Utilising health data held within a personal smartphone, and internal tracked data (GPU, Accelerometer, Gyroscope etc.), SHES aims to process the mentioned data efficiently, and securely, through automatic communications with emergency services, ultimately reducing communication bottlenecks. Live video-streaming through real-time video communication protocols is also a focus of SHES to improve initial communications between emergency services and patients. A prototype of this system has been developed. The system has been evaluated by a preliminary usability, reliability, and communication performance study

Norm-based and commitment-driven agentification of the Internet of Things

There are no doubts that the Internet-of-Things (IoT) has conquered the ICT industry to the extent that many governments and organizations are already rolling out many anywhere,anytime online services that IoT sustains. However, like any emerging and disruptive technology, multiple obstacles are slowing down IoT practical adoption including the passive nature and privacy invasion of things. This paper examines how to empower things with necessary capabilities that would make them proactive and responsive. This means things can, for instance reach out to collaborative peers, (un)form dynamic communities when necessary, avoid malicious peers, and be “questioned” for their actions. To achieve such empowerment, this paper presents an approach for agentifying things using norms along with commitments that operationalize these norms. Both norms and commitments are specialized into social (i.e., application independent) and business (i.e., application dependent), respectively. Being proactive, things could violate commitments at run-time, which needs to be detected through monitoring. In this paper, thing agentification is illustrated with a case study about missing children and demonstrated with a testbed that uses different IoT-related technologies such as Eclipse Mosquitto broker and Message Queuing Telemetry Transport protocol. Some experiments conducted upon this testbed are also discussed

Cognitive computing meets the internet of things

Abstract: This paper discusses the blend of cognitive computing with the Internet-of-Things that should result into developing cognitive things. Today’s things are confined into a data-supplier role, which deprives them from being the technology of choice for smart applications development. Cognitive computing is about reasoning, learning, explaining, acting, etc. In this paper, cognitive things’ features include functional and non-functional restrictions along with a 3 stage operation cycle that takes into account these restrictions during reasoning, adaptation, and learning. Some implementation details about cognitive things are included in this paper based on a water pipe case-study

A location-sensitive and network-aware broker for recommending Web services

© 2019, Springer-Verlag GmbH Austria, part of Springer Nature. Collaborative filtering (CF) is one of the renowned recommendation techniques that can be used for predicting unavailable Quality-of-Service (QoS) values of Web services. Although several CF-based approaches have been proposed in recent years, the accuracy of the QoS values, that these approaches provide, raises some concerns and hence, could undermine the real “quality” of Web services. To address these concerns, context information such as communication-network configuration and user location could be integrated into the process of developing recommendations. Building upon such context information, this paper proposes a CF-based Web services recommendation approach, which incorporates the effect of locations of users, communication-network configurations of users, and Web services run-time environments on the recommendations. To evaluate the accuracy of the recommended Web services based on the defined QoS values, a set of comprehensive experiments are conducted using a real dataset of Web services. The experiments are in line with the importance of integrating context into recommendations

AI and machine learning: A mixed blessing for cybersecurity

While the usage of Artificial Intelligence and Machine Learning Software (AI/MLS) in defensive cybersecurity has received considerable attention, there remains a noticeable research gap on their offensive use. This paper reviews the defensive usage of AI/MLS in cybersecurity and then presents a survey of its offensive use. Inspired by the System-Fault-Risk (SFR) framework, we categorize AI/MLS-powered cyberattacks by their actions into seven categories. We cover a wide spectrum of attack vectors, discuss their practical implications and provide some recommendations for future research

Open challenges in vetting the internet‐of‐things

Internet‐of‐Thing (IoT) is a rapid‐emerging technology that exploits the concept of internetwork to connect things such as physical devices and objects together. A huge number of things (6.4 billion are in use in 2016) are already acting without direct human control raising a lot of concerns about the readiness and appropriateness of existing security practices, techniques, and tools to secure the data collected and protect people\u27s private lives. As a first step, this paper presses the importance of having a dedicated process for vetting IoT (by analogy to vetting mobile apps) with focus on exposing things\u27 vulnerabilities that could be the primary source of attacks. These vulnerabilities are identified according to things\u27 duties decomposed into sensing, actuating, and communicating. A set of questions shed light on things\u27 vulnerabilities per type of duty

A Quality-of-Things model for assessing the Internet-of-Things\u27 nonfunctional properties

© 2019 John Wiley & Sons, Ltd. The Internet of Things (IoT) is in a “desperate” need for a practical model that would help in differentiating things according to their nonfunctional properties. Unfortunately, despite IoT growth, such properties either lack or ill-defined resulting into ad hoc ways of selecting similar functional things. This paper discusses how things\u27 nonfunctional properties are combined into a Quality-of-Things (QoT) model. This model includes properties that define the performance of things\u27 duties related to sensing, actuating, and communicating. Since the values of QoT properties might not always be available or confirmed, providers of things can tentatively define these values and submit them to an Independent Regulatory Authority (IRA) whose role is to ensure fair competition among all providers. The IRA assesses the values of nonfunctional properties of things prior to recommending those that could satisfy users\u27 needs. To evaluate the technical doability of the QoT model, a set of comprehensive experiments are conducted using real data sets. The results depict an acceptable level of the QoT estimation accuracy

In Situ Mutation for Active Things in the IoT Context

Copyright © 2018 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved This paper discusses mutation as a new way for making things, in the context of Internet-of-Things (IoT), active instead of being passive as reported in the ICT literature. IoT is gaining momentum among ICT practitioners who see a lot of benefits in using things to support users have access to and control over their surroundings. However, things are still confined into the limited role of data suppliers. The approach proposed in this paper advocates for 2 types of mutation, active and passive, along with a set of policies that either back or deny mutation based on specific “stopovers” referred to as permission, prohibition, dispensation, and obligation. A testbed and a set of experiments demonstrating the technical feasibility of the mutation approach, are also presented in the paper. The testbed uses NodeMCU firmware and Lua script interpreter

The internet of things: Challenges and considerations for cybercrime investigations and digital forensics

Copyright © 2020, IGI Global. The Internet of Things (IoT) represents the seamless merging of the real and digital world, with new devices created that store and pass around data. Processing large quantities of IoT data will proportionately increase workloads of data centres, leaving providers with new security, capacity, and analytics challenges. Handling this data conveniently is a critical challenge, as the overall application performance is highly dependent on the properties of the data management service. This article explores the challenges posed by cybercrime investigations and digital forensics concerning the shifting landscape of crime – the IoT and the evident investigative complexity – moving to the Internet of Anything (IoA)/Internet of Everything (IoE) era. IoT forensics requires a multi-faceted approach where evidence may be collected from a variety of sources such as sensor devices, communication devices, fridges, cars and drones, to smart swarms and intelligent buildings