5G enabled Freeports:A conceptual framework

A novel conceptual framework is developed that depicts a generic Freeport model underpinned by 5G technology. The framework is based on preliminary findings from a 5G testbed project and secondary 5G use cases from both practice and academic literature. We first provide a descriptive model of the current state of a port without 5G and Freeport status, identify the challenges and opportunities for logistics flows if Freeport status is attained and then prescribe how 5G may enable seamless logistics flows. With multiple challenges for ports generally, Freeport status increases the level of complexity of the core and support business processes that deliver goods from origin to destination. Despite that increased complexity, Freeports can attract investment and generate revenue, thus the enablement of Freeports is notionally beneficial in the long run. As complexity is anathema to smooth logistics flows, we develop a prescriptive model to exploit 5G to improve efficiency and effectiveness within a Freeport. We demonstrate the application of the prescriptive model with a 5G Freeport use case supported by simulation results, from which we aim to contribute to the overall adoption of 5G in Freeports

Designing wearable sensing platforms for healthcare in a residential environment

Wearable technologies are valuable tools that can encourage people to monitor their own well-being and facilitate timely health interventions. In this paper, we present SPW-2; a low-profile versatile wearable sensor that employs two ultra low power accelerometers and an optional gyroscope. Designed for minimum maintenance and a long-term operation outside the laboratory, SPW-2 is able to offer a battery lifetime of multiple months. Measurements on its wireless performance in a real residential environment with thick brick walls, demonstrate that SPW-2 can fully cover a room and - in most cases - the adjacent room, as well

Challenges in the Design and Implementation of IoT Testbeds in Smart-Cities : A Systematic Review

Advancements in wireless communication and the increased accessibility to low-cost sensing and data processing IoT technologies have increased the research and development of urban monitoring systems. Most smart city research projects rely on deploying proprietary IoT testbeds for indoor and outdoor data collection. Such testbeds typically rely on a three-tier architecture composed of the Endpoint, the Edge, and the Cloud. Managing the system's operation whilst considering the security and privacy challenges that emerge, such as data privacy controls, network security, and security updates on the devices, is challenging. This work presents a systematic study of the challenges of developing, deploying and managing urban monitoring testbeds, as experienced in a series of urban monitoring research projects, followed by an analysis of the relevant literature. By identifying the challenges in the various projects and organising them under the V-model development lifecycle levels, we provide a reference guide for future projects. Understanding the challenges early on will facilitate current and future smart-cities IoT research projects to reduce implementation time and deliver secure and resilient testbeds

A Guide to the SPHERE 100 Homes Study Dataset

The SPHERE project has developed a multi-modal sensor platform for health and behavior monitoring in residential environments. So far, the SPHERE platform has been deployed for data collection in approximately 50 homes for duration up to one year. This technical document describes the format and the expected content of the SPHERE dataset(s) under preparation. It includes a list of some data quality problems (both known to exist in the dataset(s) and potential ones), their workarounds, and other information important to people working with the SPHERE data, software, and hardware. This document does not aim to be an exhaustive descriptor of the SPHERE dataset(s); it also does not aim to discuss or validate the potential scientific uses of the SPHERE data