A smartwater metering deployment based on the fog computing paradigm

In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system's design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system

Performance Analysis of Smartphone-based Mobile Wi-Fi Hotspots Operating in a Congested Environment

In this work, we address the ubiquity of internet connections in smart cities by analyzing mobile Wi-Fi hotspots in terms of speed and energy efficiency in a congested Wi-Fi environment. We consider state-of-theart consumer smartphones in our work since they are the major devices in establishing mobile Wi-Fi hotspots nowadays. There are two main wireless connections in mobile Wi-Fi hotspots, the cellular connection and the Wi-Fi connection. It has been known that the speed of WiFi connections enormously supersedes the speed of cellular connections with the use of present technologies of each. In this work, we show that this well-known fact becomes controversial when establishing mobile Wi-Fi hotspots using smartphones in a nowadays typical congested Wi-Fi environment

RSS Indoor Localization Based on a Single Access Point

This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor-WKNN and Minimum Mean Square Error-MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the "Tolerance Based-Normal Probability Distribution (TBNPD)" algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP

A MULTILEVEL USER VALIDATION FRAMEWORK FOR ACCESSING CLOUD SERVICES

Cloud computing is a paradigm that offers enormous advantages to cloud users for example, huge memory, adaptable processing abilities, security to the data and boundless registering capabilities. To utilize the maximum capacity of Cloud computing, information is moved, handled and stored by Cloud Service Providers (CSP). Be that as it may, information owners are suspicious to put their information in cloud that is outside their own control. The main issue with Cloud computing is the manner by which to provide the security and protection of cloud user information being prepared and additionally stored in a Cloud computing condition. With regards to cloud information assurance, the techniques utilized can be fundamentally the same as ensuring information inside a conventional server group. To perform user validation for accessing cloud services, a strong cryptography method is introduced along with a multi factor verification process. Moving information into the cloud implies that the clients have less authority over their information, this implies the cloud clients must believe the CSP to secure the information from both outside and inside attacks. In the proposed work, a Multi Level User Authentication (MLUA) framework is introduced for accessing cloud services. The unauthorized users are not allowed to access cloud resources. The cloud user, data owner and cloud service providers are involved in multi factor authentication. The CSP will generate a Digital Unique Authentication Identity (DUAI) number along with general verification for undergoing multi level verification process. The proposed method is compared with the traditional methods and the results show that the proposed method is better in performance and accuracy in identification of valid cloud users

The Rural Digital Divide in the Face of the COVID-19 Pandemic in Europe-Recommendations from a Scoping Review

The COVID-19 pandemic has revealed the digital vulnerability of many citizens of the rural world. This article identifies and analyzes the proposals made by academic literature to overcome the digital divide in the European rural world for the five-year period 2016-2020. A scoping review has been carried out according to the PRISMA methodology in the two dimensions of the digital divide: access and connectivity, and use and exploitation. Online databases were used to identify scientific articles from which, after screening, 28 key documents were selected. The results update Salemink systematic review of articles published between 1991 and 2014 on digital and rural development in Western countries and it also intends to go beyond by extracting recommendations. A variety of political, social, educational, technical and economic issues has been exposed, with a common emphasis on the empowerment of rural populations. The findings provide actionable evidence and proposals to facilitate decision-making in current policy information to overcome rural digital divide. From them, seven recommendations that could have a wide and rapid impact to minimize the effects of the COVID-19 pandemic linked to the rural digital divide are synthesized. Three lines of action in the medium term are also proposed: the evaluation of national and regional public policies; the consideration of digital inclusion as a potential instrument to reduce rural depopulation; and the training in advanced digital skills to improve the social communication processes, considered key to promote empowerment and entrepreneurship

Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture)

In the near future, the fifth-generation wireless technology is expected to be rolled out, offering low latency, high bandwidth and multiple antennas deployed in a single access point. This ecosystem will help further enhance various location-based scenarios such as assets tracking in smart factories, precise smart management of hydroponic indoor vertical farms and indoor way-finding in smart hospitals. Such a system will also integrate existing technologies like the Internet of Things (IoT), WiFi and other network infrastructures. In this respect, 5G precise indoor localization using heterogeneous IoT technologies (Zigbee, Raspberry Pi, Arduino, BLE, etc.) is a challenging research area. In this work, an experimental 5G testbed has been designed integrating C-RAN and IoT networks. This testbed is used to improve both vertical and horizontal localization (3D Localization) in a 5G IoT environment. To achieve this, we propose the DEep Learning-based co-operaTive Architecture (DELTA) machine learning model implemented on a 3D multi-layered fingerprint radiomap. The DELTA begins by estimating the 2D location. Then, the output is recursively used to predict the 3D location of a mobile station. This approach is going to benefit use cases such as 3D indoor navigation in multi-floor smart factories or in large complex buildings. Finally, we have observed that the proposed model has outperformed traditional algorithms such as Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)

The Penetration of Internet of Things in Robotics: Towards a Web of Robotic Things

As the Internet of Things (IoT) penetrates different domains and application areas, it has recently entered also the world of robotics. Robotics constitutes a modern and fast-evolving technology, increasingly being used in industrial, commercial and domestic settings. IoT, together with the Web of Things (WoT) could provide many benefits to robotic systems. Some of the benefits of IoT in robotics have been discussed in related work. This paper moves one step further, studying the actual current use of IoT in robotics, through various real-world examples encountered through a bibliographic research. The paper also examines the potential ofWoT, together with robotic systems, investigating which concepts, characteristics, architectures, hardware, software and communication methods of IoT are used in existing robotic systems, which sensors and actions are incorporated in IoT-based robots, as well as in which application areas. Finally, the current application of WoT in robotics is examined and discussed