scholarly journals Virtualizing AI at the Distributed Edge Towards Intelligent IoT Applications

2021 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Claudia Campolo ◽  
Giacomo Genovese ◽  
Antonio Iera ◽  
Antonella Molinaro
Keyword(s):  
Resource Constraints ◽  
Smart Cities ◽  
Traditional Approach ◽  
Low Cost ◽  
Iot Applications ◽  
Software And Hardware ◽  
Iot Devices ◽  
Consumer Devices ◽  
Hardware Platforms ◽  
Smart Factories

Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a virtualization layer hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution.

scholarly journals Open-Source Electronics Platforms as Enabling Technologies for Smart Cities: Recent Developments and Perspectives

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 404 ◽  
Author(s):  
Daniel Costa ◽  
Cristian Duran-Faundez
Keyword(s):  
Open Source ◽  
Smart City ◽  
Smart Cities ◽  
Low Cost ◽  
Raspberry Pi ◽  
Computational Power ◽  
Different Types ◽  
Recent Developments ◽  
Programmable Devices ◽  
Hardware Platforms

With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.

scholarly journals Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Saeed H. Alsamhi ◽  
Faris A. Almalki ◽  
Hatem Al-Dois ◽  
Soufiene Ben Othman ◽  
Jahan Hassan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Smart Cities ◽  
Dynamic Environments ◽  
Iot Applications ◽  
Smart Healthcare ◽  
Intelligent Management ◽  
Reduce Energy Consumption ◽  
Iot Devices ◽  
Shed Light

The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.

scholarly journals Automatic Failure Recovery for Container-Based IoT Edge Applications

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3047
Author(s):  
Kolade Olorunnife ◽  
Kevin Lee ◽  
Jonathan Kua
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Smart Homes ◽  
Edge Computing ◽  
Failure Recovery ◽  
Software Failures ◽  
Iot Applications ◽  
Remote Management ◽  
Management Ability ◽  
Iot Devices

Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario.

scholarly journals Edge-Based Missing Data Imputation in Large-Scale Environments

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 195
Author(s):  
Davide Andrea Guastella ◽  
Guilhem Marcillaud ◽  
Cesare Valenti
Keyword(s):  
Urban Environment ◽  
Large Scale ◽  
Smart Cities ◽  
Low Cost ◽  
Real Data ◽  
Missing Data Imputation ◽  
Large Scale Data ◽  
Iot Devices ◽  
Edge Based ◽  
The One

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis; on the other hand, it involves different challenges such as intermittent sensors and integrity of acquired data. To this effect, edge computing emerges as a methodology to distribute computation among different IoT devices to analyze data locally. We present here a new methodology for imputing environmental information during the acquisition step, due to missing or otherwise out of order sensors, by distributing the computation among a variety of fixed and mobile devices. Numerous experiments have been carried out on real data to confirm the validity of the proposed method.

scholarly journals A Fully Open-Source Approach to Intelligent Edge Computing: AGILE’s Lesson

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1309
Author(s):  
Massimo Vecchio ◽  
Paolo Azzoni ◽  
Andreas Menychtas ◽  
Ilias Maglogiannis ◽  
Alexander Felfernig
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
Pollution Monitoring ◽  
Quantified Self ◽  
Air Pollution Monitoring ◽  
Industrial Iot ◽  
Funded Project ◽  
Software And Hardware ◽  
Iot Devices ◽  
The Internet Of Things

In this paper, we describe the main outcomes of AGILE (acronym for “Adaptive Gateways for dIverse muLtiple Environments”), an EU-funded project that recently delivered a modular hardware and software framework conceived to address the fragmented market of embedded, multi-service, adaptive gateways for the Internet of Things (IoT). Its main goal is to provide a low-cost solution capable of supporting proof-of-concept implementations and rapid prototyping methodologies for both consumer and industrial IoT markets. AGILE allows developers to implement and deliver a complete (software and hardware) IoT solution for managing non-IP IoT devices through a multi-service gateway. Moreover, it simplifies the access of startups to the IoT market, not only providing an efficient and cost-effective solution for industries but also allowing end-users to customize and extend it according to their specific requirements. This flexibility is the result of the joint experience of established organizations in the project consortium already promoting the principles of openness, both at the software and hardware levels. We illustrate how the AGILE framework can provide a cost-effective yet solid and highly customizable, technological foundation supporting the configuration, deployment, and assessment of two distinct showcases, namely a quantified self application for individual consumers, and an air pollution monitoring station for industrial settings.

scholarly journals Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues

2021 ◽  
Vol 13 (8) ◽  
pp. 210 ◽  
Author(s):  
Sheetal Ghorpade ◽  
Marco Zennaro ◽  
Bharat Chaudhari
Keyword(s):  
Internet Of Things ◽  
Performance Metrics ◽  
Smart Cities ◽  
Low Cost ◽  
Real Life ◽  
High Energy ◽  
Mobile Nodes ◽  
Node Localization ◽  
Iot Devices ◽  
Device Free

With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything from vehicles to the human body to smart homes to smart factories. Mobility of the nodes enhances the network coverage and connectivity. One of the crucial requirements in IoT systems is the accurate and fast localization of its nodes with high energy efficiency and low cost. The localization process has several challenges. These challenges keep changing depending on the location and movement of nodes such as outdoor, indoor, with or without obstacles and so on. The performance of localization techniques greatly depends on the scenarios and conditions from which the nodes are traversing. Precise localization of nodes is very much required in many unique applications. Although several localization techniques and algorithms are available, there are still many challenges for the precise and efficient localization of the nodes. This paper classifies and discusses various state-of-the-art techniques proposed for IoT node localization in detail. It includes the different approaches such as centralized, distributed, iterative, ranged based, range free, device-based, device-free and their subtypes. Furthermore, the different performance metrics that can be used for localization, comparison of the different techniques, some prominent applications in smart cities and future directions are also covered.

Reliability and Security Challenges in Electrical/Optical On-Chip Interconnects for IoT Applications

2020 ◽  
pp. 218-246
Author(s):  
Muhammad Rehan Yahya ◽  
Ning Wu ◽  
Zain Anwar Ali
Keyword(s):  
Communication Systems ◽  
Data Transfer ◽  
Smart Cities ◽  
Security Issues ◽  
Iot Applications ◽  
Security Challenges ◽  
Chip Processing ◽  
Share Data ◽  
Iot Devices ◽  
On Chip

The evolution of internet of things (IoT) applications, cloud computing, smart cities, and 4G/5G wireless communication systems have significantly increased the demands for on chip processing. Network on chip (NoC) is a viable alternative that can provide higher processing and bandwidth for increasing demands. NoC offers better performance and more flexibility with lower communication latency and higher throughput. However, use of NoC-based IoT devices have raised concerns on security and reliability of integrated chips (IC), which is used in almost every application. IoT devices share data that becomes vulnerable to attack and can be compromised during the data transfer. Keeping in view these security challenges, a detailed survey is presented that covers the security issues and challenges focusing on NoCs along with proposed countermeasures to secure on-chip communication. This study includes on-chip security issues for electrical as well as optical on-chip interconnects.

scholarly journals A System for Controlling and Monitoring IoT Applications

2018 ◽  
Vol 1 (3) ◽  
pp. 26 ◽  
Author(s):  
Zebenzui Lima ◽  
Hugo García-Vázquez ◽  
Raúl Rodríguez ◽  
Sunil Khemchandani ◽  
Fortunato Dualibe ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Internet Of Things ◽  
Open Source Software ◽  
Remote Monitoring ◽  
Low Cost ◽  
Raspberry Pi ◽  
Design And Implementation ◽  
Iot Applications ◽  
Hardware System ◽  
Software And Hardware

In this work, the design and implementation of an open source software and hardware system for Internet of Things (IoT) applications is presented. This system permits the remote monitoring of supplied data from sensors and webcams and the control of different devices such as actuators, servomotors and LEDs. The parameters which have been monitored are brightness, temperature and relative humidity all of which constitute possible environmental factors. The control and monitoring of the installation is realised through a server which is managed by an administrator. The device which rules the installation is a Raspberry Pi, a small and powerful micro-computer in a single board with low consumption, low cost and reconfigurability.

scholarly journals Neighbor Aware Protocols for IoT Devices in Smart Cities—Overview, Challenges and Solutions

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 902
Author(s):  
Sungwon Lee ◽  
Muhammad Azfar Azfar Yaqub ◽  
Dongkyun Kim
Keyword(s):  
Internet Of Things ◽  
Duty Cycle ◽  
Smart City ◽  
Mac Protocol ◽  
Smart Cities ◽  
Iot Applications ◽  
Simulation Results ◽  
Iot Devices ◽  
The Impact

The principle of Smart Cities is the interconnection of services, based on a network of Internet of Things (IoT) devices. As the number of IoT devices continue to grow, the demand to organize and maintain the IoT applications is increased. Therefore, the solutions for smart city should have the ability to efficiently utilize the resources and their associated challenges. Neighbor aware solutions can enhance the capabilities of the smart city. In this article, we briefly overview the neighbor aware solutions and challenges in smart cities. We then categorize the neighbor aware solutions and discuss the possibilities using the collaboration among neighbors to extend the lifetime of IoT devices. We also propose a new duty cycle MAC protocol with assistance from the neighbors to extend the lifetime of the nodes. Simulation results further coagulate the impact of neighbor assistance on the performance of IoT devices in smart cities.

Overview of Development Plans for Magnetic Bearing Control System

2012 ◽  
Vol 190-191 ◽  
pp. 1157-1161
Author(s):  
Xiao Ming Zhu ◽  
Wan Qing Teng
Keyword(s):  
Low Cost ◽  
Dynamic Performance ◽  
Magnetic Bearing ◽  
Code Design ◽  
New Development ◽  
Development Plans ◽  
New Type ◽  
Software Platforms ◽  
Software And Hardware ◽  
Hardware Platforms

Magnetic bearing is a new type bearing used in many fields. An appropriate controller can greatly improve its dynamic performance. With the development of software and hardware of computer, many new platforms appear suitable for studying of controller of magnetic bearing. Typical software platforms include universal operation systems, such as Dos, Windows, and some special operation systems, such as RTLinux. Some applications, such as Matlab/Simulink, can also be applied. And typical hardware platforms cover PC, DSP and some special embedded computers. The design mode of the controller also advances from code design to model design. Many new development plans of magnetic bearing controller based on these platforms and design mode have many advantages over old platforms. For designers, the development plans based on theses new platforms are good choices for bringing about a stable, short development period, low cost controller.

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