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Internet of Things (IoT) and Cloud/Edge Computing
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Internet of Things (IoT) and Cloud/Edge Computing

A Special Issue of Information (ISSN 2078-2489) belonging to the section "Internet of Things (IoT)".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 13080

Editor

Dr. Abdullah Abuhussein

E-Mail Website
Guest Editor
Information Systems Department, St. Cloud State University, St. Cloud, MN 56301, USA
Interests: cloud computing; cloud security; Internet of Medical Things (IoMT); Internet-of-things (IoT); software engineering; social engineering; security and privacy and security metrics

Special Issue Information

Dear Colleagues,

The rapid growth of the Internet of Things and cloud/edge computing has dramatically changed the way that information is created, processed, and utilized in many fields. This Special Issue is dedicated to exploring the synergy between IoT and cloud/edge computing for changing data management, security, and real-time processing. Big-data-generated IoT devices guarantee high scalability, low latency, and better decision-making with cloud/edge infrastructures.

We invite original research, reviews, and case studies addressing innovative solutions and challenges within this domain. Of interest are topics related to data processing frameworks, information security and privacy, resource management, edge intelligence, energy efficiency, and real-time analytics in IoT–cloud/edge systems.

Theoretical development, concrete implementations, and hybrid models—balancing cloud and edge computing in IoT environments—are also sought. This Special Issue aims to develop a thorough understanding of how IoT and cloud computing reshape contemporary information systems, offering academic insights into practical benefits and emerging trends, and future research directions.

Dr. Abdullah Abuhussein
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Internet of Things (IoT)
  • cloud computing (CC)
  • edge computing (EC)
  • real-time data processing
  • IoT security and privacy
  • resource management
  • edge intelligence
  • pervasive computing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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32 pages, 3925 KB  
Article
Expert-Based Evaluation and Simulation Validation of a Smart Emergency Response System for Urban Settings in Resource-Constrained Environments
by Milliam Maxime Zekeng Ndadji, Mahamat Abdel Aziz Assoul, Baudoin Nguimeya Tsofack, Garrik Brel Jagho Mdemaya, Abakar Mahamat Tahir and Taibi Mahmoud
Information 2026, 17(6), 582; https://doi.org/10.3390/info17060582 - 11 Jun 2026
Viewed by 547
Abstract
The present study provides a multi-faceted validation and refinement of a distributed system architecture designed to improve emergency response in resource-constrained urban areas. The architecture integrates IoT sensors, edge computing, field-programmable gate arrays and distributed shortest-path algorithms to enhance resilience and operational efficiency. [...] Read more.
The present study provides a multi-faceted validation and refinement of a distributed system architecture designed to improve emergency response in resource-constrained urban areas. The architecture integrates IoT sensors, edge computing, field-programmable gate arrays and distributed shortest-path algorithms to enhance resilience and operational efficiency. As a primary validation strategy, a survey of 78 Cameroonian experts in software engineering, distributed systems, urban planning and emergency technologies was conducted. The survey yielded quantitative and qualitative data across multiple analytical dimensions, including subgroup analysis and a transferability assessment covering Nigeria, Senegal, and Kenya. The statistical analysis confirmed that the architecture is technically feasible, adaptable to local constraints, and has the potential to reduce response times. As a secondary validation strategy, a simulation-based study was conducted using iFogSim on smart-city models ranging from 25 to 100 nodes, encompassing five experiments: result consistency, geographic sensitivity, concurrent incident management, path-caching efficiency, and scalability analysis. The simulation results quantitatively corroborate the expert assessments, demonstrating low end-to-end latency and sustained throughput with realistic urban load conditions. Key challenges identified include interoperability, urban data structuring, financial sustainability and inter-institutional coordination. Experts have proposed a hierarchical structure of priority actions and concrete recommendations for engineers, researchers and policymakers. The combined findings validate the architecture and establish a replicable expert-simulation evaluation framework applicable to analogous distributed emergency-response systems in comparable resource-constrained contexts. The empirical results further constitute a reference baseline for the design and implementation of similar architectures. Full article
(This article belongs to the Special Issue Internet of Things (IoT) and Cloud/Edge Computing)
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28 pages, 3522 KB  
Article
Closed-Loop Digital Twin for Energy-Efficient Scheduling in Food Manufacturing Systems
by Gulshat Amirkhanova, Nazly Yusubova, Bauyrzhan Amirkhanov, Meruyert Sakypbekova and Siming Chen
Information 2026, 17(2), 195; https://doi.org/10.3390/info17020195 - 13 Feb 2026
Cited by 4 | Viewed by 1761
Abstract
Food manufacturing faces challenges in balancing efficiency, energy use, and quality. This paper presents a Hybrid Digital Twin Architecture (HDTA). It combines simulation, constraint programming, and Industrial IoT into a closed-loop system. The architecture has three layers: simulation for planning, optimization for scheduling, [...] Read more.
Food manufacturing faces challenges in balancing efficiency, energy use, and quality. This paper presents a Hybrid Digital Twin Architecture (HDTA). It combines simulation, constraint programming, and Industrial IoT into a closed-loop system. The architecture has three layers: simulation for planning, optimization for scheduling, and an edge layer for control. We validated this using a bakery model with 10 products. The results show a 24.4% reduction in production time and 23% energy savings. Simulation results show complete elimination of quality time-window violations (0.0% vs. 13.3% baseline, p < 0.001). The system achieved a 2.4-month return on investment. This work demonstrates how combining these technologies can improve process industries. Full article
(This article belongs to the Special Issue Internet of Things (IoT) and Cloud/Edge Computing)
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28 pages, 3315 KB  
Article
Cloud Security Assessment: A Taxonomy-Based and Stakeholder-Driven Approach
by Abdullah Abuhussein, Faisal Alsubaei, Vivek Shandilya, Fredrick Sheldon and Sajjan Shiva
Information 2025, 16(4), 291; https://doi.org/10.3390/info16040291 - 4 Apr 2025
Viewed by 1896
Abstract
Cloud adoption necessitates relinquishing data control to cloud service providers (CSPs), involving diverse stakeholders with varying security and privacy (S&P) needs and responsibilities. Building upon previously published work, this paper addresses the persistent challenge of a lack of standardized, transparent methods for consumers [...] Read more.
Cloud adoption necessitates relinquishing data control to cloud service providers (CSPs), involving diverse stakeholders with varying security and privacy (S&P) needs and responsibilities. Building upon previously published work, this paper addresses the persistent challenge of a lack of standardized, transparent methods for consumers to select and quantify appropriate S&P measures. This work introduces a stakeholder-centric methodology to identify and address S&P challenges, enabling stakeholders to assess their cloud service protection capabilities. The primary contribution lies in the development of new classifications and updated considerations, along with tailored S&P features designed to accommodate specific service models, deployment models, and stakeholder roles. This novel approach shifts from data or infrastructure perspectives to comprehensively account for S&P issues arising from stakeholder interactions and conflicts. A prototype framework, utilizing a rule-based taxonomy and the Goal–Question–Metric (GQM) method, recommends essential S&P attributes. Multi-criteria decision-making (MCDM) is employed to measure protection levels and facilitate benchmarking. The evaluation of the implemented prototype demonstrates the framework’s effectiveness in recommending and consistently measuring security features. This work aims to reduce consumer apprehension regarding cloud migration, improve transparency between consumers and CSPs, and foster competitive transparency among CSPs. Full article
(This article belongs to the Special Issue Internet of Things (IoT) and Cloud/Edge Computing)
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Review

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18 pages, 1443 KB  
Review
Empathy by Design: Reframing the Empathy Gap Between AI and Humans in Mental Health Chatbots
by Alastair Howcroft and Holly Blake
Information 2025, 16(12), 1074; https://doi.org/10.3390/info16121074 - 4 Dec 2025
Cited by 9 | Viewed by 7901
Abstract
Artificial intelligence (AI) chatbots are now embedded across therapeutic contexts, from the United Kingdom’s National Health Service (NHS) Talking Therapies to widely used platforms like ChatGPT. Whether welcomed or not, these systems are increasingly used for both patient care and everyday support, sometimes [...] Read more.
Artificial intelligence (AI) chatbots are now embedded across therapeutic contexts, from the United Kingdom’s National Health Service (NHS) Talking Therapies to widely used platforms like ChatGPT. Whether welcomed or not, these systems are increasingly used for both patient care and everyday support, sometimes even replacing human contact. Their capacity to convey empathy strongly influences how people experience and benefit from them. However, current systems often create an “AI empathy gap”, where interactions feel impersonal and superficial compared to those with human practitioners. This paper, presented as a critical narrative review, cautiously challenges the prevailing narrative that empathy is a uniquely human skill that AI cannot replicate. We argue this belief can stem from an unfair comparison: evaluating generic AIs against an idealised human practitioner. We reframe capabilities seen as exclusively human, such as building bonds through long-term memory and personalisation, not as insurmountable barriers but as concrete design targets. We also discuss the critical architectural and privacy trade-offs between cloud and on-device (edge) solutions. Accordingly, we propose a conceptual framework to meet these targets. It integrates three key technologies: Retrieval-Augmented Generation (RAG) for long-term memory; feedback-driven adaptation for real-time emotional tuning; and lightweight adapter modules for personalised conversational styles. This framework provides a path toward systems that users perceive as genuinely empathic, rather than ones that merely mimic supportive language. While AI cannot experience emotional empathy, it can model cognitive empathy and simulate affective and compassionate responses in coordinated ways at the behavioural level. However, because these systems lack conscious, autonomous ‘helping’ intentions, these design advancements must be considered alongside careful ethical and regulatory safeguards. Full article
(This article belongs to the Special Issue Internet of Things (IoT) and Cloud/Edge Computing)
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