Digital Society: Interdisciplinary Insights and Applications of Wireless Connectivity

A special issue of Informatics (ISSN 2227-9709).

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 2860

Special Issue Editors


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Guest Editor
Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Mexico
Interests: wireless sensor networks; robotics for healthcare; information security; energy models; blockchain
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Special Issue Information

Dear Colleagues,

Wireless communication systems have evolved into ubiquitous tools that seamlessly integrate with various interdisciplinary applications. They have redefined how we communicate, share information, and access services. In society, wireless communication has fostered connectivity on a global scale, enabling instant communication, remote work, and the proliferation of smart devices. In informatics, these technologies have expanded the capabilities of computing systems, allowing for the collection and transmission of vast amounts of data, fueling advancements in artificial intelligence, cloud computing, and the Internet of Things. Furthermore, they have revolutionized healthcare through telemedicine and remote monitoring, thus optimizing patient care. As these wireless communication systems continue to reshape our daily lives across various fields, addressing security and privacy aspects has become paramount to ensure the integrity and confidentiality of the vast amounts of data being transmitted and shared. In the context of human–computer interactions, wireless systems serve as the foundation for intuitive and responsive interfaces, enabling natural interactions between individuals and digital devices. Moreover, in medical informatics, wireless technologies play a pivotal role in remote patient monitoring, facilitating the real-time collection and transmission of vital health data, thereby revolutionizing healthcare delivery. Within health informatics, these systems support the secure exchange of medical information, contributing to data-driven decision making and the improvement of healthcare outcomes. Social informatics benefit from wireless communication by fostering connectivity, enabling instant communication and facilitating the sharing of information, which is integral to modern social interactions. In essence, wireless communication systems are the linchpin that underpins the seamless integration of technology into our daily lives across these diverse fields, enhancing user experiences, expanding healthcare capabilities, and shaping the way we interact with and benefit from digital technology.

Prof. Dr. Carolina Del Valle Soto
Prof. Dr. Ramiro Velázquez
Guest Editors

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Keywords

  • wireless communication systems
  • ubiquitous tools
  • human–computer interaction
  • medical informatics
  • smart devices proliferation
  • internet of things

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Published Papers (1 paper)

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Research

14 pages, 11276 KiB  
Article
Uncovering the Limitations and Insights of Packet Status Prediction Models in IEEE 802.15.4-Based Wireless Networks and Insights from Data Science
by Mariana Ávalos-Arce, Heráclito Pérez-Díaz, Carolina Del-Valle-Soto and Ramon A. Briseño
Informatics 2024, 11(1), 7; https://doi.org/10.3390/informatics11010007 - 26 Jan 2024
Viewed by 2272
Abstract
Wireless networks play a pivotal role in various domains, including industrial automation, autonomous vehicles, robotics, and mobile sensor networks. This research investigates the critical issue of packet loss in modern wireless networks and aims to identify the conditions within a network’s environment that [...] Read more.
Wireless networks play a pivotal role in various domains, including industrial automation, autonomous vehicles, robotics, and mobile sensor networks. This research investigates the critical issue of packet loss in modern wireless networks and aims to identify the conditions within a network’s environment that lead to such losses. We propose a packet status prediction model for data packets that travel through a wireless network based on the IEEE 802.15.4 standard and are exposed to five different types of interference in a controlled experimentation environment. The proposed model focuses on the packetization process and its impact on network robustness. This study explores the challenges posed by packet loss, particularly in the context of interference, and puts forth the hypothesis that specific environmental conditions are linked to packet loss occurrences. The contribution of this work lies in advancing our understanding of the conditions leading to packet loss in wireless networks. Data are retrieved with a single CC2531 USB Dongle Packet Sniffer, whose pieces of information on packets become the features of each packet from which the classifier model will gather the training data with the aim of predicting whether a packet will unsuccessfully arrive at its destination. We found that interference causes more packet loss than that caused by various devices using a WiFi communication protocol simultaneously. In addition, we found that the most important predictors are network strength and packet size; low network strength tends to lead to more packet loss, especially for larger packets. This study contributes to the ongoing efforts to predict and mitigate packet loss, emphasizing the need for adaptive models in dynamic wireless environments. Full article
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