Sensors 2023, 23(5), 2448; https://doi.org/10.3390/s23052448 - 22 Feb 2023
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Abstract
This topical collection focuses on applying sensors and communications technologies for social good [...]
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Topical Collection "Sensors and Communications for the Social Good"
A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Sensor Networks".
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Editors
Dipartimento di Matematica, Università degli Studi di Padova, 35131 Padova, Italy
Interests: wireless networks; web squared; online entertainment; mobile applications
Special Issues, Collections and Topics in MDPI journals
Interests: wireless networks; web squared; online entertainment; mobile applications
Special Issues, Collections and Topics in MDPI journals
Department of Mathematics, University of Padua, Via Trieste, 35131 Padova, Italy
Interests: multimedia document and application design; mobile-context-aware information systems; distributed multimedia modeling
Interests: multimedia document and application design; mobile-context-aware information systems; distributed multimedia modeling
Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: mobile networks and systems; internet of things
Special Issues, Collections and Topics in MDPI journals
Interests: mobile networks and systems; internet of things
Special Issues, Collections and Topics in MDPI journals
Topical Collection Information
Dear Colleagues,
This Topical Collection focuses on the application of IT technologies to social good. Social good is typically defined as an action that provides some sort of benefit to the general public. In this case, internet connection, education, and healthcare are all good examples of social goods. However, new media innovations and the explosion of online communities have added new meaning to the term. Social good is now about global citizens uniting to unlock the potential of individuals, technology, and collaboration to create a positive societal impact.
Prof. Dr. Claudio Palazzi
Prof. Dr. Ombretta Gaggi
Prof. Dr. Pietro Manzoni
Collection Editors
Manuscript Submission Information
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Keywords
- IT for education
- data science
- health and social care
- citizen science
- decentralized approaches to IT
- frugal solutions for IT
- IT for smart living
Sensors and Communications for the Social Good
Effects of the Uncertainty of Interpersonal Communications on Behavioral Responses of the Participants in an Immersive Virtual Reality Experience: A Usability Study
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Sensors 2023, 23(4), 2148; https://doi.org/10.3390/s23042148 - 14 Feb 2023
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Two common difficulties which people face in their daily lives are managing effective communication with others and dealing with what makes them feel uncertain. Past research highlights that the result of not being able to handle these difficulties influences people’s performance in the
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Two common difficulties which people face in their daily lives are managing effective communication with others and dealing with what makes them feel uncertain. Past research highlights that the result of not being able to handle these difficulties influences people’s performance in the task at hand substantially, especially in the context of a social environment such as a workplace. Perceived uncertainty of information is a key influential factor in this regard, with effects on the quality of the information transfer between sender and receiver. Uncertainty of information can be induced into the communication system in three ways: when there is any kind of information deficit that makes the target message unclear for the receiver, when there are some requested changes that could not be predicted by the receiver, and when the content of the message is so interconnected and complex that it limits understanding. Since uncertainty is an inseparable feature of our lives, studying the effects that different levels of it have on individuals and how individuals nevertheless accomplish the tasks of daily living is of high importance. Modern technologies such as immersive virtual reality (VR) have been successful in providing effective platforms to support human behavioral and social well-being studies. In this paper, we suggest the design, development, and evaluation of an immersive VR serious game platform to study behavioral responses to the uncertain features of interpersonal communications. In addition, we report the result of a within-subject user study with 17 participants aged between 20 and 35 and their behavioral responses to two levels of uncertainty with subjective and objective measures. The results convey that the application successfully and meaningfully measured some behavioral responses related to exposure to different levels of uncertainty and overall, the participants were satisfied with the experience.
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Indoor Spatiotemporal Contact Analytics Using Landmark-Aided Pedestrian Dead Reckoning on Smartphones
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Sensors 2023, 23(1), 113; https://doi.org/10.3390/s23010113 - 22 Dec 2022
Cited by 1 | Viewed by 976
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Due to the prevalence of COVID-19, providing safe environments and reducing the risks of virus exposure play pivotal roles in our daily lives. Contact tracing is a well-established and widely-used approach to track and suppress the spread of viruses. Most digital contact tracing
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Due to the prevalence of COVID-19, providing safe environments and reducing the risks of virus exposure play pivotal roles in our daily lives. Contact tracing is a well-established and widely-used approach to track and suppress the spread of viruses. Most digital contact tracing systems can detect direct face-to-face contact based on estimated proximity, without quantifying the exposed virus concentration. In particular, they rarely allow for quantitative analysis of indirect environmental exposure due to virus survival time in the air and constant airborne transmission. In this work, we propose an indoor spatiotemporal contact awareness framework (iSTCA), which explicitly considers the self-containing quantitative contact analytics approach with spatiotemporal information to provide accurate awareness of the virus quanta concentration in different origins at various times. Smartphone-based pedestrian dead reckoning (PDR) is employed to precisely detect the locations and trajectories for distance estimation and time assessment without the need to deploy extra infrastructure. The PDR technique we employ calibrates the accumulative error by identifying spatial landmarks automatically. We utilized a custom deep learning model composed of bidirectional long short-term memory (Bi-LSTM) and multi-head convolutional neural networks (CNNs) for extracting the local correlation and long-term dependency to recognize landmarks. By considering the spatial distance and time difference in an integrated manner, we can quantify the virus quanta concentration of the entire indoor environment at any time with all contributed virus particles. We conducted an extensive experiment based on practical scenarios to evaluate the performance of the proposed system, showing that the average positioning error is reduced to less than 0.7 m with high confidence and demonstrating the validity of our system for the virus quanta concentration quantification involving virus movement in a complex indoor environment.
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Decentralized Personal Data Marketplaces: How Participation in a DAO Can Support the Production of Citizen-Generated Data
Sensors 2022, 22(16), 6260; https://doi.org/10.3390/s22166260 - 20 Aug 2022
Cited by 2 | Viewed by 1296
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Big Tech companies operating in a data-driven economy offer services that rely on their users’ personal data and usually store this personal information in “data silos” that prevent transparency about their use and opportunities for data sharing for public interest. In this paper,
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Big Tech companies operating in a data-driven economy offer services that rely on their users’ personal data and usually store this personal information in “data silos” that prevent transparency about their use and opportunities for data sharing for public interest. In this paper, we present a solution that promotes the development of decentralized personal data marketplaces, exploiting the use of Distributed Ledger Technologies (DLTs), Decentralized File Storages (DFS) and smart contracts for storing personal data and managing access control in a decentralized way. Moreover, we focus on the issue of a lack of efficient decentralized mechanisms in DLTs and DFSs for querying a certain type of data. For this reason, we propose the use of a hypercube-structured Distributed Hash Table (DHT) on top of DLTs, organized for efficient processing of multiple keyword-based queries on the ledger data. We test our approach with the implementation of a use case regarding the creation of citizen-generated data based on direct participation and the involvement of a Decentralized Autonomous Organization (DAO). The performance evaluation demonstrates the viability of our approach for decentralized data searches, distributed authorization mechanisms and smart contract exploitation.
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A Multi-Resident Number Estimation Method for Smart Homes
Sensors 2022, 22(13), 4823; https://doi.org/10.3390/s22134823 - 25 Jun 2022
Cited by 1 | Viewed by 879
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Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There
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Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There is therefore the need to find methodologies to identify if, when, and how long the person is in the company of other people (possibly, also considering the number). The challenge is to address this task in poorly sensorized apartments, with non-intrusive sensors that are typically wireless and can only provide local and simple information. The proposed method addresses technological issues, such as PIR (Passive InfraRed) blind times, topological issues, such as sensor interference due to the inability to separate detection areas, and algorithmic issues. The house is modeled as a graph to constrain transitions between adjacent rooms. Each room is associated with a set of values, for each identified person. These values decay over time and represent the probability that each person is still in the room. Because the used sensors cannot determine the number of people, the approach is based on a multi-branch inference that, over time, differentiates the movements in the apartment and estimates the number of people. The proposed algorithm has been validated with real data obtaining an accuracy of 86.8%.
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Sensoring the Neck: Classifying Movements and Actions with a Neck-Mounted Wearable Device
Sensors 2022, 22(12), 4313; https://doi.org/10.3390/s22124313 - 07 Jun 2022
Cited by 1 | Viewed by 1100
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Sensor technology that captures information from a user’s neck region can enable a range of new possibilities, including less intrusive mobile software interfaces. In this work, we investigate the feasibility of using a single inexpensive flex sensor mounted at the neck to capture
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Sensor technology that captures information from a user’s neck region can enable a range of new possibilities, including less intrusive mobile software interfaces. In this work, we investigate the feasibility of using a single inexpensive flex sensor mounted at the neck to capture information about head gestures, about mouth movements, and about the presence of audible speech. Different sensor sizes and various sensor positions on the neck are experimentally evaluated. With data collected from experiments performed on the finalized prototype, a classification accuracy of 91% in differentiating common head gestures, a classification accuracy of 63% in differentiating mouth movements, and a classification accuracy of 83% in speech detection are achieved.
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Novel Perspectives for the Management of Multilingual and Multialphabetic Heritages through Automatic Knowledge Extraction: The DigitalMaktaba Approach
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Sensors 2022, 22(11), 3995; https://doi.org/10.3390/s22113995 - 25 May 2022
Cited by 4 | Viewed by 1234
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The linguistic and social impact of multiculturalism can no longer be neglected in any sector, creating the urgent need of creating systems and procedures for managing and sharing cultural heritages in both supranational and multi-literate contexts. In order to achieve this goal, text
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The linguistic and social impact of multiculturalism can no longer be neglected in any sector, creating the urgent need of creating systems and procedures for managing and sharing cultural heritages in both supranational and multi-literate contexts. In order to achieve this goal, text sensing appears to be one of the most crucial research areas. The long-term objective of the DigitalMaktaba project, born from interdisciplinary collaboration between computer scientists, historians, librarians, engineers and linguists, is to establish procedures for the creation, management and cataloguing of archival heritage in non-Latin alphabets. In this paper, we discuss the currently ongoing design of an innovative workflow and tool in the area of text sensing, for the automatic extraction of knowledge and cataloguing of documents written in non-Latin languages (Arabic, Persian and Azerbaijani). The current prototype leverages different OCR, text processing and information extraction techniques in order to provide both a highly accurate extracted text and rich metadata content (including automatically identified cataloguing metadata), overcoming typical limitations of current state of the art approaches. The initial tests provide promising results. The paper includes a discussion of future steps (e.g., AI-based techniques further leveraging the extracted data/metadata and making the system learn from user feedback) and of the many foreseen advantages of this research, both from a technical and a broader cultural-preservation and sharing point of view.
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LIPSHOK: LIARA Portable Smart Home Kit
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Sensors 2022, 22(8), 2829; https://doi.org/10.3390/s22082829 - 07 Apr 2022
Cited by 1 | Viewed by 1032
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Several smart home architecture implementations have been proposed in the last decade. These architectures are mostly deployed in laboratories or inside real habitations built for research purposes to enable the use of ambient intelligence using a wide variety of sensors, actuators and machine
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Several smart home architecture implementations have been proposed in the last decade. These architectures are mostly deployed in laboratories or inside real habitations built for research purposes to enable the use of ambient intelligence using a wide variety of sensors, actuators and machine learning algorithms. However, the major issues for most related smart home architectures are their price, proprietary hardware requirements and the need for highly specialized personnel to deploy such systems. To tackle these challenges, lighter forms of smart home architectures known as smart homes in a box (SHiB) have been proposed. While SHiB remain an encouraging first step towards lightweight yet affordable solutions, they still suffer from few drawbacks. Indeed, some of these kits lack hardware support for some technologies, and others do not include enough sensors and actuators to cover most smart homes’ requirements. Thus, this paper introduces the LIARA Portable Smart Home Kit (LIPSHOK). It has been designed to provide an affordable SHiB solution that anyone is able to install in an existing home. Moreover, LIPSHOK is a generic kit that includes a total of four specialized sensor modules that were introduced independently, as our laboratory has been working on their development over the last few years. This paper first provides a summary of each of these modules and their respective benefits within a smart home context. Then, it mainly focus on the introduction of the LIPSHOK architecture that provides a framework to unify the use of the proposed sensors thanks to a common modular infrastructure capable of managing heterogeneous technologies. Finally, we compare our work to the existing SHiB kit solutions and outline that it offers a more affordable, extensible and scalable solution whose resources are distributed under an open-source license.
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A Digital Twin Decision Support System for the Urban Facility Management Process
Sensors 2021, 21(24), 8460; https://doi.org/10.3390/s21248460 - 18 Dec 2021
Cited by 12 | Viewed by 2537
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The ever increasing pace of IoT deployment is opening the door to concrete implementations of smart city applications, enabling the large-scale sensing and modeling of (near-)real-time digital replicas of physical processes and environments. This digital replica could serve as the basis of a
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The ever increasing pace of IoT deployment is opening the door to concrete implementations of smart city applications, enabling the large-scale sensing and modeling of (near-)real-time digital replicas of physical processes and environments. This digital replica could serve as the basis of a decision support system, providing insights into possible optimizations of resources in a smart city scenario. In this article, we discuss an extension of a prior work, presenting a detailed proof-of-concept implementation of a Digital Twin solution for the Urban Facility Management (UFM) process. The Interactive Planning Platform for City District Adaptive Maintenance Operations (IPPODAMO) is a distributed geographical system, fed with and ingesting heterogeneous data sources originating from different urban data providers. The data are subject to continuous refinements and algorithmic processes, used to quantify and build synthetic indexes measuring the activity level inside an area of interest. IPPODAMO takes into account potential interference from other stakeholders in the urban environment, enabling the informed scheduling of operations, aimed at minimizing interference and the costs of operations.
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A 5G-Enabled Smart Waste Management System for University Campus
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Sensors 2021, 21(24), 8278; https://doi.org/10.3390/s21248278 - 10 Dec 2021
Cited by 11 | Viewed by 3869
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Future university campuses will be characterized by a series of novel services enabled by the vision of Internet of Things, such as smart parking and smart libraries. In this paper, we propose a complete solution for a smart waste management system with the
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Future university campuses will be characterized by a series of novel services enabled by the vision of Internet of Things, such as smart parking and smart libraries. In this paper, we propose a complete solution for a smart waste management system with the purpose of increasing the recycling rate in the campus and provide better management of the entire waste cycle. The system is based on a prototype of a smart waste bin, able to accurately classify pieces of trash typically produced in the campus premises with a hybrid sensor/image classification algorithm, as well as automatically segregate the different waste materials. We discuss the entire design of the system prototype, from the analysis of requirements to the implementation details and we evaluate its performance in different scenarios. Finally, we discuss advanced application functionalities built around the smart waste bin, such as optimized maintenance scheduling.
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Algorithms for Smooth, Safe and Quick Routing on Sensor-Equipped Grid Networks
Sensors 2021, 21(24), 8188; https://doi.org/10.3390/s21248188 - 08 Dec 2021
Cited by 2 | Viewed by 1744
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Automation plays an important role in modern transportation and handling systems, e.g., to control the routes of aircraft and ground service equipment in airport aprons, automated guided vehicles in port terminals or in public transportation, handling robots in automated factories, drones in warehouse
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Automation plays an important role in modern transportation and handling systems, e.g., to control the routes of aircraft and ground service equipment in airport aprons, automated guided vehicles in port terminals or in public transportation, handling robots in automated factories, drones in warehouse picking operations, etc. Information technology provides hardware and software (e.g., collision detection sensors, routing and collision avoidance logic) that contribute to safe and efficient operations, with relevant social benefits in terms of improved system performance and reduced accident rates. In this context, we address the design of efficient collision-free routes in a minimum-size routing network. We consider a grid and a set of vehicles, each moving from the bottom of the origin column to the top of the destination column. Smooth nonstop paths are required, without collisions nor deviations from shortest paths, and we investigate the minimum number of horizontal lanes allowing for such routing. The problem is known as fleet quickest routing problem on grids. We propose a mathematical formulation solved, for small instances, through standard solvers. For larger instances, we devise heuristics that, based on known combinatorial properties, define priorities, and design collision-free routes. Experiments on random instances show that our algorithms are able to quickly provide good quality solutions.
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Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations
Sensors 2021, 21(23), 7998; https://doi.org/10.3390/s21237998 - 30 Nov 2021
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The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design
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The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a model for evaluating teaching and evaluation processes. The study objective presented in this paper was to develop a model for the evaluation system called the learning analytics and evaluation model (LAEM). We also validated a software instrument we designed called the EvalMathI system, which is to be used in the evaluation system and was developed and tested during the pandemic. The optimization of the evaluation process was accomplished by including and integrating the dashboard model in a responsive panel. With the dashboard from EvalMathI, six online courses were monitored in the 2019/2020 and 2020/2021 academic years, and for each of the six monitored courses, the evaluation of the curricula was performed through the analyzed parameters by highlighting the percentage achieved by each course on various components, such as content, adaptability, skills, and involvement. In addition, after collecting the data through interview guides, the authors were able to determine the extent to which online education during the COVID 19 pandemic has influenced the educational process. Through the developed model, the authors also found software tools to solve some of the problems raised by teaching and evaluation in the ERT environment.
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