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IoT and Smart Homes

A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Sensor Networks".

Viewed by 26516

Editors

Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133 Milan, Italy
Interests: specification; design and automatic generation of complex Web applications; smart homes; AAL
Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133 Milan, Italy
Interests: Ambient Intelligence; Ubiquitous Computing; Home Automation; Smart Homes; ageing; behavior; monitoring

Topical Collection Information

Dear Colleagues,

IoT networks connect sensors, actuators, and smart devices. In smart homes, they were initially used for home automation purposes, but they have been naturally extended to also track users so they can automate their actions, to optimize management of the house, and to improve users’ quality of life.

Possible topics include (but are not limited to): 

  • Ambient intelligence
  • Ambient assisted living
  • Edge and cloud computing in IoT-based smart homes
  • Network architectures in smart home applications
  • Energy management in smart homes
  • Smart home automation
  • Smart homes/smart environments
  • Smart homes for the elderly and fragile people
  • Privacy and security in IoT-based smart homes
  • Interoperability of IoT solutions for smart homes
  • Independent living and quality of life
  • Human Interaction in IoT for smart homes
  • AI and analytics in smart homes
  • New smart devices in IoT for smart homes
  • Localization based on IoT in smart homes
  • Tracking and Prediction of behaviors in smart homes
  • Applications and solutions for IoT-based smart homes
  • IoT apps in smart home systems

Prof. Dr. Sara Comai
Dr. Fabio Salice
Collection Editors

Manuscript Submission Information

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Published Papers (9 papers)

2023

Jump to: 2022, 2021

19 pages, 2031 KiB  
Article
Development of a Framework for the Communication System Based on KNX for an Interactive Space for UX Evaluation
by Ariel A. Lopez-Aguilar, M. Rogelio Bustamante-Bello, Sergio A. Navarro-Tuch and Arturo Molina
Sensors 2023, 23(23), 9570; https://doi.org/10.3390/s23239570 - 02 Dec 2023
Viewed by 906
Abstract
Domotics (Home Automation) aims to improve the quality of life of people by integrating intelligent systems within inhabitable spaces. While traditionally associated with smart home systems, these technologies have potential for User Experience (UX) research. By emulating environments to test products and services, [...] Read more.
Domotics (Home Automation) aims to improve the quality of life of people by integrating intelligent systems within inhabitable spaces. While traditionally associated with smart home systems, these technologies have potential for User Experience (UX) research. By emulating environments to test products and services, and integrating non-invasive user monitoring tools for emotion recognition, an objective UX evaluation can be performed. To achieve this objective, a testing booth was built and instrumented with devices based on KNX, an international standard for home automation, to conduct experiments and ensure replicability. A framework was designed based on Python to synchronize KNX systems with emotion recognition tools; the synchronization of these data allows finding patterns during the interaction process. To evaluate this framework, an experiment was conducted in a simulated laundry room within the testing booth to analyze the emotional responses of participants while interacting with prototypes of new detergent bottles. Emotional responses were contrasted with traditional questionnaires to determine the viability of using non-invasive methods. Using emulated environments alongside non-invasive monitoring tools allowed an immersive experience for participants. These results indicated that the testing booth can be implemented for a robust UX evaluation methodology. Full article
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2022

Jump to: 2023, 2021

21 pages, 5892 KiB  
Review
Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack
by Mohammad Ali Nassiri Abrishamchi, Anazida Zainal, Fuad A. Ghaleb, Sultan Noman Qasem and Abdullah M. Albarrak
Sensors 2022, 22(21), 8564; https://doi.org/10.3390/s22218564 - 07 Nov 2022
Cited by 6 | Viewed by 2841
Abstract
Smart home technologies have attracted more users in recent years due to significant advancements in their underlying enabler components, such as sensors, actuators, and processors, which are spreading in various domains and have become more affordable. However, these IoT-based solutions are prone to [...] Read more.
Smart home technologies have attracted more users in recent years due to significant advancements in their underlying enabler components, such as sensors, actuators, and processors, which are spreading in various domains and have become more affordable. However, these IoT-based solutions are prone to data leakage; this privacy issue has motivated researchers to seek a secure solution to overcome this challenge. In this regard, wireless signal eavesdropping is one of the most severe threats that enables attackers to obtain residents’ sensitive information. Even if the system encrypts all communications, some cyber attacks can still steal information by interpreting the contextual data related to the transmitted signals. For example, a “fingerprint and timing-based snooping (FATS)” attack is a side-channel attack (SCA) developed to infer in-home activities passively from a remote location near the targeted house. An SCA is a sort of cyber attack that extracts valuable information from smart systems without accessing the content of data packets. This paper reviews the SCAs associated with cyber–physical systems, focusing on the proposed solutions to protect the privacy of smart homes against FATS attacks in detail. Moreover, this work clarifies shortcomings and future opportunities by analyzing the existing gaps in the reviewed methods. Full article
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22 pages, 2920 KiB  
Article
Towards a Policy Development Methodology for Human-Centred IoT Collectives
by Amna Batool, Seng W. Loke, Niroshinie Fernando and Jonathan Kua
Sensors 2022, 22(19), 7401; https://doi.org/10.3390/s22197401 - 29 Sep 2022
Viewed by 1516
Abstract
Embedding ethical concepts into smart Internet-connected devices and making them behave in a more human-centred manner, i.e., ethically and in a socially acceptable manner, has received significant attention in the software industry. To make smart devices behave in more human-centered manners, it is [...] Read more.
Embedding ethical concepts into smart Internet-connected devices and making them behave in a more human-centred manner, i.e., ethically and in a socially acceptable manner, has received significant attention in the software industry. To make smart devices behave in more human-centered manners, it is important to develop a methodology for defining smart devices’ key roles and mapping them with socio-ethical and administrative policies. This paper proposes a policy development methodology for making smart devices more human-centred by following its four phases i.e., concept development, defining and mapping policies, implementing the processing of policies, and deploying the devices. The suggested methodology may be used in a variety of situations where smart devices interact with people. For illustration, the proposed methodology has been applied to three different settings, including a supermarket, a children’s hospital, and early learning centers, where each phase defined in the methodology has been followed. The application of the methodology to smart internet-connected devices, including robots, smart cameras, and smart speakers, has shown significant results. It has been observed that the devices behave in more human-centric ways while performing their core functions, adhering to socio-ethical policies. Full article
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17 pages, 2116 KiB  
Article
Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home
by Ashleigh Philip, Shama Naz Islam, Nicholas Phillips and Adnan Anwar
Sensors 2022, 22(19), 7102; https://doi.org/10.3390/s22197102 - 20 Sep 2022
Cited by 4 | Viewed by 1807
Abstract
This paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air conditioning [...] Read more.
This paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air conditioning loads to these periods to reduce the electricity demand. In particular, we propose a multi-stage approach which maximises the utilisation of renewable energy at the first stage to satisfy air conditioning loads, and then schedules residual energy consumption of these loads to low price periods at the second stage. The proposed approach is investigated for the temperature and renewable generation data of NSW, Australia, over the period 2012–2013. It is shown that the approach developed can significantly reduce the energy consumption and cost associated with AC operation for nearly all days in summer when cooling is required. Specifically, the proposed approach was found to achieve a 24% cost saving in comparison to the no pre-cooling case for the highest average temperature day in January, 2013. The analysis also demonstrated that the proposed scheme performed better when the thermal insulation levels in the smart home are higher. However, the optimal pre-cooling scheme can still achieve reduced energy costs under lower thermal insulation conditions compared to the no pre-cooling case. Full article
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16 pages, 4209 KiB  
Article
Edge-Based Transfer Learning for Classroom Occupancy Detection in a Smart Campus Context
by Lorenzo Monti, Rita Tse, Su-Kit Tang, Silvia Mirri, Giovanni Delnevo, Vittorio Maniezzo and Paola Salomoni
Sensors 2022, 22(10), 3692; https://doi.org/10.3390/s22103692 - 12 May 2022
Cited by 6 | Viewed by 2315
Abstract
Studies and systems that are aimed at the identification of the presence of people within an indoor environment and the monitoring of their activities and flows have been receiving more attention in recent years, specifically since the beginning of the COVID-19 pandemic. This [...] Read more.
Studies and systems that are aimed at the identification of the presence of people within an indoor environment and the monitoring of their activities and flows have been receiving more attention in recent years, specifically since the beginning of the COVID-19 pandemic. This paper proposes an approach for people counting that is based on the use of cameras and Raspberry Pi platforms, together with an edge-based transfer learning framework that is enriched with specific image processing strategies, with the aim of this approach being adopted in different indoor environments without the need for tailored training phases. The system was deployed on a university campus, which was chosen as the case study. The proposed system was able to work in classrooms with different characteristics. This paper reports a proposed architecture that could make the system scalable and privacy compliant and the evaluation tests that were conducted in different types of classrooms, which demonstrate the feasibility of this approach. Overall, the system was able to count the number of people in classrooms with a maximum mean absolute error of 1.23. Full article
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2021

Jump to: 2023, 2022

16 pages, 8930 KiB  
Article
High-Efficiency Multi-Sensor System for Chair Usage Detection
by Alessandro Baserga, Federico Grandi, Andrea Masciadri, Sara Comai and Fabio Salice
Sensors 2021, 21(22), 7580; https://doi.org/10.3390/s21227580 - 15 Nov 2021
Viewed by 1976
Abstract
Recognizing Activities of Daily Living (ADL) or detecting falls in domestic environments require monitoring the movements and positions of a person. Several approaches use wearable devices or cameras, especially for fall detection, but they are considered intrusive by many users. To support such [...] Read more.
Recognizing Activities of Daily Living (ADL) or detecting falls in domestic environments require monitoring the movements and positions of a person. Several approaches use wearable devices or cameras, especially for fall detection, but they are considered intrusive by many users. To support such activities in an unobtrusive way, ambient-based solutions are available (e.g., based on PIRs, contact sensors, etc.). In this paper, we focus on the problem of sitting detection exploiting only unobtrusive sensors. In fact, sitting detection can be useful to understand the position of the user in many activities of the daily routines. While identifying sitting/lying on a sofa or bed is reasonably simple with pressure sensors, detecting whether a person is sitting on a chair is an open problem due to the natural chair position volatility. This paper proposes a reliable, not invasive and energetically sustainable system that can be used on chairs already present in the home. In particular, the proposed solution fuses the data of an accelerometer and a capacitive coupling sensor to understand if a person is sitting or not, discriminating the case of objects left on the chair. The results obtained in a real environment setting show an accuracy of 98.6% and a precision of 95%. Full article
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23 pages, 2526 KiB  
Article
On Supporting University Communities in Indoor Wayfinding: An Inclusive Design Approach
by Catia Prandi, Giovanni Delnevo, Paola Salomoni and Silvia Mirri
Sensors 2021, 21(9), 3134; https://doi.org/10.3390/s21093134 - 30 Apr 2021
Cited by 10 | Viewed by 3594
Abstract
Mobility can be defined as the ability of people to move, live and interact with the space. In this context, indoor mobility, in terms of indoor localization and wayfinding, is a relevant topic due to the challenges it presents, in comparison with outdoor [...] Read more.
Mobility can be defined as the ability of people to move, live and interact with the space. In this context, indoor mobility, in terms of indoor localization and wayfinding, is a relevant topic due to the challenges it presents, in comparison with outdoor mobility, where GPS is hardly exploited. Knowing how to move in an indoor environment can be crucial for people with disabilities, and in particular for blind users, but it can provide several advantages also to any person who is moving in an unfamiliar place. Following this line of thought, we employed an inclusive by design approach to implement and deploy a system that comprises an Internet of Things infrastructure and an accessible mobile application to provide wayfinding functions, targeting the University community. As a real word case study, we considered the University of Bologna, designing a system able to be deployed in buildings with different configurations and settings, considering also historical buildings. The final system has been evaluated in three different scenarios, considering three different target audiences (18 users in total): i. students with disabilities (i.e., visual and mobility impairments); ii. campus students; and iii. visitors and tourists. Results reveal that all the participants enjoyed the provided functions and the indoor localization strategy was fine enough to provide a good wayfinding experience. Full article
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22 pages, 2870 KiB  
Article
Understanding Social Behaviour in a Health-Care Facility from Localization Data: A Case Study
by Gloria Bellini, Marco Cipriano, Sara Comai, Nicola De Angeli, Jacopo Pio Gargano, Matteo Gianella, Gianluca Goi, Giovanni Ingrao, Andrea Masciadri, Gabriele Rossi and Fabio Salice
Sensors 2021, 21(6), 2147; https://doi.org/10.3390/s21062147 - 18 Mar 2021
Cited by 11 | Viewed by 3987
Abstract
The most frequent form of dementia is Alzheimer’s Disease (AD), a severe progressive neurological pathology in which the main cognitive functions of an individual are compromised. Recent studies have found that loneliness and living in isolation are likely to cause an acceleration in [...] Read more.
The most frequent form of dementia is Alzheimer’s Disease (AD), a severe progressive neurological pathology in which the main cognitive functions of an individual are compromised. Recent studies have found that loneliness and living in isolation are likely to cause an acceleration in the cognitive decline associated with AD. Therefore, understanding social behaviours of AD patients is crucial to promote sociability, thus delaying cognitive decline, preserving independence, and providing a good quality of life. In this work, we analyze the localization data of AD patients living in assisted care homes to gather insights about the social dynamics among them. We use localization data collected by a system based on iBeacon technology comprising two components: a network of antennas scattered throughout the facility and a Bluetooth bracelet worn by the patients. We redefine the Relational Index to capture wandering and casual encounters, these being common phenomena among AD patients, and use the notions of Relational and Popularity Indexes to model, visualize and understand the social behaviour of AD patients. We leverage the data analyses to build predictive tools and applications to enhance social activities scheduling and sociability monitoring and promotion, with the ultimate aim of providing patients with a better quality of life. Predictions and visualizations act as a support for caregivers in activity planning to maximize treatment effects and, hence, slow down the progression of Alzheimer’s disease. We present the Community Behaviour Prediction Table (CBPT), a tool to visualize the estimated values of sociability among patients and popularity of places within a facility. Finally, we show the potential of the system by analyzing the Coronavirus Disease 2019 (COVID-19) lockdown time-frame between February and June 2020 in a specific facility. Through the use of the indexes, we evaluate the effects of the pandemic on the behaviour of the residents, observing no particular impact on sociability even though social distancing was put in place. Full article
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24 pages, 550 KiB  
Article
A Secure and Lightweight Authentication Protocol for IoT-Based Smart Homes
by JiHyeon Oh, SungJin Yu, JoonYoung Lee, SeungHwan Son, MyeongHyun Kim and YoungHo Park
Sensors 2021, 21(4), 1488; https://doi.org/10.3390/s21041488 - 21 Feb 2021
Cited by 50 | Viewed by 5940
Abstract
With the information and communication technologies (ICT) and Internet of Things (IoT) gradually advancing, smart homes have been able to provide home services to users. The user can enjoy a high level of comfort and improve his quality of life by using home [...] Read more.
With the information and communication technologies (ICT) and Internet of Things (IoT) gradually advancing, smart homes have been able to provide home services to users. The user can enjoy a high level of comfort and improve his quality of life by using home services provided by smart devices. However, the smart home has security and privacy problems, since the user and smart devices communicate through an insecure channel. Therefore, a secure authentication protocol should be established between the user and smart devices. In 2020, Xiang and Zheng presented a situation-aware protocol for device authentication in smart grid-enabled smart home environments. However, we demonstrate that their protocol can suffer from stolen smart device, impersonation, and session key disclosure attacks and fails to provide secure mutual authentication. Therefore, we propose a secure and lightweight authentication protocol for IoT-based smart homes to resolve the security flaws of Xiang and Zheng’s protocol. We proved the security of the proposed protocol by performing informal and formal security analyses, using the real or random (ROR) model, Burrows–Abadi–Needham (BAN) logic, and the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, we provide a comparison of performance and security properties between the proposed protocol and related existing protocols. We demonstrate that the proposed protocol ensures better security and lower computational costs than related protocols, and is suitable for practical IoT-based smart home environments. Full article
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