A field-measurements-based LoRa network planning tool

Long range (LoRa) transmission technology enables energy-constrained devices such as the tiny sensor systems used in internet-of-things applications that are distributed over wide areas while still being able to establish appropriate connectivity. This has resulted in the development of an exponentially increasing number of different solutions and services based on LoRa, be they dedicated to the long-term monitoring of distributed plants and infrastructures or to human-centred applications such as safety-oriented sensor systems for use in the workplace. In dense LoRa networks, predicting the number of supported nodes in relation to their position and the propagation environment is essential for ensuring reliable and stable communication and minimising costs. In this paper, after comparing different path loss models based on a field measurement campaign for LoRa received signal strength indicator values within a university campus, two main modifications of the LoRa simulator tool were implemented. These were aimed at improving the accuracy of the prediction of the number of sustainable nodes in relation to the target data extraction rate set. The simulations based on field measurements demonstrated that through an improved path loss evaluation and the use of three gateways, the number of nodes could be increased theoretically from around 100 to around 6,000

Cross-domain classification of physical activity intensity: An eda-based approach validated by wrist-measured acceleration and physiological data

Performing regular physical activity positively affects individuals’ quality of life in both the short-and long-term and also contributes to the prevention of chronic diseases. However, exerted effort is subjectively perceived from different individuals. Therefore, this work explores an out-of-laboratory approach using a wrist-worn device to classify the perceived intensity of physical effort based on quantitative measured data. First, the exerted intensity is classified by two machine learning algorithms, namely the Support Vector Machine and the Bagged Tree, fed with features computed on heart-related parameters, skin temperature, and wrist acceleration. Then, the outcomes of the classification are exploited to validate the use of the Electrodermal Activity signal alone to rate the perceived effort. The results show that the Support Vector Machine algorithm applied on physiological and acceleration data effectively predicted the relative physical activity intensities, while the Bagged Tree performed best when the Electrodermal Activity data were the only data used

The importance of physiological data variability in wearable devices for digital health applications

This paper aims at characterizing the variability of physiological data collected through a wearable device (Empatica E4), given that both intra- and inter-subject variability play a pivotal role in digital health applications, where Artificial Intelligence (AI) techniques have become popular. Inter-beat intervals (IBIs), ElectroDermal Activity (EDA) and Skin Temperature (SKT) signals have been considered and variability has been evaluated in terms of general statistics (mean and standard deviation) and coefficient of variation. Results show that both intra- and inter-subject variability values are significant, especially when considering those parameters describing how the signals vary over time. Moreover, EDA seems to be the signal characterized by the highest variability, followed by IBIs, contrary to SKT that results more stable. This variability could affect AI algorithms in classifying signals according to particular discriminants (e.g. emotions, daily activities, etc.), taking into account the dual role of variability: hindering a net distinction between classes, but also making algorithms more robust for deep learning purposes thanks to the consideration of a wide test population. Indeed, it is worthy to note that variability plays a fundamental role in the whole measurement chain, characterizing data reliability and impacting on the final results accuracy and consequently on decision-making processes

Analyzing technology acceptance and perception of privacy in ambient assisted living for using sensor-based technologies

People increasingly use various technologies that enable them to ease their everyday lives in different areas. Not only wearable devices are gaining ground, but also sensor-based ambient devices and systems are increasingly perceived as beneficial in supporting users. Especially older and/or frail persons can benefit from the so-called lifelogging technologies assisting the users in different activities and supporting their mobility and autonomy. This paper empirically investigates users' technology acceptance and privacy perceptions related to sensor-based applications implemented in private environments (i.e., passive infrared sensors for presence detection, humidity and temperature sensors for ambient monitoring, magnetic sensors for user-furniture interaction). For this purpose, we designed an online survey entitled "Acceptance and privacy perceptions of sensor-based lifelogging technologies"and collected data from N = 312 German adults. In terms of user acceptance, statistical analyses revealed that participants strongly agree on the benefits of such sensorbased ambient technologies, also perceiving these as useful and easy to use. Nevertheless, their intention to use the sensor-based applications was still rather limited. The evaluation of privacy perceptions showed that participants highly value their privacy and hence require a high degree of protection for their personal data. The potential users assessed the collection of data especially in the most intimate spaces of domestic environments, such as bathrooms and bedrooms, as critical. On the other hand, participants were also willing to provide complete data transparency in case of an acute risk to their health. Our results suggest that users' perceptions of personal privacy largely affect the acceptance and successful adoption of sensor-based lifelogging in home environments

Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance

The majority of car accidents worldwide are caused by drowsy drivers. Therefore, it is important to be able to detect when a driver is starting to feel drowsy in order to warn them before a serious accident occurs. Sometimes, drivers are not aware of their own drowsiness, but changes in their body signals can indicate that they are getting tired. Previous studies have used large and intrusive sensor systems that can be worn by the driver or placed in the vehicle to collect information about the driver’s physical status from a variety of signals that are either physiological or vehicle-related. This study focuses on the use of a single wrist device that is comfortable for the driver to wear and appropriate signal processing to detect drowsiness by analyzing only the physiological skin conductance (SC) signal. To determine whether the driver is drowsy, the study tests three ensemble algorithms and finds that the Boosting algorithm is the most effective in detecting drowsiness with an accuracy of 89.4%. The results of this study show that it is possible to identify when a driver is drowsy using only signals from the skin on the wrist, and this encourages further research to develop a real-time warning system for early detection of drowsiness

Upper and lower treeline biogeographic patterns in semi-arid pinyon-juniper woodlands

none7siAim: Upper and lower treelines are particularly exposed to a changing climate. It has been hypothesized that upper treelines are constrained by growing season temperature, whereas lower tree lines are water limited. We expect different causal mechanisms of upper versus lower tree line formation to generate distinct patterns of spatial heterogeneity. Here, we compare dynamics, spatial patterns and shape complexity of upper and lower tree lines of semi‐arid pinyon‐juniper woodlands. Location: Toiyabe Range of the Nevada Great Basin (western US). Taxon: Pinus monophylla Torr. & Frém. and Juniperus osteosperma (Torr.). Methods: Within 20 sample plots (10 along the upper and 10 along the lower tree line), we mapped tree canopies through photointerpretation of high‐resolution imagery. We performed point pattern analyses to compare the spatial arrangement of trees and used LANDSAT 30‐year time series and NDVI to understand the vegetation dynamics of these ecotones. We adopted the surface roughness method to measure tree line shape complexity. Results: Lower tree lines were denser and showed a stronger trend of increasing NDVI change over the 1984–2015 period. Trees at the lower tree line were more strongly aggregated than at the upper tree line at spatial scales ranging from 15 to 65 meters. Shape complexity was higher at upper tree lines, expressed by a higher mean surface roughness; however, the spatial structures of upper and lower tree lines were similar. Main conclusions: Upper tree line expansion of pinyon‐juniper woodlands in the study area has been limited and highly variable, but lower tree line downslope expansion into adjacent shrub steppe vegetation was evident. The expected difference between energy‐ and water‐limited tree lines did not manifest in the observed spatial structures. Differences in tree line shape complexity were not significant, although lower tree lines exhibited less complex shapes, likely because they have been more strongly influenced by anthropogenic factors.The datasets generated and analysed during the current study are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.11836284mixedGarbarino, Matteo; Malandra, Francesco; Dilts, Thomas; Flake, Sam; Montalto, Luigi; Spinsante, Susanna; Weisberg, Peter J.Garbarino, Matteo; Malandra, Francesco; Dilts, Thomas; Flake, Sam; Montalto, Luigi; Spinsante, Susanna; Weisberg, Peter J

Counting surrounding nodes using DS-SS signals and de Bruijn sequences in blind environment

In recent years the technological development has encouraged several applications based on node to node communications without any fixed infrastructure. This paper presents preliminary evaluation of popular estimating techniques to populate active nodes in the neighborhood using De Bruijn sequences. They have much higher cardinality compared to any other family of binary sequences at a parity of length. This characteristic of De Bruijn sequences can be exploited to identify the presence of an active node in a dense surrounding, to assist the primary node in making intelligent decisions in a blind or foggy environment. The simulation model in this paper evaluates the use of eigenvalue estimation to estimate the spreading sequence among noisy signals, based on eigenvalues analysis techniques. The received signal is divided into windows, from which a covariance matrix is computed; the sequence can be reconstructed from the two first eigenvectors of this matrix, and that useful information, such as the desynchronization time, can be extracted from the eigenvalues. © 2013 IEEE

Overnight Supervision of Alzheimer's Disease Patients in Nursing Homes - System Development and Field Trial

The number of patients affected by Alzheimer's disease among the population is currently growing, while the availability of resources for their assistance is decreasing. A solution for this problem is provided by the use of Ambient Assisted Living technologies, with the objectives to prolong the independent living of patients at home, to relieve assistance burden on caregivers, and to improve care effectiveness in nursing homes. This paper describes an integrated system designed to support the work of nurses during the night, to ensure comfort and safety of Alzheimer's disease patients in nursing homes. The project started from a similar solution designed for home use, suitably re-engineered for adoption in nursing homes. The system has been designed according to nurses' requirements and expectations, both by revising some existing functionalities, and by developing new components. The results gained from an experimental trial are also presented and discussed

Delay and Disruption Tolerant Authentication for Space Communications

Some space communication scenarios, such as Deep Space communication networks, represent an example of Delay and Disruption Tolerant Networks, which may experience dynamic, long-delay links, and outages. Networks of this kind require a strong re-engineering of many of the protocols for data transmission usually adopted in traditional, terrestrial data networks. The Bundle Protocol has been proposed by the IETF as an overlay communication infrastructure, to cope with the heterogeneous components of a Disruption Tolerant Network; however, there are still many open issues that need to be analyzed. This paper focuses on the impact of delay and disruption tolerant networks on the efficiency and robustness of authentication mechanisms, and discusses some solutions possibly suitable to the Bundle architecture

Remote health monitoring for elderly through interactive television

Abstract Background Providing remote health monitoring to specific groups of patients represents an issue of great relevance for the national health systems, because of the costs related to moving health operators, the time spent to reach remote sites, and the high number of people needing health assistance. At the same time, some assistance activities, like those related to chronical diseases, may be satisfied through a remote interaction with the patient, without a direct medical examination. Methods Moving from this considerations, our paper proposes a system architecture for the provisioning of remote health assistance to older adults, based on a blind management of a network of wireless medical devices, and an interactive TV Set Top Box for accessing health related data. The selection of TV as the interface between the user and the system is specifically targeted to older adults. Due to the private nature of the information exchanged, a certified procedure is implemented for data delivery, through the use of non conditional smart cards. All these functions may be accomplished through a proper design of the system management, and a suitable interactive application. Results The interactive application acting as the interface between the user and the system on the TV monitor has been evaluated able to help readability and clear understanding of the contents and functions proposed. Thanks to the limited amount of data to transfer, even a Set Top Box equipped with a traditional PSTN modem may be used to support the proposed service at a basic level; more advanced features, like audio/video connection, may be activated if the Set Top Box enables a broadband connection (e.g. ADSL). Conclusions The proposed layered architecture for a remote health monitoring system can be tailored to address a wide range of needs, according with each patient’s conditions and capabilities. The system exploits the potentialities offered by Digital Television receivers, a friendly MHP interface, and the familiar remote control, to make the service effective and easy to use also for elderly people.</p