Search results for "Human activity"
showing 9 items of 19 documents
A Fog-Based Application for Human Activity Recognition Using Personal Smart Devices
2019
The diffusion of heterogeneous smart devices capable of capturing and analysing data about users, and/or the environment, has encouraged the growth of novel sensing methodologies. One of the most attractive scenarios in which such devices, such as smartphones, tablet computers, or activity trackers, can be exploited to infer relevant information is human activity recognition (HAR). Even though some simple HAR techniques can be directly implemented on mobile devices, in some cases, such as when complex activities need to be analysed timely, users’ smart devices can operate as part of a more complex architecture. In this article, we propose a multi-device HAR framework that exploits the fog c…
A Federated Learning Approach for Distributed Human Activity Recognition
2022
In recent years, the widespread diffusion of smart pervasive devices able to provide AI-based services has encouraged research in the definition of new distributed learning paradigms. Federated Learning (FL) is one of the most recent approaches which allows devices to collaborate to train AI-based models, whereas guarantying privacy and lower communication costs. Although different studies on FL have been conducted, a general and modular architecture capable of performing well in different scenarios is still missing. Following this direction, this paper proposes a general FL framework whose validity is assessed by considering a distributed activity recognition scenario in which users' perso…
Human Activity Recognition Process Using 3-D Posture Data
2015
In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution o…
SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications
2020
Abstract The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately, because both of their distributed nature and high degree of modularity, edge-fog-cloud computing systems are particularly prone to cyber security attacks that can be performed against every element of the infrastructure. In order to address this issue, in this paper we present SMCP…
Towards a Smart Campus Through Participatory Sensing
2018
In recent years, the percentage of the population owning a smartphone has increased significantly. These devices provide users with more and more functions that make them real sensing platforms. Exploiting the capabilities offered by smartphones, users can collect data from the surrounding environment and share them with other entities in the network thanks to existing communication infrastructures, i.e., 3G/4G/5G or WiFi. In this work, we present a system based on participatory sensing paradigm using smartphones to collect and share local data in order to monitor make a campus 'smart'. In particular, our system infers the activities performed by users (e.g., students) in a campus in order …
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points
2022
In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…
Human Activity Signatures Captured under Different Directions Using SISO and MIMO Radar Systems
2022
In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2×2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Anc…
Estimation of the Time-Variant Velocity of a Single Walking Person in Two-Dimensional Non-Stationary Indoor Environments Using Radio-Frequency Techni…
2020
Accurate estimation of the time-variant (TV) velocity of moving persons/objects in indoor spaces is of crucial importance for numerous wireless indoor applications. This article introduces a novel iterative procedure to estimate the TV velocity, i.e., TV speed and TV angle-of-motion (AOM), of a single moving person in 2D indoor environments by using radio-frequency (RF) techniques. The indoor area is equipped with a distributed 2 × 2 multiple-input multiple-output (MIMO) system. The proposed method is divided into two parts. In the first part, we estimate the path gains and the instantaneous Doppler frequencies by fitting the exact spectrograms of the complex channel gains of a 2D no…
Learning and using English and Swedish beyond the classroom : activity systems of six upper secondary school students
2012
Tämän tutkimuksen tarkoituksena oli katsoa englannin ja ruotsin oppimista koulun ulkopuolella toiminnan teorian ja erityisesti Engeströmin (1987, 1999) toimintajärjestelmämallin näkökulmasta, josta aihetta ei ole aiemmin lähestytty. Tutkimus vastaa seuraaviin kysymyksiin: 1) Ovatko abiturientit enemmän kielenkäyttäjiä vai -oppijoita englannissa ja ruotsissa koulun ulkopuolella? 2) Millaisia eroja ja yhtäläisyyksiä heidän toiminnassaan on englannissa ja ruotsissa? 3) Mitkä tekijät selittävät aktiivisuutta ja passiivisuutta? Tutkimus on toteutettu tapaustutkimuksena. Tutkimusaineistona on kuusi puolistrukturoitua haastattelua. Haastateltavat ovat 18-vuotiaita lukion kolmannen vuosikurssin opi…