The Experience of Developing the UJAmI Smart Lab

Espinilla, Macarena; Martínez, Luis; Medina, Javier; Nugent, Chris

doi:10.1109/access.2018.2849226

Cited by 39 publications

(33 citation statements)

References 34 publications

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“…Another example is the MIT PlaceLab [Intille et al 2006], which offers a facility for the study of ubiquitous technologies in home settings via a network of sensors that capture a complete record of audiovisual activity, including information about objects manipulated, environmental conditions, and use of appliances. Some other examples of living labs include the Gator Tech Smart House [Helal et al 2005] from the University of Florida; the MIT Human Speechome Project [Roy et al 2006]; the Assisted Living Laboratory [Kleinberger et al 2007] at the Fraunhofer IESE in Kaiserslautern; the Georgia Tech Aware Home [Kientz et al 2008]; the TigerPlace [Skubic et al 2009] in Columbia, Missouri; and, more recently, the Halmstad Intelligent Home [Lundström et al 2016] at Halmstad University and the UJAmI [Espinilla et al 2018] at the University of Jaén, Spain. However, most of these labs have the drawback of using intrusive sensors such as cameras.…”

Section: Related Workmentioning

confidence: 99%

MakeSense

Jiang

Pozza

Gilbert

et al. 2020

ACM Trans. Internet Things

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There has been increasing interest in deploying Internet of Things (IoT) devices to study human behavior in locations such as homes and offices. Such devices can be deployed in a laboratory or "in the wild" in natural environments. The latter allows one to collect behavioral data that is not contaminated by the artificiality of a laboratory experiment. Using IoT devices in ordinary environments also brings the benefits of reduced cost, as compared with lab experiments, and less disturbance to the participants' daily routines, which in turn helps with recruiting them into the research. However, in this case, it is essential to have an IoT infrastructure that can be easily and swiftly installed and from which real-time data can be securely and straightforwardly collected. In this article, we present MakeSense, an IoT testbed that enables real-world experimentation for large-scale social research on indoor activities through real-time monitoring and/or situation-aware applications. The testbed features quick setup, flexibility in deployment, the integration of a range of IoT devices, resilience, and scalability. We also present two case studies to demonstrate the use of the testbed: one in homes and one in offices. CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing systems and tools; • Applied computing → Sociology; • Computer systems organization → Sensor networks; • Hardware → Sensor devices and platforms;

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Section: Related Workmentioning

confidence: 99%

MakeSense

Jiang

Pozza

Gilbert

et al. 2020

ACM Trans. Internet Things

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“…The University of Jaén Ambient Intelligence (UJAmI) [12][13][14] represents an innovative space that plays a key role in the implementation of new ground-breaking research within the realms of Ambient Intelligence (AmI) [4], which is a paradigm in information technology aimed at empowering people's capabilities through the means of digital environments.…”

Section: Ujami Smart Lab Of the University Of Jaénmentioning

confidence: 99%

“…The aim of the creation of the UJAmI Smart Lab [14] in 2014 was to produce a real apartment: sensitive, adaptive and responsive to human needs (habits, gestures and emotions) which subsequently underpinned assistive technology based solutions in the home.…”

Section: Ujami Smart Lab Of the University Of Jaénmentioning

confidence: 99%

UCAmI Cup. Analyzing the UJA Human Activity Recognition Dataset of Activities of Daily Living

2018

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Many real-world applications, which are focused on addressing the needs of a human, require information pertaining to the activities being performed. The UCAmI Cup is an event held within the context of the International Conference on Ubiquitous Computing and Ambient Intelligence, where delegates are given the opportunity to use their tools and techniques to analyse a previously unseen human activity recognition dataset and to compare their results with others working in the same domain. In this paper, the human activity recognition dataset used relates to activities of daily living generated in the UJAmI Smart Lab, University of Jaén. The dataset chosen for the first edition of the UCAmI Cup represents 246 activities performed over a period of ten days carried out by a single inhabitant. The dataset includes four data sources: (i) event streams from 30 binary sensors, (ii) intelligent floor location data, (iii) proximity data between a smart watch worn by the inhabitant and 15 Bluetooth Low Energy beacons and (iv) acceleration of the smart watch. In this first edition of the UCAmI Cup, 26 participants from 10 different countries contacted the organizers to obtain the dataset.‬‬‬‬‬

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“…The H 2 Al design was also influenced by systems used in other similar smart home environments that focus on research on activity recognition and support of daily activities for persons with cognitive or physical impairments, such as the SERG lab at Ulster University (UK) [18], the Halmstad Intelligent Home at Halmstad University (Sweden) [19] and the Smart Home Lab at University of Jaen (Spain) [20]. These labs collaborate in a European Marie Skłodowska Curie Action named Remind (The use of computational techniques to Improve compliance to reminders within smart environments) that aims at ultimately setting up experiments across multiple labs [21].…”

Section: Remind-sensorcentralmentioning

confidence: 99%

H2Al—The Human Health and Activity Laboratory

Synnes¹,

Lilja²,

Nyman³

et al. 2018

UCAmI 2018

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The Human Health and Activity Laboratory (H2Al) is a new research facility at Luleå University of Technology implemented during 2018 as a smart home environment in an educational training apartment for nurses and therapists at the Luleå campus. This paper presents the design and implementation of the lab together with a discussion on potential impact. The aim is to identify and overcome economical, technical and social barriers to achieve an envisioned good and equal health and welfare within and from home environments. The lab is equipped with multiple sensor and actuator systems in the environment, worn by persons and based on digital information. The systems will allow for advanced capture, filtering, analysis and visualization of research data such as A/V, EEG, ECG, EMG, GSR, respiration and location while being able to detect falls, sleep apnea and other critical health and wellbeing issues. The resulting studies will be aimed towards supporting and equipping future home environments and care facilities, spanning from temporary care to primary care at hospitals, with technologies for activity and critical health and wellness issue detection. The work will be conducted at an International level and within a European context, based on a collaboration with other smart labs, such that experiments can be replicated at multiple sites. This paper presents some initial lessons learnt including design, setup and configuration for comparison of sensor placements and configurations as well as analytical methods.

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The Experience of Developing the UJAmI Smart Lab

Cited by 39 publications

References 34 publications

MakeSense

MakeSense

UCAmI Cup. Analyzing the UJA Human Activity Recognition Dataset of Activities of Daily Living

H2Al—The Human Health and Activity Laboratory

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