A review of smart homes - Present state and future challenges
By M. Chan, D. Estève, C. Escriba, E. Campo. Comput. Methods Programs Biomed., 2008
1,048 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/7cb5b4b077080cfb6d1426f2b4d4ea24824b0313
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Davit Marikyan
- Diane Joyce Cook
- Mamun Bin Ibne Reaz
- Eleftherios Alamanos
- Ashutosh Saxena
- Jaeyong Sung
- Bart Selman
- Bogdan Kwolek
In Computer Networks and Communications
- Diane Joyce Cook
- Davit Marikyan
- Eleftherios Alamanos
- Ashutosh Saxena
- Jaeyong Sung
- Michel Vacher
- Pedro Chahuara
- François Portet
In Computer Vision and Pattern Recognition
- Ashutosh Saxena
- Diane Joyce Cook
- Jaeyong Sung
- Narayanan Chatapuram Krishnan
- Davit Marikyan
- Eleftherios Alamanos
- Savvas Papagiannidis
- Hema Swetha Koppula
Citations in the corpus
- SVM-Based Multimodal Classification of Activities of Daily Living in Health Smart Homes: Sensors, Algorithms, and First Experimental Results (2010, background): “several teams have been working on Health Smart Homes equipped with various sensors [2].”
- Transfer Learning for Activity Recognition: A Survey (2013, background): “Although recent progress in transfer learning has been analyzed in [50,61,70] and several surveys have been conducted on activity recognition [2,4,10,24], no one has specifically looked into the intersection of these two areas.”
- A Review of Smart Homes—Past, Present, and Future (2012, background): “and describes a general overview of smart home research [3].”
- Sensor-Based Activity Recognition (2012, methodology): “As such, dense sensing-based activity monitoring has been widely adopted in AAL, via the smart home paradigm [46], [47], [50], [52]–[56], [81].”
- Human fall detection on embedded platform using depth maps and wireless accelerometer (2014, methodology): “Table 2 shows results of experimental evaluation of the system for fall detection, which were obtained on depth image sequences from URFD dataset.”
- An overview of the Internet of Things for people with disabilities (2012, background): “Modern sensor-embedded houses or smart houses can assist impaired people and resolve their social isolation (Chan et al., 2008).”
- Computer simulation of the activity of the elderly person living independently in a Health Smart Home (2012, background): “[1] M.”
- Wireless sensor networks for healthcare: A survey (2010, neutral): “There are other survey studies in the literature [8, 9, 10, 11, 12].”
- Human Activity Detection from RGBD Images (2011, methodology): “Our personal robotics approach could be contrasted with approaches based on so-called smart homes, which are homes wired with sensor networks that monitor the user (Chan et al., 2008).”
- Smart homes and their users: a systematic analysis and key challenges (2014, background): “This decision support functionality is centred on monitoring through wearable, implantable and sensing devices to facilitate preventative care and detect adverse health incidents [17].”
- A Survey on Ambient-Assisted Living Tools for Older Adults (2013, neutral): “survey papers [40].”
- The Sweet-Home speech and multimodal corpus for home automation interaction (2014, background): “Smart spaces, such as smart homes, are emerging as a way to fulfil this goal (Chan et al., 2008).”
- A systematic review of the smart home literature: A user perspective (2019, methodology): “Given the above limitations and the fact that it has been almost a decade since the literature was more holistically reviewed [1], there is a strong need to revisit and review the current state of the literature.”