Internet of Things data analytics for user authentication and activity recognition

Batool, Samera; Saqib, Nazar Abbas; Khan, Muazzam A.

doi:10.1109/fmec.2017.7946428

Cited by 19 publications

(13 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Activity recognition involves the use of movement sensors such as accelerometers, gyroscopes and magnetometers with the aim to help provide the user with feedback on their health in terms of them having enough physical exercise or not, used for sports therapy, fall detection and for monitoring of different diseases such as Parkinson's or other motor degenerative ailments. The most popular sensor for activity recognition are inertial sensors which have been used by [133,134] in a cloud based setting using various deep and machine learning algorithms. In [135], Castro et al include vital sign data in addition to movement information for human activity recognition in a cloud environment, they utilize the DT as their classifier.…”

Section: Smart Healthmentioning

confidence: 99%

“…Moreover, an edge computing system is presented in [152] which utilizes EEG signals to determine seizures in patients. [133] Homogeneous (Accelerometer) CNN [134] RNN (LSTM) [153] Fog Edge Heterogeneous (Accelerometer, Gyroscope, Magnetometer) CNN [137] Fog RF [138] Edge Heterogeneous (Accelerometer and Gyroscope) SVM [136] Patient health monitoring DT [139] Cloud Classification-Recommendation about diet etc.…”

Section: Smart Healthmentioning

confidence: 99%

See 1 more Smart Citation

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

et al. 2021

View full text Add to dashboard Cite

Internet of Things (IoT) is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The IoT for Smart Cities has many different domains and draws upon various underlying systems for its operation. In this paper, we provide a holistic coverage of the Internet of Things in Smart Cities. We start by discussing the fundamental components that make up the IoT based Smart City landscape followed by the technologies that enable these domains to exist in terms of architectures utilized, networking technologies used as well as the Artificial Algorithms deployed in IoT based Smart City systems. This is then followed up by a review of the most prevalent practices and applications in various Smart City domains. Lastly, the challenges that deployment of IoT systems for smart cities encounter along with mitigation measures.

show abstract

Section: Smart Healthmentioning

confidence: 99%

Section: Smart Healthmentioning

confidence: 99%

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In our previous research work [16], we have introduced an IoT data analytics technique for activity and user identification. We have developed models using classification algorithms for users and activity recognition.…”

Section: Related Workmentioning

confidence: 99%

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

et al. 2020

Self Cite

View full text Add to dashboard Cite

In IoT based systems, authentication of users and devices is a major challenge where the traditional authentication mechanisms such as login-password are no longer supportable. It requires continuous authentication methods to ensure authenticity of the users and devices specifically for long sessions. The authentication through the IoT-Sensors based data has already gained the attention of a considerable number of researchers as it does not require direct involvement of the users and provide an extra layer of security and user privacy. Due to the instability of IoT-Sensor data, the authentication techniques need to extract a large number of features to produce high-accurate results. Moreover, the limited capabilities of computation, communication, storage, and the small battery power of IoT devices further makes its implementation hard. In this paper, we have introduced a user authentication framework for remote IoT users based on unique walking patterns to extract gait-related features with minimum data samples and cycle length. For an in-depth analysis of the distinctive features of the sensor-based gait profiles, we have applied an ECG signal processing technique. The proposed approach applies to a diverse range of IoT devices such as cellphones, smartwatches, and wearable sensors. The main contribution of the proposed approach is the deeper gait analysis with the least number of features and data for authentication purposes. We have introduced an authentication algorithm for feature comparison. The machine learning models have been applied to the gait based profiles for validation of the proposed approach. The detailed experimental analysis of different data sets has achieved an accuracy of 94% and an equal error rate (EER) of 6% higher than the existing approaches.

show abstract

“…Again, here IoT offers many possibilities. The ability to track visitors using either their own personal phone [55] or to deploy a large number of small, cheap, ultra-low-power sensors across the site can drastically change the way sites track visitors. Indeed, these technologies can allow heritage sites that were never before able to deploy visitor tracking or interactive systems (due to the lack of infrastructure) to do so.…”

Section: B Visitor Identification and Trackingmentioning

confidence: 99%

Interacting with Heritage: On the Use and Potential of IoT Within the Cultural Heritage Sector

Marshall

2018

2018 Fifth International Conference on Internet of Things: Systems, Management and Security

View full text Add to dashboard Cite

Internet of Things data analytics for user authentication and activity recognition

Cited by 19 publications

References 10 publications

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

IoT in Smart Cities: A Survey of Technologies, Practices and Challenges

Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

Interacting with Heritage: On the Use and Potential of IoT Within the Cultural Heritage Sector

Contact Info

Product

Resources

About