A home security system for seniors based on the beacon technology

Wu, Hsien‐Tsai; Tsai, Chun-Wei

doi:10.1002/cpe.4496

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…Ambient devices monitor the interaction between humans and their environments that include sound, pressure, temperature, and other sensors. Inbuilt sensors of smart phones have also attracted enormous researchers for human activity recognition 6 . This can enhance health monitoring, indoor localization, and pedestrian navigation.…”

Section: Introductionmentioning

confidence: 99%

Data dissemination approach using machine learning techniques for WBANs

Punj

Kumar

2021

Concurrency and Computation

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Summary Nowadays, the technological advancements of low power electronic and sensing devices, wearable systems, communication technologies, and cloud computing have encouraged the provision of ubiquitous health monitoring, medical diagnosis, and treatment consultations. The data collected from the patients are transmitted to mHealth server for real‐time and self‐reliant activity detection, behavior analysis, ambient assisted living, elderly care, activity of daily living, rehabilitations, entertainments, and surveillance in smart home environments. This helps in building sensor analyst systems that analyze the data on mHealth server for disseminating it to the respective end users. This is of utmost importance as it can provide real time feedback to patients, family members, caregivers, and so forth about the behavioral changes of elderly people and people with special needs. In this article, we have proposed knowledge based data dissemination system using machine learning techniques that analyses the data collected on mHealth server in three steps. First, the data are analyzed using support vector machine, k‐nearest neighbor, neural network, and logistic regression. Second, it finds hidden patterns from the data using hidden Markov model (HMM). Third, it defines fuzzy rules to disseminate the data to the end users. The system has been compared against conventional approaches. The uniqueness of the system lies in the fact that it uses temporal nature of data and provides with real‐time feedback as well as predicts outcomes and detects hidden patterns. The results have shown that the techniques NN, HMM, and fuzzy logic when used in conjunction with each other for disease prediction, hidden pattern detection, and data dissemination gives an accuracy of 98%. Thus, increasing effectiveness of sensor analyst system.

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Section: Introductionmentioning

confidence: 99%

Data dissemination approach using machine learning techniques for WBANs

Punj

Kumar

2021

Concurrency and Computation

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“…Wi and Tsai propose a system to analyze at‐home behavior and physiological indices of the elderly people. The design concepts for software and hardware equipment emphasize the following features: (1) low‐cost sensor devices, (2) user‐friendly interface for the wearable device, (3) easy installation for the equipment, and (4) low‐power consumption for the wearable device.…”

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confidence: 99%

Data fusion in the internet of data

Piccialli

Jung

2018

Concurrency and Computation

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This special issue collates a selection of representative research articles that were primarily presented at the 2nd International Workshop on Data Mining on Internet of Things (IoT) Systems. This annual workshop brings together researchers and practitioners from both academia and industry who are working on data mining approaches on the IoT with applications in the Smart City framework and in the Cultural Heritage research domain in order to promote an exchange of ideas, discuss future collaborations, and develop new research directions.The Internet of Things envisages a plethora of heterogeneous objects interacting with the physical environments. It can be foreseen that IoT applications will raise the scale of data to an unprecedented level. Collecting, analyzing, and correlating data from different resources is a key role to drive smart interactions between actors of IoT environments.In this scenario, the Internet of Data (IoD) represents a concept of network composed by data entities coming from the Interne of Things (IoT).The IoD can be considered an extension of the IoT into the digital world, since the amount of data being collected is staggering. The opportunities created by IoD have the potential to be infinite. The IoD presents an ambitious purpose, ie, organizing the data to be interconnected as a network in order to infer useful information for data analysis and creates useful, customized, and location-based services.The scope of this special issue is broad and is representative of the multidisciplinary nature of the Internet of Data research field.Zheng et al 1 propose a term representation framework for four different features, ie, temporal feature, geographical feature, term co-occurrence, and hashtag. The framework deals with a series of attribution definition to detect topics on a Twitter dataset and confirm the effectiveness of LTDMF.The authors have also deeply analyze the importance of different features in topic detection.Kumar et al 2 present an efficient and secure time-limited hierarchical key assignment scheme key management suitable for data outsourcing scenario. They compare the proposed scheme with other recent similar schemes with respect to the cost of static and dynamic operations.The obtained results show that with similar unit private storage cost; the proposed scheme manages to reduce the key generation cost at the data owner and key derivation cost by each user.Wi and Tsai 3 propose a system to analyze at-home behavior and physiological indices of the elderly people. The design concepts for software and hardware equipment emphasize the following features: (1) low-cost sensor devices, (2) user-friendly interface for the wearable device, (3) easy installation for the equipment, and (4) low-power consumption for the wearable device.Experiment results show that the system simulation proves the algorithm to be feasible.Malik et al 4 discuss a data transformation methodology for geo-related semantic annotation and the importance of reducing the response time of investigation and offe...

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A Divide and Conquer Based Data Aggregation Technique for WBANs

Roopali

Kumar

2021

Communications in Computer and Information Science

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A home security system for seniors based on the beacon technology

Cited by 5 publications

References 24 publications

Data dissemination approach using machine learning techniques for WBANs

Data dissemination approach using machine learning techniques for WBANs

Data fusion in the internet of data

A Divide and Conquer Based Data Aggregation Technique for WBANs

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