Design and development of an IOT based wearable device for the safety and security of women and girl children

Jatti, Anand; Kannan, Madhvi; M, Alisha R; Vijayalakshmi, P.; Sinha, Shrestha

doi:10.1109/rteict.2016.7808003

Cited by 46 publications

(19 citation statements)

References 9 publications

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“…Machine learning is the most popular research technique for data processing with 100 publications. This technique is used for data prediction [218,219], activity recognition [220,221], and data classification [222,223]. Next, data mining appears with 89 documents, with distributed data mining [224], and applications such as event detection [225,226] as sub-techniques.…”

Section: Software Processing Techniquesmentioning

confidence: 99%

Internet of Things: A Scientometric Review

et al. 2017

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Abstract:Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, which generate a large number of samples, creating a big data challenge. This IoT paradigm has gained traction in recent years, yielding extensive research from an increasing variety of perspectives, including scientific reviews. These reviews cover surveys related to IoT vision, enabling technologies, applications, key features, co-word and cluster analysis, and future directions. Nevertheless, we lack an IoT scientometrics review that uses scientific databases to perform a quantitative analysis. This paper develops a scientometric review about IoT over a data set of 19,035 documents published over a period of 15 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) in two main scientific databases (Clarivate Web of Science and Scopus). A Python script called ScientoPy was developed to perform quantitative analysis of this data set. This provides insight into research trends by investigating a lead author's country affiliation, most published authors, top research applications, communication protocols, software processing, hardware, operating systems, and trending topics. Furthermore, we evaluate the top trending IoT topics and the popular hardware and software platforms that are used to research these trends.

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Section: Software Processing Techniquesmentioning

confidence: 99%

Internet of Things: A Scientometric Review

et al. 2017

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“…Goodwin et al [23] also presented a remarkable way to detect violence by using cardiovascular, electrodermal activity and motion (accelerometry) but focused on people with autism spectrum disorder, so the circumstances are not exactly similar to a IPV context. Therefore, although being some proposal very complete [24], previous proposals have a lack of completeness, this is, relying in a couple of features and other works with a more complete monitoring in order to continuously monitor daily activities (which could include an assault) like the exposed ones in the review done by Kumari et al [25] are not specifically designed for IPV survivors monitoring.…”

Section: Existing Proposals For Violence Detection Based On Biosensorsmentioning

confidence: 99%

An Autonomous Alarm System for Personal Safety Assurance of Intimate Partner Violence Survivors Based on Passive Continuous Monitoring through Biosensors

et al. 2020

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Intimate Partner Violence (IPV) dramatically compromises the free and complete development of many women around the world, therefore leading to social asymmetry regarding the right to personal safety. In many cases, a woman who has reported her partner to police for gender-based violence needs to ensure her protection (either before the trial of the aggressor or after their freedom). Thus, it would be ideal if autonomous alarm systems could be developed in order to call the police if necessary. Up to now, many proposals have been presented in this regard, including solutions based on Information and Communication Technologies (ICT) but, unfortunately, these approaches usually rely on the active participation of the victims (survivors), who have to turn the system on by themselves if needed. Therefore, in order to overcome such limitations, in this work, a passive continuous monitoring system is proposed which uses biosensors attached to the survivor as well as machine learning techniques to infer if an abnormal situation related to gender-based violence is taking place, activating in this case an alarm. The monitoring structure of the system supervises a great deal of bio-signals according to the current status of technology of wearables and biomedical devices. The presented biosensors-based surveillance solution can also be manually disconnected for 30/60/90 min (on demand) in order to avoid false positives when a woman is, for example, practicing sports or carrying out other inoffensive activities that could incorrectly activate the alarm.

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“…In the figure, we have tired to figure out how the SOS button properly worked, if the mobile headphone is conncected or not. We use headphone power up button as a SOS button [8][9][10][11][12][13]. First connect headphone to app.…”

Section: Working Principle 21 Block Diagram Of Proposed Systemmentioning

confidence: 99%

Manifesting a mobile application on safety which ascertains women salus in Bangladesh

Hossain

Rahman

Islam³

et al. 2019

IJECE

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This paper reflects on the indemnity of women in our society. The proposed model ensures the embodiment of a mobile application. The algorithm, we developed for this model focuses the safety issues which is applicable to both inside as well as outside of the house for the women in Bangladesh. The solution of this problems can be done through some interrelated features such as i) SOS button pressing which ensures automatic calling, instant location tracking system through GPS of the phone and sending tracked location to all trusted numbers, automatically secrete video recording system ii) voice command detection which assures exact same features as SOS button pressing iii) phone shaking features serve user instant immunity by calling a trusted number. This research also assures experimented data analysis at Dhaka city based on respond time, the time it takes to arrive the SMS and Phone call and current location of the victim. Also do a short comparison among the most popular safety related mobile applications.

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Design and development of an IOT based wearable device for the safety and security of women and girl children

Cited by 46 publications

References 9 publications

Internet of Things: A Scientometric Review

Internet of Things: A Scientometric Review

An Autonomous Alarm System for Personal Safety Assurance of Intimate Partner Violence Survivors Based on Passive Continuous Monitoring through Biosensors

Manifesting a mobile application on safety which ascertains women salus in Bangladesh

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