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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21545
Article Published : 8519
Total Authors : 22414
Total Reviewer : 805
Total Countries : 159
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Published Paper Details
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| Paper Title: | Analysis Living and Non-Living Things Fall Detection and Prevention Using Wireless Network & IoT |
| Authors Name: | Somasundaram N , M.Aishwarya , Dr. R.Natarajan |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_183743
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| Published Paper Id: | IJRTI2208200 |
| Published In: | Volume 7 Issue 8, August-2022 |
| DOI: | |
| Abstract: | In the fall of the aging people and paralysis patient always lead to serious health issues as the decline of their physical fitness. Cleavage is the most common slash in fall of an aging people and there is also a certain possibility to get coma, brain trauma, and paralysis patient. About to the fall situations, the fall process is the main source of tear because of the high influence. But sometimes, late medical reclaim may be depressed the situation. That means the faster the reclaim comes, the less threat the aging human beings will face. Thus the paper progress a fall detection system based on a suitable device. The system monitors the movements of human body, recognizes a fall from day to day activities by an effective quaternion algorithm, and automatic sends request for help to the cared with the patient’s location. In the fall detection algorithms plan based on the option of acceptance features. According the acceptance feature, fall detection algorithms, classified as gateway based and machine learning based. Gateway based method; gateway of recognition feature is set by the designer before appeal which makes the algorithm have rapid response and less resource consumption. In the machine learning based design, the grouping of fall and day to day activities is available with the assistance of technologies such as support vector machine (SVM) and neural network. |
| Keywords: | DC Motor, GSM Modem, Support Vector Machine, Tri-Axis Accelerometer |
| Cite Article: | "Analysis Living and Non-Living Things Fall Detection and Prevention Using Wireless Network & IoT ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 8, page no.1243 - 1246, August-2022, Available :http://www.ijrti.org/papers/IJRTI2208200.pdf |
| Downloads: | 000205176 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2208200
Registration ID:183743
Published In: Volume 7 Issue 8, August-2022
DOI (Digital Object Identifier):
Page No: 1243 - 1246 Country: Aruppukottai / Virudhunagar, Tamilnadu, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2208200 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2208200 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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