Performance Evaluation of Wearable IoT-Enabled Mesh Network for Rural Health Monitoring
G. Merlin Sheeba
School of Electrical and Electronics, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
Search for more papers by this authorY. Bevish Jinila
School of Computing, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
Search for more papers by this authorG. Merlin Sheeba
School of Electrical and Electronics, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
Search for more papers by this authorY. Bevish Jinila
School of Computing, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
Search for more papers by this authorR.J. Hemalatha
Search for more papers by this authorD. Balaganesh
Search for more papers by this authorAnand Paul
Search for more papers by this authorSummary
Wearable Internet of Things (IoT)–enabled biosensors are attaining endless interest day by day. The biosensors are a device made up of transducer, biosensor reader device, and a biological element. The growing healthcare demand and consciousness in elderly people has become one of the important aspects. Due to huge technology growth, the medical treatments in urban and rural areas have accelerated to greater dimensions. In rural region, the elderly are not treated in time or treated reactively. The sensors are in the form of bandages, tattoos, shirts, etc., which allows continuous monitoring of blood pressure, glucose, and other biometric physiological data. To address this issue a point-of-care monitoring unit is developed in rural areas for healthcare and awareness. To enhance the performance of the system, a smart and intelligent mesh backbone is integrated for fast transmission of the critical medical data to a remote health IoT cloud server. By experimental analysis, it can be inferred that the survival rate of the critical patients is 10% better compared to conventional scheme. In addition, the end-to-end delay in data transmission is considerably 10% to 30% less compared to conventional scheme.
References
- Aljumah , A.A. et al., Application of data mining: Diabetes healthcare in young and old patients. J. King Saud Univ.-Comp . Inform. Sci. , 25 , 127 – 136 , 2013 .
- Misra , P. , Upadhyaya , R.P. et al., A review of the epidemiology of diabetes in rural India . Diabetes Res. Clin. Pract. , 92 , 3 , 303 – 311 , 2011 .
- Buckaert , S. , Interconnecting Wireless Sensor network and wireless Mesh network: Challenges and Strategies, in : Proc. of IEEE Communication Society GLOBECOM, DBLP 2009 .
-
Lee , R.-G.
,
Hsiao , C.-C.
,
Chen , C.-C.
,
Liu , M.-H.
,
A mobile-care system integrated with Bluetooth blood pressure and pulse monitor, and cellular phone
.
IEICE Trans. Inform. Syst., E89-D
,
5
,
1702
–
11
,
2006
.
10.1093/ietisy/e89-d.5.1702 Google Scholar
- Lee , R.-G. , Chen , K.-C. , Hsiao , C.-C. , Tseng , C.-L. , A mobile care system with alert mechanism . IEEE Trans. Inform. Technol. Biomed. , 11 , 5 , 507 – 17 , 2007 .
- Lai , C.-C. et al., A H-QOS Demand personalized home physiological monitoring system over a wireless multihop relay network for mobile home healthcare application . J. Network Comput. Appl. , 32 , 6 , 1229 – 1241 , 2009 .
- Yuce , M.R. , Implementation of Wireless Body area network for healthcare system . Sens. Actuators A: Phys. , 162 , 1 , 116 – 129 , 2010 .
- Darwish and Hassanien, A.E., Wearable and Implantable Wireless Sensor Network Solution for Healthcare Monitoring . Sensors , 11 , 5561 – 5595 , 2010 .
- Youm , S. et al., Development of remote healthcare system for measuring and promoting healthy lifestyle . Expert Syst. Appl. , 38 , 2828 – 2834 , 2011 .
- Kim , Y. and Lee , S. , Energy-efficient wireless hospital sensor networking for remote patient monitoring . Inform. Sci. , 282 , 332 – 349 , 2014 .
- Sung , W.-T. and Chang , K.-Y. , Health parameter monitoring via a novel wireless system . Appi. Soft Comput. , 22 , 667 – 680 , 2014 .
- Yang , J.-J. et al., Emerging information technologies for enhanced healthcare . Comput. Ind. , 69 , 3 – 11 , 2015 .
- Wolfram , et al., Health Enabling Technologies for the elderly-An overview of service based on a literature review . Comput. Methods Programs Biomed. , 106 , 70 – 78 , 2012 .
- Sheeba , G.M. and Nachiappan , A. , Improving Link Quality using OSPF Routing Protocol in a Stable WiFi Mesh Network . International Conference on Communication and Signal Processing , IEEE, pp. 23 – 26 , 2012 .
- Steele , R. et al., Elderly persons' perception and acceptance of using wireless sensor networks to assist healthcare . Int. J. Med. Inform. , 78 , 788 – 801 , 2009 .
- Hawley-Hague , H. et al., Older adults' perceptions of technologies aimed at fallsprevention, detection or monitoring: A systematic review . Int. J. Med. Inform. , 83 , 416 – 426 , 2014 .
- Sheeba , G.M. and Nachiappan , A. , Fuzzy Differential Evolution Based Gateway Placements in WMN for Cost Optimization . Adv. Intell. Syst. Comput. , 385 , 137 – 145 , 2015 .
- Jothil K.R. and Jeyakumar , A.E. , An Effective Approach for Bio-Medical Data Transmission Using Hop Scheduled Data Dissemination Through VANET . J. Pure Appl. Microbiol. , 9 , 147 – 153 , 2015 .
- Sheeba , G.M. and Nachiappan , A. , Gateway Placements in WMN with Cost Minimization and Optimization using SA and DE Techniques . Int. J. Pharm. Technol. , 7 , 1 , 8274 – 8281 , 2015 .
- Wan , J. , A. A. H. Al-awlaqi , M., Li, M. et al ., Wearable IoT enabled real-time health monitoring system . J. Wirel. Commun. Netw ., 2018 , 298 , 2018 , https://doi.org/10.1186/s13638-018-1308-x .
- Sheeba , G.M. and Nachiappan , A. , Computation of Mesh Node Placements Using DE Approach to Minimize Deployment Cost with Maximum Connectivity . Wirel. Pers. Commun. , 107 , 291 – 302 , 2019 , https://doi.org/10.1007/s11277-019-06255-8 .