Abstract
IoT is the collaboration of physical devices, electronics, software, sensors, actuators, and network connectivity which helps in collecting and exchanging of data. It is a smart technology which cooperates with the environment by the sensors and actuators which are found very useful in monitoring the health of the people. It holds different features such as diagnosis, signal analysis, drug development, medical image analysis, and radiology. These features of IoT devices are used for monitoring the health of old-age citizen as they are highly influenced by several diseases which require continuous monitoring and treatment. In this paper, a novel IoT and neural network-based old-age health risk prediction framework is proposed, and the performance of the proposed framework is found to be good with respect to parameters like time consumption, monitoring efficiency, and cost incurred.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
https://en.wikipedia.org/wiki/List_of_countries_by_life_expectancy/
Kumar, S.S., Kumar, Dr. K.A.: Neural networks in medical and healthcare. Int. J. Innovative Res. Develop. 2(8), 241–244 (2013)
Khoi, N.M., Saguna, S., Mitra, K., Ǻhlund, C.: IReHMo: an efficient IoT-based remote health monitoring system for smart regions. In: IEEE Xplore, pp. 1–6 (2015)
Koshti, M., Ganorkar, S., Prof. Dr.: IoT based health monitoring system using Raspberry Pi and ECG signal. Int. J. Innovative Res. Sci. Eng. Technol. 5, 8977–8985 (2016)
Azimi, I., Rahmani, A.M., Liljeberg, P., Tenhunen, H.: Internet of things for remote elderly monitoring: a study from user-centered perspective. J. Ambient Intell. Humanized Comput, 1–17 (2016). Springer
World Health Organization website (https://www.who.int/)
Aruna, D.S., Godfrey, W.S., Sasikumar, S.: Patient health monitoring system (PHMS) using IoT devices. Int. J. Comput. Sci. Eng. Technol. 7, 68–73 (2016)
Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., Kantarci, B., Andreescu, S.: Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: opportunities and challenges. In: IEEE International Conference on Services Computing, pp. 285–292 (2015)
Gómez, J., Oviedo, B., Zhuma, E.: Patient monitoring system based on internet of things. In: 7th International Conference on Ambient Systems, Networks and Technologies, pp. 90–97 (2016)
Babu, B.S., Bhargavi, K.: CAs-based QoS scheme for remote health monitoring. Int. J. Agent Technol. Syst. 5(4), 44–67 (2013)
Gautam, A., et al.: An improved mammogram classification approach using back propagation neural network. In: Data Engineering and Intelligent Computing, pp. 369–376. Springer, Singapore (2018)
Tiwari, A., Gautam, A.: Classification of Mammograms using Sigmoidal Transformation and SVM. In: Proceedings of International Conference on Smart Computing and Informatics (SCI-2017), pp. 1–8, March 2017
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Prajapati, D., Bhargavi, K. (2018). Old-Age Health Risk Prediction and Maintenance via IoT Devices and Artificial Neural Network. In: Bhateja, V., Coello Coello, C., Satapathy, S., Pattnaik, P. (eds) Intelligent Engineering Informatics. Advances in Intelligent Systems and Computing, vol 695. Springer, Singapore. https://doi.org/10.1007/978-981-10-7566-7_37
Download citation
DOI: https://doi.org/10.1007/978-981-10-7566-7_37
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7565-0
Online ISBN: 978-981-10-7566-7
eBook Packages: EngineeringEngineering (R0)