Figure 2.7 Sign-in page.
The data is pulled from the database to the app and is displayed in the form of an electrocardiogram (ECG). We interface the GSM Module with the LinkIT One, so that upon a threshold being crossed (if the heart-rate is above 100 beats per minute or if it is lower than 60 beats per minute), an emergency SMS is sent to those who matter to the patient, like doctors and close relatives. The SMS indicates the ward number of the patient if he/she is in the hospital, else it provides the patient’s house address. If the threshold is crossed the graph turns red indicating danger.
Figure 2.8 Choose an account.
Figure 2.9 Options.
Figure 2.10 List of patients.
Figure 2.11 Patient details page.
2.4 Conclusion
A prototype of a system was designed and constructed which takes in signals from a medical sensor, such as a pulse sensor, performs operations on it, calculates the beats per minute, and data is transmitted to a database, from which data is retrieved and displayed on a dedicated website for medical professionals. A cross platform app is also created for the same.
We believe that this is a step forward in the field of remote patient monitoring, as patient data, i.e., critical medical parameters such as pulse, blood pressure, oxygen saturation, etc. can be monitored by medical professionals from the convenience of their offices, or even homes, and post-hospitalization care will become more accessible and efficient. Patients who live far away from medical care centers need not travel large distances, just to undergo check-up. This is a cost effective and efficient solution.
References
1. Hu, F., Xie, D., Shen, S., On the Application of the Internet of Things in the Field of Medical and Health Care. 2013 IEEE International Conference on Green Computing and Communications and IEEE, 2013.
2. Jimenez, F. and Torres, R., Building an IoT-aware healthcare monitoring system. 2015 34th International Conference of the Chilean Computer Science Society (SCCC), 2015.
3. Chiuchisan, I., Costin, H.-N., Geman, O., Adopting the Internet of Things Technologies in Health Care Systems. 2014 International Conference and Exposition on Electrical and Power Engineering (EPE 2014), Iasi, Romania, 16–18 October, 2014.
4. Luo, J., Tang, K., Chen, Y., Luo, J., Remote Monitoring Information System and Its Applications Based on the Internet of Things. 2009 International Conference on Future BioMedical Information Engineering, 2009.
5. Istepanian, R.S.H., Sungoor, A., Faisal, A., Philip, N., Internet of M-Health Things, m-IOT. Imperial College London ... Taccini, 2005.
6. Amendola, S., Lodato, R., Manzari, S., Occhiuzzi, C., Marrocco, G., RFID Technology for IoT-Based Personal Healthcare in Smart Spaces. IEEE Internet Things J., 1, 2, 144–152, 2014.
7. Stankovic, Q., Cao, Doan, T., Fang, L., He, Z., Kiran, R., Lin, S., Son, S., Stoleru, R., Wood, A., Wireless Sensor Networks for In-Home Healthcare: Potential and Challenges. 2015 34th International Conference of the Chilean Computer Science Society (SCCC).
1 *Corresponding author: [email protected]
2 †Corresponding author: [email protected]
3 ‡Corresponding author: [email protected]
4 §Corresponding author: [email protected]
5 ¶Corresponding author: [email protected]
6 **Corresponding author: [email protected]
3
An Efficient Clustering Technique for Wireless Body Area Networks Based on Dragonfly Optimization
Bilal Mehmood and Farhan Aadil*
Computer Science Department, COMSATS University Islamabad, Attock Campus, Attock, Pakistan
Abstract
Wireless body area network (WBAN) is a network of tiny health monitoring sensors, implanted or placed on the human body to collect and communicate human physiological data. WBAN used to have a connection with Medical-Server to monitor patient’s health. It is capable to protect critical patient’s lives, due to its ability to continuous remote monitoring. Inter-WBAN system provides a dynamic environment for patients to move around freely. While moving, some of the WBANs (patients) may or may not be in the range of Remoter Base Station (RBS). Here we need an efficient approach for inter-WBAN communication. In the proposed clustered-based routing technique network overhead is reduced and cluster lifetime is increased. The cluster head act as a gateway in between cluster members and external network. Moreover, for the selection of optimized cluster heads, we used evolutionary algorithms to select the most optimized solution, within the set of solutions. In the clustering approach, network efficiency is dependent on the cluster’s lifetime. The proposed technique forms efficient clusters with an increased lifetime along with remarkable network and energy efficiency.
Keywords: Wireless body area network (WBAN), energy-efficient clustering, inter-WBAN routing
3.1 Introduction
WBANs are a network of small size, lightweight, low power, wearable/implantable sensors. These sensors monitor human’s physiological activities like Patient’s Heartbeat, blood pressure, Electrocardiogram (ECG), EMG, etc. WBANs allow connectivity in between heterogeneous body sensor to a portable hub devise that provide a connection to the external internet. There are a variety of applications of the WBANs. Military can use it to monitor the physical location, physical condition, and vital signs of a field person. In the medical perspective, we can keep track patient’s physiological condition, to provide medical facilities [1]. On a single body, multiple sensors can be placed and these nodes used to form a single WBAN. Each WBAN has a centralized entity called Personal Server (PS). It gathers data from other sensors