Health Monitoring system
Health Monitoring system -? Smart Health System The wireless medical sensor network is used in healthcare applications that have the collections of biosensors connected to a human body or emergency care unit to monitor the patient’s physiological vital status. The real-time medical data collected using wearable medical sensors are transmitted to a diagnostic center. The data generated from the sensors are aggregated at this center and transmitted further to the doctor’s personal digital assistant for diagnosis. Unauthorized access to one’s health data may lead to misuse and legal complications while unreliable data transmission or storage may lead to life-threatening risks to patients. So, this Letter combines the symmetric algorithm and attribute-based encryption to secure the data transmission and access control system for the medical sensor network. Further, the data is sent to a centralized server through a wireless network. In this case, this server can be a PC connected to the same network, for this transmission UDP protocol can be used. This data can be accessed only through fingerprint authentication.?
In the recent period, we observed a gradual rise in expectations of life in various parts of the world, which leads to a frequent increase in the number of aged people. As per the report of the United Nations, the number of aged people will be about 2.0 billion (22% of the total world’s population) by 2050. The research found that nearly 89% of aged people are living individually. However, a medical research survey found that it is 80% of the aged people elder than 65 and they suffer from at least one disease, and older people have difficulty caring for themselves. By WHO 2015 report 400 million people do not have necessary Health facilities. The number of patients has increased nearly double every four decades, and it is difficult for hospitals to care for all patients. According to the United States report, we can avoid about 41 million deaths yearly if we provide Healthcare facilities at the time. Providing a gracious quality of life to patients is a big social challenge.
The body sensor network provides a large convenience to detect the abnormality inpatient’s body and provide proper treatment at the time. Sensors sense the physiological data (Body Temperature, Heart Rate, Blood Pressure, ECG Signal, etc.) periodically every 10 seconds from the patient’s body. In capturing the physiological data from the sensor in the patient’s body, we need to process data pre-processing techniques on sensor data to resolve duplication, errors (Outliers), and missing values in data.
- Automate health monitoring?
- AES-based encryption?
- Safe cloud communication?
- Sensor-based patient monitoring
- Does Raspberry pi act as the heart of this system?
- It is used for data processing and communication?
- Every sensor is connected to the raspberry pi?
- Temperature and ECG sensors are connected through an ADC module
- Raspberry pi?
- ECG sensor?
- Temperature sensor
- MCP3008? ADC?
- Programing platform: Python IDLE?
- Programing language: python 3
- Algorithm: AES
- Single Sagar, Deshpande Niranjan, Vadane Pandurang, Dighe M, “ IoT Based Health-Care System Using Raspberry Pi ”, International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 04, IRJET, April 2017
- M. Surya Deekshith Gupta, Vamsikrishna Patchava, Virginia Menezes, “ Healthcare based on IoT using Raspberry Pi ”, International Conference on Green Computing and Internet of Things (ICGIoT), New Delhi, January 2017.
- Prosanta Gope, Tzonelih Hwang, “ BSN-Care: A Secure IoT-based Modern Healthcare System Using Body Sensor Network ”, IEEE Trans., November 2015.
- Tutorials Point – “Decryption Advanced Encryption Standard” from https://www.tutorialspoint.com/cryptography/advanced_encryption_stan dard.htm.
- Commonlounge – “ Encryption Advanced Encryption Standard” from https://www.commonlounge.com/discussion.
- Taiyang Wu, Fan Wu, Jean-Michel Redouté, Mehmet Rasit Yuce, “ An Autonomous Wireless Body Area Network Implementation Towards IoT Connected Healthcare Applications ”, 2169-3536 IEEE, Translations, 2016.
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