5G-Smart Diabetes: Toward Personalized Diabetes Diagnosis with Healthcare Big Data Clouds

 

Abstract

Recent advances in wireless networking and big data technologies, such as 5G networks, medical big data analytics, and the Internet of Things, along with recent developments in wearable computing and artificial intelligence, are enabling the development and implementation of innovative diabetes monitoring systems and applications. Due to the life-long and systematic harm suffered by diabetes patients, it is critical to design effective methods for the diagnosis and treatment of diabetes. Based on our comprehensive investigation, this article classifies those methods into Diabetes 1.0 and Diabetes 2.0, which exhibit deficiencies in terms of networking and intelligence. Thus, our goal is to design a sustainable, cost-effective, and intelligent diabetes diagnosis solution with personalized treatment. In this article, we first propose the 5G-Smart Diabetes system, which combines the state-of-the-art technologies such as wearable 2.0, machine learning, and big data to generate comprehensive sensing and analysis for patients suffering from diabetes. Then we present the data sharing mechanism and personalized data analysis model for 5G-Smart Diabetes. Finally, we build a 5G-Smart Diabetes testbed that includes smart clothing, smartphone, and big data clouds. The experimental results show that our system can effectively provide personalized diagnosis and treatment suggestions to patients.

System Requirements

Hardware Requirements

 

  • System : I3 PROCESSOR
  • Hard Disk                  : 300 GB.
  • Floppy Drive : 1.44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse : Logitech.
  • Ram : 8 GB.

 

Software Requirements

 

  • Operating system :  Windows XP/Ubuntu
  • Coding Language :  java for Mapper and Reducer
  • Front End        :  Php, Javascript (Intelligent Graph)
  • Back End :  Hadoop Cluster
  • Tool :  Virtual Box Oracle tool

 

 

Existing System

The system is uncomfortable, and real-time data collection is difficult. Furthermore, it lacks continuous monitoring of multi-dimensional physiological indicators of patients suffering from diabetes. The diabetes detection model lacks a data sharing mechanism and personalized analysis of big data from different sources including lifestyle, sports, diet, and so on. There are no continuous suggestions for the prevention and treatment of diabetes and corresponding supervision strategies.

Disadvantages:

Uncomfortable, and real-time data collection is difficult.

It lacks continuous monitoring of multi-dimensional physiological indicators of patients suffering from diabetes and personalized analysis of big data.

Proposed System

A next generation diabetes solution called the 5G-Smart Diabetes system, which integrates novel technologies including fifth generation (5G) mobile networks, machine learning, medical big data, social networking, smart clothing, and so on. Then we present the data sharing mechanism and personalized data analysis model for 5G-Smart Diabetes. Finally, based on the smart clothing, smartphone, and big data healthcare clouds, we build a 5G-Smart Diabetes testbed and give the experiment results. Furthermore, the “5G” in 5G-Smart Diabetes has a two-fold meaning. On one hand, it refers to the 5G technology that will be adopted as the communication infrastructure to realize high-quality and continuous monitoring of the physiological states of patients with diabetes and to provide treatment services for such patients without restraining their freedom. On the other hand, “5G” refers to the following “5 goals”: cost effectiveness, comfortability, personalization, sustainability, and smartness.

Advantages:

cost effectiveness: It is achieved from two aspects. First, 5G-Smart Diabetes keeps users in a healthy lifestyle so as to prevent users from getting the disease in the early stage.

comfortability: To achieve comfort for patients, it is required that 5G-Smart Diabetes does not disturb the patients’ daily activities as much as possible.

Personalization:  5G-Smart Diabetes utilizes various machine learning and cognitive computing algorithms to establish personalized diabetes diagnosis for the prevention and treatment of diabetes.

Sustainability: By continuously collecting, storing, and analyzing information on personal diabetes, 5G-Smart Diabetes adjusts the treatment strategy in time based on the changes of patients status.

Smartness: With cognitive intelligence toward patients’ status and network resources, 5G-Smart Diabetes achieves early detection and prevention of diabetes and provides personalized treatment to patients.

 

Conclusion

In this article, we first propose a 5G-Smart Diabetes system that includes a sensing layer, a personalized diagnosis layer, and a data sharing layer. Compared to Diabetes 1.0 and Diabetes 2.0, this system can achieve sustainable, cost-effective, and intelligence diabetes diagnosis. Then we propose a highly cost-efficient data sharing mechanism in social space and data space. In addition, using machine learning methods, we present a personalized data analysis model for 5G-Smart Diabetes. Finally, based on the smart clothing, smartphone and data center, we build a 5G-Smart Diabetes testbed. The experimental results show that our system can provide personalized diagnosis and treatment suggestions to patients.