Non-Invasive Method of Human Exhaled Breath Analysis for Diabetes Detection Using Bidirectional Long-Short-Term Memory Algorithm

Volatile organic compounds (VOCs) have the potential to be used as biomarkers for pathophysiological and physical abnormalities associated with several disorders. A promising non-invasive metabolic monitoring method is the Analysis of VOCs in exhaled breath. It may also be used to monitor the development of certain diseases and their early detection. Diabetes is a metabolic disease and a complicated syndrome. The relationship between oxidative stress, inflammatory syndrome, hypertension, and diabetes is complicated. This study describes the creation of an Internet of Things (IoT) based breath analyzer to identify and track diseases using exhaled breath. Diabetic breath biomarkers and breath analysis are the main topics of discussion. A group of 25 diabetic patients and 15 non-diabetic individuals were tested using this system. Data is initially gathered using the wired module and the Cool Term software. The system is created for both wired and wireless devices. A deep learning algorithm analyses the disease characteristics after data collection. It clearly distinguishes between samples with diabetes and those without with 84% accuracy. This technology could detect a non-transmissible or transmissible disease early, preventing infection to others

Network Performance Measurement through Machine to Machine Communication in Tele-Robotics System

Machine-to-machine (M2M) communication devices communicate and exchange information with each other in an independent manner to perform necessary tasks. The machine communicates with another machine over a wireless network. Wireless communication opens up the environment to huge vulnerabilities, making it very easy for hackers to gain access to sensitive information and carry out malicious actions. This paper proposes an M2M communication system through the internet in Tele-Robotics and provides network performance security. Tele-robotic systems are designed for surgery, treatment and diagnostics to be conducted across short or long distances while utilizing wireless communication networks. The systems also provide a low delay and secure communication system for the tele-robotics community and data security. The system can perform tasks autonomously and intelligently, minimizing the burden on medical staff and improving the quality and system performance of patient care. In the medical field, surgeons and patients are located at different places and connected through public networks. So the design of a medical sensor node network with LEACH protocol for secure and reliable communication ensures through the attack and without attack performance. Finally, the simulation results show low delay and reliable secure network transmission