The job selection process can be troubling for employees in today's global economy. It involves searching through newspapers, job websites, and human agents for employment opportunities. However, there is often no feedback from employers on the criteria submitted by employees. To address this, we propose the creation of intelligent agents to interact with employers and job search coordinators. These agents will use fuzzy preference rules to make decisions. The agents will also collect feedback from past and current employees to rate employers. The system will use Android 2.2, JADE- LEAP, and the Google API to provide a robust and user-friendly solution.

Keywords : Java Agent Development Environment, Lightweight Agent Platform, UML.

Author : D Sreenivasulu Reddy , S Touheed , K Rohith Kumar Reddy , C Naveen Kumar, B Vikas

Title : Job Search System in Android Environment

Volume/Issue : 2024;1(4)

Page No : 1 - 4

Present-day intensive care units, or ICUs, offer critically ill patients who are susceptible to several problems, including death and morbidity, round-the-clock monitoring. ICU environments produce a lot of data and call for a high staff-to-patient ratio. Making decisions and interpreting data in real time is a difficult task for clinicians. In intensive care units (ICUs), machine learning (ML) tools are advancing the early detection of high-risk events. because of more powerful computers and publicly accessible databases like the Medical Information Mart for Intensive Care (MIMIC). Techniques in ICU settings uses MIMIC data. The ICU patient risk level monitoring system plays a crucial role in improving patient safety, optimizing resource allocation, and enhancing clinical decision-making in intensive care settings. By continuously monitoring and analyzing patient data, it provides valuable insights that help healthcare providers intervene promptly and prevent adverse outcomes.

Keywords : Intensive Care Unit, Critical Care, MIMIC, ML, AI, NLP.

Author : M Veeresh Babu , R Harshitha , A Keerthana , K Haripriya , N Manisha

Title : ICU Patient Risk Level Monitoring System using Supervised Learning Approaches

Volume/Issue : 2024;1(4)

Page No : 5 - 9

Water pollution has become a major concern in recent times due to the contamination and pollution of drinking water. The ecosystem's life cycle may be impacted by the diseases that contaminated water might spread to people and animals. Early detection of water contamination allows for the implementation of appropriate controls and the avoidance of dangerous circumstances. Real time monitoring of the water's quality is necessary to ensure a supply of pure water. As sensors, communication, and the Internet of Things (IoT) continue to advance, smart solutions for monitoring water contamination are becoming more and more important. This study presents a thorough analysis of the most recent efforts undertaken in the field of smart water pollution monitoring systems. The idea suggests an inexpensive and effective Internet of Things (IoT)-based hydrological monitoring system that continuously tracks the quality indicators. Water samples are used to evaluate the constructed model, and the parameters are sent to the cloud server for additional processing.

Keywords : pH, Temperature sensor, Water flow, Turbidity, water quality monitoring, IoT, Arduino.

Author : R Pradeep Kumar , B Sreekanth , R Rohitha , G Shamitha , T Sai Asha , P Neelima

Title : Hydrological Monitoring using Internet of Things

Volume/Issue : 2024;1(4)

Page No : 10 - 14

The Al Virtual Mouse uses computer vision techniques to track hand movements and translates them into cursor movements on the screen. The system is designed to be intuitive and user-friendly, allowing users to interact with their computer without the need for a physical mouse. The virtual mouse is developed using Python and OpenCV libraries. The project includes the implementation of various image processing algorithms, such as hand segmentation, feature extraction, and classification. Moreover, it is robust to various lighting conditions, backgrounds, and hand sizes. The developed system provides an alternative to conventional mouse devices, particularly for individuals with disabilities or those who prefer a more natural way of interacting with their computers. The target of this project is the invention of something new in the world of technology that helps an individual work without the help of a physical mouse. It will save the user money and time.

Keywords : Gesture recognition, CNN algorithm, OpenCV, Mediapipe, Virtual Mouse, AI chatbot.

Author : T Somasekhar , P Phani Bhushan , O Ravi Kumar, K Vamsidhar Reddy , A Uday Vardhan

Title : Gestured Control Virtual Mouse with AI Chatbot

Volume/Issue : 2024;1(4)

Page No : 15 - 18