An Analytical approach on DFD to UML model transformation techniques

With a drastic change in climate continuously it is very harmful to the people who are living in the disaster-prone areas. In some areas the people are not warned for the consequences of coming specifically in their areas, they are told about the average temperature and humidity of the city while the humidity and temperature vary at different altitude and changes at short distances. The system is a very cost-effective and efficient method for controlling and monitoring the weather, and it sends the data to the cloud so that it can be visible anywhere through internet. The temperature, humidity, and pressure play a significant role in different fields like agricultural, industrial and Logistical Field. Weather forecast is necessary for the growth and development of these industries. The Internet of Things (IoT) is the technology used in developing the proposed system, which is an efficient and advanced method for connecting the sensors to the cloud which can store real-time sensor data and connect the entire world of things in a network. Here things might be anything like electronic gadgets, sensors, and automotive electronic equipment. The system deals with controlling and monitoring the environmental conditions like Temperature, Pressure, Smoke, Relative humidity level and various other gases with sensors and sends the information to the cloud and then plot the sensor data in graphical form. An Intelligent prediction is to be done using machine learning. Machine learning is a branch of Artificial Intelligence (AI) which is a compelling method of Analyzing and predicting the given data-set. The data collected will be analyzed continuously. The real-time data which has to be sent through the sensor can be accessible throughout the world using the internet

Section: Resultsmentioning

confidence: 99%

An Intelligent Weather Monitoring System using Internet of Things

Prasanna¹,

Iyapparaja²,

Kumar³

et al. 2019

“…We have implemented the proposed system for indoor and outdoor areas using RFID, which is provided with the identity card of the user and GPS which will be tracked from the registered mobile number. Indoor areas tracking is achieved using RFID [20,21] and the latter one is used for outdoor tracking. Every user is tracked using the user id (UID) which is verified with the database, when it is valid the position of the user is displayed to the smartphone by RFID.…”

Section: System Implementation and Resultsmentioning

confidence: 99%

An Intelligent Faculty Tracking and Attendance Marking System using Machine Learning

R L*,

Aby,

Joe

et al. 2019

In the current era, machine learning and IoT have grown vastly and is one of the most important technologies used today. It has various applications like automated systems, driverless cars, fire alarming system, etc. In this project we are going to implement an intelligent attendance marking system and how to track a faculty in school/college using face detection, i.e., by using machine learning algorithm for attendance marking and using RFID, IP camera, GPS technology for tracking the location of the faculty in the school/college. This system consists of two modules of operations. The first module is the attendance marking module and the second module is tracking the location. This system checks for the location of the faculty when the user enters the name to be searched in the app. The system first checks for the faculty in closed areas like the classroom, canteen, library, etc. and then open areas like the ground, parking area, etc. If the faculty’s location is not identified then the system checks the attendance data and informs whether the faculty is absent or not to the user. This methodology has many future scopes. If the machine contains precise data it becomes less time-consuming, it can improve its accuracy and produce exact results and it can reduce the human effort. It can replace the biometric system for attendance marking.

“…The Android application to assist the farmers is developed using Android Studio [26]. The login page of the smart farming system is shown in Figure 5.…”

Section: Figure 4: Connection Diagrammentioning

confidence: 99%

An Intelligent System for Monitoring and Managing Agricultural Fields

2019

Agriculture is a primary concern of every developing nation to maintain their GDP. But most of the processes involved in agricultural sector are still orthodox and inefficient. Though the technology is improving day by day, it is high time to incorporate technology innovations into the field of agriculture for better productivity and resource utilization. We propose an intelligent farming technology with the aid of Internet of Things (IoT) to make various farming techniques smarter and efficient. Various sensors were deployed in the fields to remotely monitor the parameters of soil, water and air. The sensed information is fed to an Android app and it will process the data and alert the farmer if any unusual events occur. Experimental results prove that our model can be used for efficient utilization of agricultural resources like water and fertilizers and thereby improve the productivity and profit.