Real-Time Achievement by Tracking Mobile Wireless Sensors Using PFA and EEA

At present, the effectuation for real-time achievement became very important in many activities, like; auto driver, medical utilization, asteroids tracking, controlling smart devices movements, observing and detection, etc. Different kinds of detection devices which named “sensors”, can establish those techniques, such as laser sensors, infrared sensor, ultrasonic sensors, radio (radars) technique, light sensors, and so on. The ultrasonic sensor has been used commonly, it has wide challenges comparing with other kinds of sensors especially when mobility involved as an agent tool. In this paper, with regard to the ultrasonic sensor, sensor(s) allocating and identifying by itself then has got stirring among known fixed area for real-time estimation using Euclidean Estimation Algorithm and Particle Filter Algorithm as an intelligent estimation algorithms by comparing the prediction that obtained by distance and time. These achievements trying to estimate the error ratio comparing to the substantial tracking which using the mathematic mean with standard deviation as a threshold factor. In this paper ultrasonic sensor model (HC-SR04) with microcontroller (Arduino- MEGA) has been used as well as (Arduino-UNO) used, two Bluetooth sensors model (HC-05), two steeper motors for controlling the movements of the mobile robot (car) as an agent to make sensors movable within known area for estimate the distance and time precisely. This results of this proposal depending on corporations about many testing of movable sensors reading as a data set for comparisons and testing the results. In general as a conclusion, this article found that Euclidean Estimation Algorithm (EEA) is better than Particle Filter Algorithm (PFA).