Aircraft are becoming unmanned increasingly popular as demands for increasing population and agriculture are being met. With the right cameras, detectors and components, Drones will contribute to a simple, effective and accurate cultivation. The solutions proposed for these drones can help improve things even further if they are integrated into various machine learning concepts and internet concepts. This document highlights the related work in this area along with suggested solutions that can be integrated into drones using the result of the Microcontroller 8051 module

Speech is classified into voice, unvoiced and silence. The voice speech is the periodic vibration of vocal folds. Background noise affects the speech signals. In many speech applications calculation of pitch plays a major role. The paper proposes a pitch detection algorithm based on the short-time average magnitude difference function (AMDF) and the short-term autocorrelation function (ACF). Detecting the Pitch within the speech signal is important in most of all the speech related applications. Detection of Pitch is useful in identification of speaker. One solution to get detect with the pitch is by using the time domain algorithms. This paper gives idea about estimation and detection of pitch in time domain algorithm for different voice samples