Unmanned Aerial Vehicle
Volumn 2

Unmanned Aerial Vehicle

Ashay Pathak – Electronics Engineering, Jhulelal Institute of Technology

Mitendra Gadpal – Electronics Engineering, Jhulelal Institute of Technology

Sagarika Mahapatro Electronics Engineering, Jhulelal Institute of Technology

Rishikesh Tambulkar – Professor, Jhulelal Institute of Technology

Abstract:

The UAV is an acronym for Unmanned Aerial Vehicle, which is an aircraft with no pilot on board. UAVs can be remote controlled aircraft or can fly autonomously based on pre-programmed flight plans or more complex dynamic automation system. UAVs are currently used for a number of mission, including reconnaissance and attack roles. For the purpose of this article, and to distinguish UAVs from missiles, a UAV is defined as being capable of control, sustained level flight and powered by a jet.

Objective:To apply the developed method to the design of UAV Systems that can be controlled using an Android based Application to overcome mechanical linkages.

INTRODUCTION

UAVs are defined as reusable and uninhabited aerial vehicles, which are remotely controlled, semi-autonomous, autonomous, or a combination of such capabilities, and can carry various types of payloads, making them capable of performing some of the tasks within earth’s atmosphere, or beyond, for a duration. In reality, UAVs are used widely by the military purposes for missions that are tiring, time consuming and dangerous for aircraft pilots.

UAVs are commonly used in situations where the risk of sending a human piloted aircraft is unacceptable, or the situation makes using a manned aircraft impractical.

Consequently, the military has increased funding for the development of UAVs, which has caused the appearance of UAVs generations with many number of capabilities related to their missions.

In recent years, there has been tremendous growth in android phones embedded with various sensors such as accelerometers, magnetometers, multiple microphones, and e cameras [1]–[3].The sensor networks scope has expanded into many application domains that can provide users with new functions which were previously unheard[4].

Currently the android is popular and widespread used operating system. Developing an android application and interfacing it with the small UAV machine is great idea all of time that is provided for end users operating space widely and convenient carrying functions.

LITERATURE SURVEY

The term UAV is an acronym of Unmanned Aerial vehicle, meaning aerial vehicles which operate without a human pilot. This paper will review the history of UAS development, consider the uses for UAS technology, examine the security, safety, insurance, privacy and regular issues that are associated with integration into the national airspace (NAS), and conclude with some recommendations.

Peculiarity detection has generated sustained research over past years. Applications include fraud detection and instruction, medical, robot behavior novelty detection etc. We focus on anomaly detection in UAV. The domain is categorized by a huge amount of data from various sensors and measurements that is typically streamed online, and requires peculiarly to be quickly discovered, to prevent threats to the safety of unmanned aerial vehicle. [5] There are three main types of sensors that is supported by Android. The first type is motion sensors that measure the acceleration and rotation of a device, e.g., gyroscopes and accelerometers. The second type is environmental sensors that give the information about the environment of a device. Examples include barometers, thermometers, and photometers. The third type is position sensors that provide positional information for a device, like orientation. These also include orientation sensors and magnetometers.

Unmanned Aerial Vehicle
Unmanned Aerial Vehicle

PROPOSED SYSTEM

Design Objectives

  • Stability
  • Obstacle Avoidance
  • Determining Positions
  • Communication

To achieve these objectives we need:

  • IMU (Inertial Measurement Unit)
  • Sensors
  • GPS
  • RF Trans-receiver

Android UAV also includes:

  • Android application for data acquisition.
  • Arduino code for flight control based on Aero Quad.
  • Auxiliary electronics and electrical connections.

CONCLUSION

Many complex issues surround the integration of UAVs into the airspace and all require significant research and regulatory efforts to meet minimum standards of privacy, security and safety.

For the ensured operational safety, technological innovations must enable a UAV’s operator so as to detect other aircraft to avoid midair collisions within the current and next generation traffic control systems. The absence of standard training procedures requires regulatory attention to guarantee operators are competent and international regulations must be uniform to encourage UAS expansion.

Using a mobile smartphone, we have demonstrated some unprecedented applications that are installed inside an automobile to evaluate a vehicle’s condition, such as vehicle’s shifting and overall UAV anomaly, including directions, magnetic field, light and sound.

Our application resulted in high accuracy, making it possible to give results on the state of a particular UAV. Along with these findings, an analysis of a flying behavior for safe and sudden maneuvers, such as vehicle accelerations and orientation changes, has been identified. Using a multiple-axis classification method for directions increased the accuracy, resulting in a better flying anomaly detection system. Being fueled by demand, future advancements in embedded hardware will yield the smartphone and its sensors to be more powerful devices in terms of processing, sensitivity, and accuracy, paving the way for many more innovative applications.

Unlocking its potential in intelligent transportation systems seems only logical as there are conceivably numerous of applications that can help reduce safety concerns on the air.

REFERENCES

  1. V. N. Padmanabhan, P.Mohan ―Nericell: Rich monitoring of road and traffic conditions using mobile smartphones,‖ in Proc. ACM SenSys NC, November 2008.
  2. J. Dai, J. Teng, X. Bai, Z. Shen, and D. Xuan, ―Mobile phone drunk driving detection, in Pro. 4th International Conf. Pervasive Health—NO PERMISSIONS, Mar. 2010, pp. 1–8.
  3. R.Dantu and L. Langle, ―Are you a safe driver in Pro. International CSE Conf., Aug. 2009, vol. 2, pp. 502–507.
  4. S. Andrews, S. Apte, S. Amin, J. Ban, M. Benko, R. M. Bayen, C. Claudel, C. Claudel, T. Dodson, O. Elhamshary, M. Gruteser, R. Herrera, JC. Herring, B. Hoh, Q. Jacobson, T. Iwuchukwu, J. Lew, X. Litrico, J. Margulici, L. Luddington X. Pan, T. Rabbani, T. Racine, E. Sherlock-Thomas, D. Sutter, and A. Tinka, ―Using GPS mobile phones as traffic sensors: A field experiment,‖ in Pro.15th World Cong. Intel. Transp. Syst., New York, Nov. 2008
  5. V. Chandola, A. Banerjee, and V. Kumar. Anomaly detection: A survey. ACM Comput. Surv., 41(3):1– 58, 2009.

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