Abstract
There are various technologies available to surveillance the farmland through which the farmer can assess the conditions of the crops. Among all technology the autonomous quadcopter is an efficient, small size and cheaper tool to take farmland images. Autonomous quadcopter is advantageous because of its automatic navigation without human interaction. In this work, the paddy field considered with four predefined coordinates. The sensor circuit is deployed at the four coordinates to measure the water level and moisture condition in the field. Here, Way point GPS navigation algorithm is proposed and it allows the quadcopter to fly on its own with its destination. GPS navigation algorithm were implemented and simulated in Proteus. Camera is interfaced with quadcopter to capture the images and that images are analyzed through image processing and send the results to farmers mobile using Wi-Fi.
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Kowsalya, R., Eswaran, P. (2018). Development of Autonomous Quadcopter for Farmland Surveillance. In: Zelinka, I., Senkerik, R., Panda, G., Lekshmi Kanthan, P. (eds) Soft Computing Systems. ICSCS 2018. Communications in Computer and Information Science, vol 837. Springer, Singapore. https://doi.org/10.1007/978-981-13-1936-5_9
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DOI: https://doi.org/10.1007/978-981-13-1936-5_9
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