Chapter1 1 1. A Case Study of Wavelets and SVM Application in Coffee Agriculture: Detecting Cicadas Based on Their Acoustic and Image Patterns

Abstract One of the main problems in agriculture is crop pest management, which causes financial damage to farmers. This management is traditionally performed with pesticides; however, with a large area of application, it would be more economically viable and more environmentally recommended to know precisely the regions where there is concrete infestation. In coffee farms, cicada makes a distinctive sound when it hatches after years of underground nymph-shaped living. One possibility of contributing to its management would be the development of a device capable of capturing the sound of the adult cicada in order to detect its presence and to quantify crop insects. This device would be spread across the coffee plots to capture sounds within the widest possible area coverage. With monitoring and quantification data, the manager would have more input for decision-making and could adopt the most appropriate management technique based on concrete information on population density separated by crop region. Thus, this chapter presents an algorithm based on wavelets and support vector machines (SVMs), to detect acoustic patterns in plantations, advising on the presence of cicadas.