Nowadays palm trees diseases responsible for massive economic losses worldwide and

they are extremely challenging to detect in the early stages either because these diseases are

hidden inside the texture of the palm or because it appears on its leaves. In this paper we’re

interested in detecting two of the most common diseases threatening palms nowadays, Leaf Spots and Red

Palm Weevil. Detection of RPW and Leaf Spots a number of detection approaches have been used; however,

none of them have been shown to be reliable.

For the detection of RPW the damage to the palm cannot only be seen with the naked eye or a standard

camera since the damage occurred inside the roots of the palms. As a result, we are willing

to use the Thermal camera as a paradigm shifting device for the early identification of RPW

and the detection of Leaf Spots. Our camera shows the damaged parts inside the palm using

Computer Vision (CV) and Arterial Intelligence (AI) techniques. In comparison with existing, commonly-used

technologies, this paper technique represents a cost-effective way.

• Detecting Red Palm Weevil and Leaf Spots using deep learning techniques such as CNN(RESNET50

and MOBILENETV2).

• Collecting manually the medium-scale dataset.

• Develop a mobile application integrated with the thermal camera as external hardware; So

it can detect the red palm weevil pest in its early stages.

• The application will give the user the privilege for uploading pictures of the diseased parts

and analyze them.

• Providing farmers with rapid, thorough, and report of palm tree diagnosis.

• Featuring a user friendly interface , So farmers have no difficulty using it.

• Offering a treatment way if the infection is detected.

The purpose of the application is to detect the presence of Red Palm Weevil and Leaf Spots in

palm trees using thermal imaging technology and provide timely alerts to farmers or concerned

authorities. The application would be primarily used by farmers, agricultural experts, and authorities

responsible for pest control in agricultural areas.