{"id":2108,"date":"2023-01-03T12:05:12","date_gmt":"2023-01-03T12:05:12","guid":{"rendered":"https:\/\/www.kios.ucy.ac.cy\/amas\/?p=2108"},"modified":"2025-03-12T13:39:18","modified_gmt":"2025-03-12T13:39:18","slug":"m-l-algorithms","status":"publish","type":"post","link":"https:\/\/www.kios.ucy.ac.cy\/hpi\/m-l-algorithms\/","title":{"rendered":"M.L. Algorithms"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"2108\" class=\"elementor elementor-2108\" data-elementor-settings=\"{&quot;ha_cmc_init_switcher&quot;:&quot;no&quot;}\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-bb19bf8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bb19bf8\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e4a6d3b\" data-id=\"e4a6d3b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f8d1214 elementor-widget elementor-widget-heading\" data-id=\"f8d1214\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Hyperion Application<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f1ff36b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f1ff36b\" data-element_type=\"section\" data-settings=\"{&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-78771b0\" data-id=\"78771b0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5e8e993 elementor-widget elementor-widget-heading\" data-id=\"5e8e993\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<span class=\"elementor-heading-title elementor-size-default\">Abstract<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5072ea2 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"5072ea2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Using machine learning and deep learning techniques to identify drone movement through classification is a powerful and efficient way to monitor and track drones in various applications. This can include tracking drones in areas where they are not allowed, such as near airports or other sensitive locations, as well as identifying patterns of movement for use in logistics and other industries.<\/p><p>In our case,&nbsp; we use supervised learning techniques to classify drone movement , where we train a model on labeled data to predict the class of new, unseen data. More specifically, we achieved this by implimenting various algorithms, such as Decision Tree, Random Forest, Light Gradient Boosting, Stochastic Gradient Descent, Logistic Regression, K nearest neighbor, Gaussian Naive Bayes and LSTM. For the above algorithms we used the python library sckit learn except for LSTM for which we used the keras library. By executing these algorithms and comparing them, we took the best results from LSTM.<\/p><p>Specifically we created two diferrent datasets. In the first dataset, the drone has the ability to perform a single movevment at each timestep, and in the second dataset the drone can perform more than one movements at each timestep. It is worth mentioning that the data that we used to train our model, we gathered them making flights with our drone Matrice 300 which was equipped with a variety of sensors, cameras and weather station. \u03a4he data that is included in the datasets is the timestamp, wind speed, wind angle, battery voltage, battery current, position x, position y, position z, altitude, oritentation x, orientation y, orientation z, orientation w, velocity x, velocity y, velocity z, angular x, angular y, angular z, linear acceleration x, linear acceleration y, linear acceleretion z and payload, yaw and flight mode.<\/p><p>Our target was to identify the current state of the drone. For this reason, we trained our model on the datasets that we mentioned above,&nbsp; containing&nbsp; five different types of drone movement : hovering (IDLE-HOVER), ascending (ASCEND), turn(TURN), flying in a straight line (HMSL) and descending (DESCEND). We implemented a multi-class classification to identify the single movement of the drone and multilabel classification to identify the multi-movement of the drone. In the training process we used the features mentioned above except the altitude and yaw. The target variable was the flight mode. To evaluating our model, we used accuracy, precision, recall and f1-score. The best results we collected, after many tests, for multiclass classification and multilabel classification were 96% and 96.5% respectively.<\/p><p>Overall, we use machine learning and deep learning techniques in our research for classifying drone movement and predict the trajectory of the drone. Result of this, is the provision of a fast and accurate way to track and monitor drones in various applications customized to the specific needs of the user.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-65b60fd elementor-arrows-position-inside elementor-pagination-position-outside elementor-widget elementor-widget-image-carousel\" data-id=\"65b60fd\" data-element_type=\"widget\" data-settings=\"{&quot;slides_to_show&quot;:&quot;1&quot;,&quot;navigation&quot;:&quot;both&quot;,&quot;autoplay&quot;:&quot;yes&quot;,&quot;pause_on_hover&quot;:&quot;yes&quot;,&quot;pause_on_interaction&quot;:&quot;yes&quot;,&quot;autoplay_speed&quot;:5000,&quot;infinite&quot;:&quot;yes&quot;,&quot;effect&quot;:&quot;slide&quot;,&quot;speed&quot;:500}\" data-widget_type=\"image-carousel.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-image-carousel-wrapper swiper\" role=\"region\" aria-roledescription=\"carousel\" aria-label=\"Image Carousel\" dir=\"ltr\">\n\t\t\t<div class=\"elementor-image-carousel swiper-wrapper\" aria-live=\"off\">\n\t\t\t\t\t\t\t\t<div class=\"swiper-slide\" role=\"group\" aria-roledescription=\"slide\" aria-label=\"1 of 2\"><figure class=\"swiper-slide-inner\"><img decoding=\"async\" class=\"swiper-slide-image\" src=\"https:\/\/www.kios.ucy.ac.cy\/amas\/wp-content\/uploads\/2023\/01\/ml_palamas.png\" alt=\"\" \/><\/figure><\/div><div class=\"swiper-slide\" role=\"group\" aria-roledescription=\"slide\" aria-label=\"2 of 2\"><figure class=\"swiper-slide-inner\"><img decoding=\"async\" class=\"swiper-slide-image\" src=\"https:\/\/www.kios.ucy.ac.cy\/amas\/wp-content\/uploads\/2023\/01\/ml_palamas2.png\" alt=\"\" \/><\/figure><\/div>\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-swiper-button elementor-swiper-button-prev\" role=\"button\" tabindex=\"0\">\n\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"eicon-chevron-left\"><\/i>\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"elementor-swiper-button elementor-swiper-button-next\" role=\"button\" tabindex=\"0\">\n\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"eicon-chevron-right\"><\/i>\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<div class=\"swiper-pagination\"><\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-372cb47 elementor-widget elementor-widget-toggle\" data-id=\"372cb47\" data-element_type=\"widget\" data-widget_type=\"toggle.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-5781\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-5781\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-toggle-title\" tabindex=\"0\"><\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t<div id=\"elementor-tab-content-5781\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-5781\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Hyperion Application Abstract Using machine learning and deep learning techniques to identify drone movement through classification is a powerful and efficient way to monitor and track drones in various applications. This can include tracking drones in areas where they are not allowed, such as near airports or other sensitive locations, as well as identifying patterns 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