A method for airside activity management using video analytics , comprising: obtaining, in real time, video data of a survey area from at least one video camera (202A-N); and determining time stamps associated with one or more airside activities of an aircraft from touchdown to takeoff by applying video analytics on the obtained video data to manage the one or more airside activities, wherein the airside activities comprise ground handling activities, wherein determining the time stamps associated with one or more of the ground handling activities of the aircraft comprises: identifying the aircraft and one or more ground handling vehicles by applying video analytics on the obtained video data , wherein each of the one or more ground handling vehicles is associated with a ground handling activity; creating a bounding box around the identified aircraft and each of the one or more ground handling vehicles ; tracking movements of the at least one of the aircraft and the one or more ground handling vehicles using the created bounding boxes ; computing distance between the bounding box associated with the aircraft and the bounding box associated with each of the one or more ground handling vehicles ; and determining start and stop time stamps associated with one or more of the ground handling activities based on distance between the bounding boxes associated with the aircraft and each of the one or more ground handling vehicles . obtaining, in real time, video data of a survey area from at least one video camera (202A-N); and determining time stamps associated with one or more airside activities of an aircraft from touchdown to takeoff by applying video analytics on the obtained video data to manage the one or more airside activities, wherein the airside activities comprise ground handling activities, wherein determining the time stamps associated with one or more of the ground handling activities of the aircraft comprises: identifying the aircraft and one or more ground handling vehicles by applying video analytics on the obtained video data , wherein each of the one or more ground handling vehicles is associated with a ground handling activity; creating a bounding box around the identified aircraft and each of the one or more ground handling vehicles ; tracking movements of the at least one of the aircraft and the one or more ground handling vehicles using the created bounding boxes ; computing distance between the bounding box associated with the aircraft and the bounding box associated with each of the one or more ground handling vehicles ; and determining start and stop time stamps associated with one or more of the ground handling activities based on distance between the bounding boxes associated with the aircraft and each of the one or more ground handling vehicles . identifying the aircraft and one or more ground handling vehicles by applying video analytics on the obtained video data , wherein each of the one or more ground handling vehicles is associated with a ground handling activity; creating a bounding box around the identified aircraft and each of the one or more ground handling vehicles ; tracking movements of the at least one of the aircraft and the one or more ground handling vehicles using the created bounding boxes ; computing distance between the bounding box associated with the aircraft and the bounding box associated with each of the one or more ground handling vehicles ; and determining start and stop time stamps associated with one or more of the ground handling activities based on distance between the bounding boxes associated with the aircraft and each of the one or more ground handling vehicles . <EOS>