Mobile device, network node and methods for identifying equipment

A method performed by a network node for identifying an equipment, the method comprising:

• receiving from one or more mobile devices, one or more radiation indications associated with a recorded image of the equipment, which image is recorded in a recording direction at a first location, the one or more radiation indications comprising signal qualities and frequencies of one or more beams or signals from the equipment;
• determining a direction of radiation from the equipment by analysing the received one or more radiation indications;
• and
• determining an identity of the equipment based on the recorded image and the determined direction of radiation from the equipment, the determining of the identity of the equipment comprising:
• generating a radio energy signature map based on the received one or more radiation indications and the recorded image, the radio energy signature map comprising energy measurements determined at different points around the equipment;
• determining the direction of radiation from the equipment by analyzing the received one or more radiation indications;
• and
• determining an identity of the equipment using image processing, the image processing being performed by using machine learning on the generated radio energy signature map and the determined direction of radiation from the equipment.

A mobile device for handling identification of equipment, wherein the mobile device is configured to:

• record an image, in a recording direction at a first location, of the equipment;
• upon recording the image, obtain one or more radiation indications for determining a direction of radiation from the equipment, the one or more radiation indications comprising signal qualities and frequencies of one or more beams or signals from the equipment;
• provide the obtained one or more radiation indications associated with the recorded image, to an internal identifying process at one or both of the mobile device and a network node for identifying the equipment, the internal identifying process comprising:
• generating a radio energy signature map based on the obtained one or more radiation indications and the recorded image, the radio energy signature map comprising energy measurements determined at different points around the equipment;
• determining the direction of radiation from the equipment by analyzing the obtained one or more radiation indications;
• and
• determining an identity of the equipment using image processing, the image processing being performed by using machine learning on the generated radio energy signature map and the determined direction of radiation from the equipment.

A network node for identifying an equipment, the network node comprising processing circuitry, the processing circuitry is configured to:

• receive from one or more mobile devices, one or more radiation indications associated with a recorded image of the equipment, which image is recorded in a recording direction at a first location, the one or more radiation indications comprising signal qualities and frequencies of one or more beams or signals from the equipment;
• determine a direction of radiation from the equipment by analysing the received one or more radiation indications;
• and
• determine an identity of the equipment based on the recorded image and the determined direction of radiation from the equipment, the determining of the identity of the equipment comprising:
• generating a radio energy signature map based on the received one or more radiation indications and the recorded image, the radio energy signature map comprising energy measurements determined at different points around the equipment;
• determining the direction of radiation from the equipment by analyzing the received one or more radiation indications;
• and
• determining an identity of the equipment using image processing, the image processing being performed by using machine learning on the generated radio energy signature map and the determined direction of radiation from the equipment.