Electronic apparatus for managing network connection and control method thereof

1. An electronic apparatus comprising:

a transceiver;

a memory configured to store a first artificial intelligence (AI) model; and

a processor configured to:

based on environment information being received from at least one of a plurality of devices that are connected to the electronic apparatus, input the environment information to the first AI model, and

in response to one of the plurality of devices being predicted to lose a network connection based on an output of the first AI model, maintain the network connection of the predicted device through another device of the plurality of devices,

wherein the processor is further configured to:

control the transceiver to transmit, to the device predicted to lose the network connection, a control signal for controlling the device predicted to lose the network connection to transmit information obtained by the device predicted to lose the network connection to the other device,

control the transceiver to transmit, to the other device, a control signal for controlling the other device to transmit the information received from the device predicted to lose the network connection to the electronic apparatus, and

receive, in response to the network connection between the device predicted to lose the network connection and the electronic apparatus being lost, the information obtained by the device predicted to lose the network connection from the other device via the transceiver.

2. The electronic apparatus of claim 1 ,

wherein the first AI model is trained based on training data including information of a device that has lost a network connection to the electronic apparatus among the plurality of devices, and

wherein information of the plurality of devices is obtained during a time including a point in time at which the network connection is lost.

3. The electronic apparatus of claim 1 ,

wherein the memory further stores a second AI model, and

wherein the processor is further configured to identify the other device based on the second AI model and the environment information.

4. The electronic apparatus of claim 3 ,

wherein the second AI model is trained based on training data including network connection information indicating a state of a network connection between the device predicted to lose the network connection and at least one device among the plurality of devices located near the device predicted to lose the network connection, and

wherein information of the plurality of devices is obtained during a time including a point in time at which the network connection is established.

5. The electronic apparatus of claim 1 ,

wherein the memory is further configured to store a third AI model, and

wherein the processor is further configured to:

in case that the other device is not identified, determine prediction information on a future operation progress state of the device predicted to lose the network connection based on the third AI model and a current operation progress state of the device predicted to lose the network connection, and

control the transceiver to transmit the prediction information to at least one of the plurality of devices.

6. The electronic apparatus of claim 5 , wherein the processor is further configured to:

in response to the network connection between the device predicted to lose the network connection and the electronic apparatus being lost and then resumed, receive state information of an operation progress state of the predicted device during a time for which the network connection is lost, from the predicted device via the transceiver, and

train the third AI model based on the state information.

7. The electronic apparatus of claim 1 , wherein a communication method between the plurality of devices and the electronic apparatus is different from a communication method between the device predicted to lose the network connection and the other device.

8. The electronic apparatus of claim 1 , wherein the environment information comprises at least one of information of an operation progress state of each device, information of a network connection of each device, or information of a surrounding environment of each device.

9. A method of an electronic apparatus, the method comprising:

based on environment information being received from at least one of a plurality of devices that are connected to the electronic apparatus, inputting the environment information to a first artificial intelligence (AI) model; and

in response to one of the plurality of devices being predicted to lose a network connection based on an output of the first AI model, controlling the device predicted to lose the network connection to maintain the network connection of the device predicted to lose the network connection through another device of the plurality of devices,

wherein the controlling of the predicted device comprises:

transmitting, to the device predicted to lose the network connection, a control signal for controlling the device predicted to lose the network connection to transmit information obtained by the device predicted to lose the network connection to the other device,

transmitting, to the other device, a control signal for controlling the other device to transmit the information received from the device predicted to lose the network connection to the electronic apparatus, and

receiving, in response to the network connection between the device predicted to lose the network connection and the electronic apparatus being lost, the information obtained by the device predicted to lose the network connection from the other device.

10. The method of claim 9 ,

wherein the first AI model is trained based on training data including information of a device that has lost a network connection to the electronic apparatus among the plurality of devices, and

wherein information of the plurality of devices is obtained during a time including a point in time at which the network connection is lost.

11. The method of claim 9 , wherein the controlling of the predicted device comprises:

inputting the received environment information to a second AI model trained to identify the other device of the plurality of devices network-connected to the electronic apparatus; and

identifying the other device based on an output of the second AI model.

12. The method of claim 11 ,

wherein the second AI model is trained based on training data including network connection information indicating a state of a network connection between the predicted device and at least one device located near the device predicted to lose the network connection, and

wherein information of the plurality of devices is obtained during a time including a point in time at which the network connection is established.

13. The method of claim 9 , further comprising:

in case that the other device is not identified, inputting operation progress state information on a current operation progress state of the predicted device to a third AI model;

obtaining prediction information on a future operation progress state of the device predicted to lose the network connection based on an output of the third AI model; and

transmitting the prediction information to at least one of the plurality of devices.

14. The method of claim 13 , further comprising:

in response to the network connection between the device predicted to lose the network connection and the electronic apparatus being lost and then resumed, receiving state information of an operation progress state of the device predicted to lose the network connection during a time for which the network connection is lost, from the device predicted to lose the network connection; and

training the third AI model based on the state information.

15. The method of claim 9 , wherein a communication method between the plurality of devices and the electronic apparatus is different from a communication method between the device predicted to lose the network connection and the other device.

16. The method of claim 9 , wherein the environment information comprises at least one of information of an operation progress state of each device, information of a network connection of each device, or information of a surrounding environment of each device.

17. The method of claim 9 , further comprising:

combining the environment information and training data based on a network connection to a first device of the plurality of devices being lost; and

training the first AI model to determine that the first device will lose the network connection using the combined training data.

18. The method of claim 9 , further comprising:

setting a priority for each of the plurality of devices based on corresponding environment information;

identifying a weight for each of the plurality of devices based on a primary function of each corresponding device; and

selecting the other device based on the priority of the other device and the weight for the other device.

19. The method of claim 9 ,

wherein a first device transmits environment information of the first device using a first communication method, and

wherein a second device transmits environment information of the second device using a second communication method that is different from the first communication method.

20. The method of claim 9 , further comprising:

determining the device predicted to lose the network connection will lose the network connection; and

retraining the first AI model based on the device predicted to lose the network connection not losing the network connection.