1) A method of managing messages in a communication device, the method comprising:-receiving, by an intelligent messenger device, one or more messages via a communication
device; identifying dynamically, by the intelligent messenger device, one or more critical content
in the one or more messages and determining one or more critical messages based on the
identification; analyzing, by the intelligent messenger device, the one or more critical messages based on
the content and context associated with the one or more critical messages and assigning
vocabulary weight to each of the one or more critical content and a context weight to the critical
message;
generating, by the intelligent messenger device, a priority to each of the one or more
critical messages based on the analysis; queuing, by the intelligent messenger device, the one or more messages based on the
priority of each of the one or more critical messages; dynamically allocating resources, by the intelligent messenger device, by adjusting at least
one of buffer, and packet delay associated with the communication device based on the priority
of the one or more messages in the queue; managing, by the intelligent messenger device, the one or more messages in the
communication device based on the queuing and the dynamic allocation of resources.
2. The method as claimed in claim 1, wherein the managing comprises at least one of transmitting and receiving the one or more messages via the communication device.
3. The method as claimed in claim 1, wherein queuing is based on the priority of each of the one or more critical messages and at least one of historical information, presence of one or more critical messages in the packet buffer and availability of the packet buffer associated with the communication device.
4. The method as claimed in claim 1, wherein the one or more messages comprise at least one of audio, video, and text messages.
5. The method as claimed in claim 1, wherein the one or more critical content is identified based
on one or more predefined keywords and wherein assigning the vocabulary weight to each of the

one or more critical content is based on pre-defined weight associated with the one or more pre¬defined keywords.
6. The method as claimed in claim 1, wherein the context weight is assigned based on sentiment analysis of the one or more critical messages using a convolutional neural network (CNN) and contextual analysis of the messages using natural language processing (NLP).
7. The method as claimed in claim 1, wherein dynamically allocating the resources further comprises one of invocation or revocation of one or more application running in the communication device.
8. An intelligent messenger device for managing messages in a communication device comprising:
a processor; and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to:
receive one or more messages via a communication device;
identify dynamically one or more critical content in the one or more messages and determining one or more critical messages based on the identification;
analyze the one or more critical messages based on the content and context associated with the one or more critical messages and assigning vocabulary weight to each of the one or more critical content and a context weight to the critical message;
generate a priority to each of the one or more critical messages based on the analysis;
queue the one or more messages based on the priority of each of the one or more critical messages;
dynamically allocate resources by adjusting at least one of packet buffer, and packet delay associated with the communication device based on the priority index of the one or more messages in the queue;
manage the one or more messages in the communication device based on the queuing and the dynamic allocation of resources.
9. The device as claimed in claim 8, wherein the managing comprises at least one of transmitting and receiving the one or more messages via the communication device.

10. The device as claimed in claim 8, wherein queuing is based on the priority of each of the
one or more critical messages and at least one of historical information, presence of one or
more critical messages in the packet buffer and availability of the packet buffer associated
with the communication device.
11. The device as claimed in claim 8, wherein the one or more messages comprise at least one of audio, video, and text messages.
12. The device as claimed in claim 8, wherein the one or more critical content is identified based on one or more predefined keywords and wherein assigning the vocabulary weight to each of the one or more critical content is based on a pre-defined weight associated with the one or more pre-defined keywords.
13. The method as claimed in claim 8, wherein the context weight is assigned based on sentiment analysis of the one or more critical messages using a convolutional neural network (CNN) and contextual analysis of the messages using natural language processing (NLP).
14. The device as claimed in claim 8, wherein dynamically allocating the resources further comprises one of invocation or revocation of one or more application running in the communication device.