---> CPE WAN Management Protocol**) Implementation of multithreaded download and upload parameters compliant with TR-143 specifications.**) Library upgrade for TLS/SSL support, implementation of XMPP protocol tests for robust client-server communication, and enhancement of XMPP code for instant reconnection after network disruptions ensured overall improved performance.**) STUN protocol testing and integration of credentials encryption module for connection requests.**) Resolution of TR-069 events bugs during CWMP endpoint and ACS connection.**) Configuration of WAN parameters and alignment of TR-181 Ethernet parameters with OpenWRT 22.**) Engineering of a comprehensive USP controller for overseeing and controlling connected USP agents and fixing bugs related to Firmware Download and upgrade operations.---> Wi-Fi and EasyMesh**) Engineering of TR-181 parameters for Wi-Fi devices.**) Update of TR-181 Wi-Fi object for alignment with OpenWRT 22.**) Development of services using 'procd' in OpenWRT.**) Resolution of bugs related to SSID MAC addresses and statistics.**) Implementation of Wi-Fi network scanning and neighbor display module.**) Implementation of Python functional tests for Wi-Fi module.===> EasyMesh - prplMesh**) Orchestration of prplMesh integration into router firmware, supporting various OpenWrt versions and diverse hardware models.**) Conducting Python tests for EasyMesh roaming functionality.**) Authoring of detailed documentation for solution building and EasyMesh setup.**) Merge of TR-181 Wi-Fi Data Elements parameters into Piva CWMP solution.== Theoretical Skills:TR-069, TR-369, CWMP, XMPP, STUN, UPNP, MQTT, HTTP, FTP, TCP/UDP, NAT, WiFi, IEEE 802.11 a/b/g/n/ac, wireless security protocols.== Other Skills: UCI, UBUS, OPKG, cross-compilation, Valgrind, GDB server, events handling, multithreading, debugging, memory handling.

The internship aim is the improvement of an operational try-on solution in terms of precision, loading time and inference time.To achieve the goals of the internship:- I refactored the code of the existent solution. In fact, that was a new significant task for me since, it is a challenging mission to understand the problematic design and the code hierarchy at the same time.- I enlarged my mathematic and theoretical notions of neural networks namely CNN.- I strengthen my knowledge of Tensorflow framework and discovered for the first time Tensorflow.js, "The browser version of Tensorflow."- I learned node.js basics.- I revised models architectures to reduce the solution design complexity.- I experimented more than one solution to low-light try-on experiences.- I enlarged my theoretical and technical fundamentals of LSTM and recurrent neural networks in general.- I improved my ability of generating and handling big amount of data.

This internship is my first experience with working in a professional environment.During these two months I learned the value of communication and sharing constructive ideas added to the significance of accepting to be jugged and to be convincing at the same time.The internship aim was to trace players in a stadium:- Track them.- Generate their heatmap.To achieve the goals of the internship:- I strengthen my knowledge in the field of Deep learning and namely CNN and tracking algorithms (YOLO, SSD).- I worked more and more with Python, Tensorflow and OpenCV.- I discovered the tracking mechanism of DeepSort algorithm.- I experienced, for the same time the effectiveness of K-means as an unsupervised learning algorithm.