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We have developed LoRaMesher, an on-going implementation for doing mesh networking with LoRa nodes. https://github.com/LoRaMesher/LoRaMesher The TFM will develop LoRaMesher further on a specific topic, such as embedded systems, network level, machine learning or application level, according to the interest.
We have developed LoRaMesher, an on-going implementation for doing mesh networking with LoRa nodes.
https://github.com/LoRaMesher/LoRaMesher
LoRaMesher is base on this protocol design: https://upcommons.upc.edu/bitstream/handle/2117/347444/A_minimalistic_distance_vector_routing_protocol_for_LoRa_mesh_networks.pdf?sequence=1
LoRa is a communication technology for IoT applications. It is typically used to send small amounts of data from the sensor node to a gateway (this is the so-called LoRaWAN architecture). But with LoRaMesher another network topology is also possible: to do mesh networking with LoRa among sensor nodes.
What for? E.g. for wildlife preservation:
https://www.hackster.io/mithun-das/mahout-save-the-elephants-819b54
Technical details about LoRaMesher: Code is in C++. The implementation leverages RTOS to perform the functions.
We deploy LoRaMesher on ESP32 LoRa boards, such as the T-Beam (e.g. https://tienda.bricogeek.com/arduino-compatibles/1502-ttgo-t-beam-esp32-wifi-gps-neo-6m-lora-868-mhz.html).
A project with LoRaMesher can focus on a specific topic (embedded systems, network level, machine learning or application level) according to interest.
* improving the LoRaMesher protocoll design and implementation, e.g.
- design, implementation and evaluation of different protocol alternatives for reliable messaging with LoRaMesher
- explore different metrics for the routing table in LoRaMesher (currently we use hops, but it is not reflecting the link quality, leading to suboptimal performance in heterogeneous links)
* machine learning.
- We have an initial federated learning prototype application that runs over LoRaMesher, a first steo to go further.
* applications that use LoRaMesher as a communication layer
- We have already developed a demo application called LoRaChat. A user connects the Android bluetooth terminal and can chat with other users in the LoRaMesh network.
https://github.com/Jaimi5/LoRaChat
A similar application is that of Meshtastic. https://meshtastic.org
- We currently work on an IoT monitoring application which spans over the LoRa mesh network and services in Internet.
It could be very interesting to demonstrate this concept of interconnected LoRa and Internet services with a new application. We would like to create and test new applications which (in part) use the LoRaMesh network. These application can have an Android app (if the application is end user oriented) or the code can run entirely on the IoT board (maybe a "tracker" for a Peer-to-Peer system, and then integrate the LoRa mesh implementation as a library.
* embedded systems: We would like to port LoRaMesher to the Arduino Portenta board (LoRaMesher currently runs only on ESP32 boards). We have the board ready with LoRa radio. But the FreeRTOS usage that we make in LoRaMesher has to be "translated" into the equivalent in MBedOS.
Se trata de utilizar técnicas de visión por ordenador para detectar los movimientos y trayectorias del portero, el balón y un jugador atacante para extraer y analizar datos y plantear mejoras en entrenamientos.
Se trata de utilizar técnicas de visión por ordenador para detectar los movimientos y trayectorias del portero, el balón y un jugador atacante para extraer y analizar datos y plantear mejoras en entrenamientos. Se espera usar cámaras para grabar situaciones del partido y posteriormente analizarlas con herramientas como opencv en python.
Amb el present projecte es pretén visualitzar, en temps real, dades procedents de simulacions CFD. Aquestes dades es troben emmagatzemades en fitxers que són el resultat de simular fenòmens físics com foc, fum o vent al llarg d'un interval de temps. El projecte consisteix en desenvolupar una eina que permeti visualitzar l'estat del fenòmen per cada instant de temps utilitzant algorismes de visualització de dades volumètriques.
S'ofereix una beca d'iniciació a la recerca de 20 hores/setmana amb un salari aprox. de 600 Euros/mes per realitzar el TFM en el marc del projecte Eprivo.eu.
Internet services are known to collect large amounts of personal information. As a result, more than half of EU citizens are concerned about their online privacy. In this context, data brokers are companies devoted to collecting and selling personal information to other companies. Data brokers are often implemented as third-party trackers, which allow them to gain visibility across the Internet. Recent works show this personal information is not only used for targeted advertising, but also for more obscure practices, such as price discrimination, credit scoring, phishing or identity theft. The project addresses these growing privacy concerns by enhancing ePrivo, a new online privacy observatory. ePrivo will continuously scan the Internet to unveil third-party trackers, the tracking methods they use and the data brokers behind them. A proof-of-concept prototype of ePrivo is already available at https://eprivo.eu. In this project, we will deploy the ePrivo service in production, extend its capabilities for web tracking and phishing detection, and release it under an open-source license. The results will be useful to the RIPE community, including ISPs, network operators, Internet users, policy makers and researchers.
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