Creation of value with open source software in the telecommunications field

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Voice and rural wireless mesh community networks: a framework to quantify scalability and manage end-user smartphone battery consumption

Philosophiae Doctor - PhDCommunity wireless mesh initiatives are a pioneering option to cheap ‘last-mile’ access to network services for rural low-income regions primarily located in Sub-Saharan Africa and Developing Asia. However, researchers have criticized wireless mesh networks for their poor scalability; and scalability quantification research has mostly consisted of modularization of per-node throughput capacity behaviour. A scalability quantification model to design wireless mesh networks to provide adequate quality of service is lacking. However, scalability quantification of community mesh networks alone is inadequate because rural users need affordable devices for access; and they need to know how best to use them. Low-cost low-end smartphones offer handset affordability solutions but require smart management of their small capacity battery. Related work supports the usage of Wi-Fi for communication because it is shown to consume less battery than 2G, 3G or Bluetooth. However, a model to compare Wi-Fi battery consumption amongst different low-end smartphones is missing, as is a comparison of different over-the-top communication applications

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems