SIRCo: uma arquitetura para Sensoriamento Inteligente de Rádios Cognitivos

The increased demand for using the Industrial, Scientific and Medical (ISM) unlicensed frequency spectrum has caused interference problems and lack of resource availability for wireless networks. Cognitive radio (CR) have emerged as an alternative to reduce interference and intelligently use the spectrum. Several protocols were proposed aiming to mitigate these problems, but most have not been implemented in real devices. This work presents an architecture for Intelligent Sensing for Cognitive Radios (ISCRa), and a spectrum decision model (SDM) based on Artificial Neural Networks (ANN), which uses as input a database with local spectrum behavior and a database with primary users information. For comparison, a spectrum decision model based on AHP, which employs advanced techniques in its spectrum decision method was implemented. Another spectrum decision model that considers only a physical parameter for channel classification was also implemented. Spectrum decision models evaluated, as well as ISCRa's architecture were developed in GNU-Radio framework and implemented on real nodes. Evaluation of SDMs considered metrics of: delivery rate, latency (Round Trip Time - RTT) and handoff. Experiments on real nodes showed that ISCRa architecture with ANN based SDM increased packet delivery rate and presented fewer frequency variation (handoff) while maintaining latency. Considering higher bandwidth as application's Quality of Service requirement, ANN-SDM obtained the best results when compared to other SDM for cognitive radio networks (CRN).

Rotulagem como mecanismo de compartilhamento de informações com agentes da cadeia produtiva do café

The Agroindustrial System coffee after decades of state regulation has become a decentralized economic activity. This situation compelled most of the actors in the production chain to resort to self r egulatory systems offered by certification agencies, which have specific criteria and procedures. However the diversity criteria of the agencies do not offer resources able to ensure efficient management of the governance structure. There is a need to reduce the asymmetry of information, which is possible through the sharing of data compatible with the production tracking feature. This work is supported in this contextualized problem, based on Transaction Cost Theory and the use of qualitative and quantitative research methodologies. The first part of the work seeks to know the procedures required by leading regulatory agencies in Brazil, with perspective to emphasize the similarities and compatibilities between them, which was reached after analysis of standards and comparison of similarities. Next is registered the operation and the coffee traceability of the structure, in order to identify, through observation, documental and bibliographical analysis, the systems in place and traceable information in line with the recommendations of the coffee certification. Finally, he sought to create a labeling model that allows to generate and share information about the product from the field to the sale for consumption. The information obtained in the previous steps were the basis for data collection with the production chain agents through a structured questionnaire administered to 618 agents of the production chain, whose answers were treated by multivariate methods of statistical analysis. The results showed that actors in the chain are in favor of inclusion and sharing information related to rural production and economic and environmental data. This knowledge enabled develop a labeling model where the information sharing agents is an efficient mechanism to mitigate the governance problems identified.