In this publication several Near Field Communication (NFC) based sensor demonstrations and related measurements are discussed. These include basic temperature sensor applications and some more complex scenarios with external sensors and actuators. The reader device can be a commercial NFC enabled mobile phone or specially developed hardware. Based on the experience gathered with demonstrations and prototypes, the main features of an optimal NFC circuitry for low cost batteryless NFC enabled sensor devices are specified. Index Terms-batteryless, NFC peer-to-peer, Smart NFC Interface, ultra-low power, wireless sensors. Hillukkala Mika, Heiskanen Mikko, Ylisaukko-oja Arto 2009 First International Workshop on Near Field Communication 978-0-7695-3577-7/09 $25.00

The processes involved in the metallurgical industry consume significant amounts of energy and materials, so improving their control would result in considerable improvements in the efficient use of these resources. This study is part of the MORSE H2020 Project, and it aims to implement an operator support system that improves the efficiency of the oxygen blowing process of a real cast steel foundry. For this purpose, a machine learning agent is developed according to a reinforcement learning method suitable for the dynamics of the oxygen blowing process in the cast steel factory. This reinforcement learning agent is trained with both historical data provided by the company and data generated by an external model. The trained agent will be the basis of the operator support system that will be integrated into the factory, allowing the agent to continue improving with new and real experience. The results show that the suggestions of the agent improve as it gains experience, and consequently the efficiency of the process also improves. As a result, the success rate of the process increases by 12%.

The steelmaking industry is one of the most energy-intensive industries and is responsible for 4% of the world's total greenhouse gas emissions. Solutions to improve operational efficiency can therefore bring major improvements to the overall environmental performance of the entire industry. This article proposes a novel steel quality prediction system based on gradient boosting trees that can be used to predict the quality of steel products during manufacturing. The prediction system enables the detection of possible surface defects in the early phase of the manufacturing process, thus avoiding costly and time-consuming manufacturing efforts to address defective products. In this study, we trained a prediction model with data collected from an SSAB Europe steelmaking plant in Raahe, Finland. From the 296 process parameters measured in the liquid steel stage of steelmaking, we selected 89 input features to train and test the prediction model. The model was then integrated into a quality monitoring tool (QMT) to utilize real-time manufacturing data in its predictions. The validation process showed that the prediction model can find more than 50% of defective steel products by marking only about 10% of the steel products as potentially at risk of surface defects in plate rolling. This can potentially save time in the quality control phase and improve process efficiency. To gain more insights into the model predictions, we used SHAP (SHapley Additive exPlanations) to find a potential connection between the process input parameters and surface defects.

In this paper, we highlight considerations for synchronization issues in body area networks. Requirements for the synchronization accuracy in body area networks depend on the application at hand. Synchronization may be needed for power management, sample ordering, calculation of stimulus responses and for sensor fusion. This paper provides a theoretical exercise to help understand the accuracy required for typical human motion sensing. It gives an overview of various synchronisation strategies used and implemented in prototype systems. Lessons learnt from practical implementations using Bluetooth, an IEEE 802.15.4 proprietary network and Nanonet are presented to illustrate the principles involved.The discussion provides some considerations and the requirements for typical WBAN applications.