Using Multi-Layer Perceptrons to Enhance the Performance of Indoor RTLS

Accuracy in indoor Real-Time Locating Systems (RTLS) is still a problem requiring novel solutions. Wireless Sensor Networks are an alternative to develop RTLS aimed at indoor environments. However, there are some effects associated to the propagation of radio frequency waves, such as attenuation, diffraction, reflection and scattering that depends on the materials and the objects in the environment, especially indoors. These effects can lead to other undesired problems, such as multipath. When the ground is the main responsible for waves reflections, multipath can be modeled as the ground reflection effect. This paper presents a model for improving the accuracy of RTLS, focusing on the mitigation of the ground reflection effect and the estimation of the final position by using Neural Networks

Trends in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection

PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2014 special sessions: Agents Behaviours and Artificial Markets (ABAM), Agents and Mobile Devices (AM), Bio-Inspired and Multi-Agents Systems: Applications to Languages (BioMAS), Multi-Agent Systems and Ambient Intelligence (MASMAI), Self-Explaining Agents (SEA), Web Mining and Recommender systems (WebMiRes) and Intelligent Educational Systems (SSIES)

Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks

Lagrange interpolation on conics and cubics

seminario matemático “garcia de galdeano” garcía de galdean