Rafael J. Valdivieso-Sarabia

Vision Based Extraction of Dynamic Gait Features Focused on Feet Movement Using RGB Camera

Bipedal gait involves the entire body but some subsystems are decisive for gait while other parts of the body play complementary roles (dynamic balance, harmony of movement, etc.). We have proposed a functional specification of gait. It is based on logical expression format and takes into account only observational kinematic aspects. The specification is open enough that it can be used in other gait analysis problems (rehabilitation, sport, children, etc.).

Vision Based Gait Analysis for Frontal View Gait Sequences Using RGB Camera

In this paper we propose a vision based gait analysis approach to work with frontal view sequences. The main issue of sagittal view gait sequences is the physical space required to record them. We propose two different approaches to obtain heel strike and toe off with frontal gait, both of them are based in the time series of the difference of component y of both feet. In the former, the zero crosses are used to determine the range in which heel strike and toe off occurs. In the latter, the maxima and minima are used instead. Testing our approach with our own dataset show that it is possible to obtain heel strike and toe off events using only frontal view gait sequences recorded with an RGB camera. Results show as well that it is possible to classify between normal and abnormal gait using frontal view.

Developing a Context Aware System for Energy Management in Urban Areas

To achieve energy self-sufficiency in housing, it is necessary to know the capacity of microgeneration of systems and the real needs of consumption of the users. Each house includes a microgeneration system based on the use of sustainable energy. In theoretical conditions, the design is capable of satisfying entirely its energy needs. However in real conditions there are situations in which it is necessary more energy, and others on the contrary, it produces more energy than necessary. This paper proposes the use of context-aware paradigm that integrate ubiquitous sensor network for the optimization of the energy resource available. The goal is to achieve the maximum energy efficiency during the distribution, in real time and according to energy demand in housings and community equipments. Using context-aware paradigm the system obtains environmental information, determines the profile of consumption of the users and calculates the instantaneous energy needs. This information is obtained from ubiquitous networks and will be used by systems of distribution of the electrical grid of the group of housings. Different paradigms of communication are used that provides the necessary support to achieve near real time. These paradigms are based on the protocols used in the development of the Internet of things.

Distributed Optimization of Finite Resource Planning for Asincronous and Non-linear Systems: Application to Power Management

This paper introduces a Multiagent System (MAS) for optimal resource planning in non-linear systems. The distributed planning strategy, which is based on interaction of agents, is composed by two phases. The first one uses an iterative double auction based protocol and allows requesting for getting back the previously allocated resources in order to establish a better planning. The second phase takes the previous resource allocation for finding better alternative paths. The proposal has been applied into our house-lab power system for optimize the use of renewable power supplies. Power production and requirements are simulated using the average of power consumption measures of each component.

Intelligent Power Management System Using Hybrid Renewable Energy Resources and Decision Tree Approach

Optimal power usage and consumption require continuous monitoring, forecasting electric energy consumption and renewable generation. To facilitate integration of renewable energies and optimize their resources, new communication and data processing technologies are used in new projects. This article shows the works and results obtained in the eoTICC project. The objective is to design and develop an intelligent energy manager using the Archimedes wind turbine and a solar generation system, both integrated in industrial and residential power facilities. Solutions based on Artificial Intelligence paradigms and Internet of Things protocols allow automatic decision making to optimize energy management. In a facility, the energy demand and weather forecasts can be known by an intelligent energy manager. With these conditions, the energy manager can develop rules based on decision trees to automate control actions aimed at optimizing the use of energy. This article shows the architecture of IoT infrastructure and the first rules designed in the project. The result obtained provides improvements in the use of renewable energy in current facilities that do not use this type of intelligent management. The improvements allow to use the energy at the time of generation, avoiding unnecessary storage.

Gait Analysis Using Computer Vision Based on Cloud Platform and Mobile Device

Frailty and senility are syndromes that affect elderly people. The ageing process involves a decay of cognitive and motor functions which often produce an impact on the quality of life of elderly people. Some studies have linked this deterioration of cognitive and motor function to gait patterns. Thus, gait analysis can be a powerful tool to assess frailty and senility syndromes. In this paper, we propose a vision-based gait analysis approach performed on a smartphone with cloud computing assistance. Gait sequences recorded by a smartphone camera are processed by the smartphone itself to obtain spatiotemporal features. These features are uploaded onto the cloud in order to analyse and compare them to a stored database to render a diagnostic. The feature extraction method presented can work with both frontal and sagittal gait sequences although the sagittal view provides a better classification since an accuracy of 95% can be obtained.

Scheduler for Automatic Management of Maintenance Jobs in Large-Size Systems: A Case Study Applied to Smart City

Maintenance of systems such as infrastructure, services and equipment on city context requires a complex management process in order to provide quality services, comply with regulations and extend lifespan of urban equipment and infrastructure without neglecting the proper use of resources to execute maintenance jobs. Cities can generate hundreds or thousands of maintenance jobs during a particular time period. These jobs can be generated automatically by equipment or can be reported by citizens/users. This work introduces a scheduling architecture for automatic management of maintenance jobs. The proposal is able to handle preventive and corrective maintenance jobs looking for available human and instrumental resources during the common time period required by the job to be executed. The scheduler uses intelligent strategies to satisfy constraints of each job in order to get a scheduling according to the criterion of the manager of maintenance. A case study is applied to smart city.

Distributed Power Management System with Dynamic Load Management Based on Multi-agent System for Smart Grid

Power management in city electrical network has some challenges like to enhance renewable power supply, optimize distribution or network’s integrity. Usually, conventional parameters are considered like costs and power constraints but load management is ignored to reduce environmental impact that energy generation produces as well as other aspects are ignored too. To address these limitations, a proposal based on a multi-agent system, which is developed in JADE framework, is introduced. The demand satisfaction is conditioned to the available power by mean of strategies oriented to control consuming spikes and to satisfy the future power demand as long as possible. Electrical network of a medium-size city is simulated to show the complex equilibrium that must be made to attend energy requests coming from a set of consuming centres. This study case let us confirm the feasibility of the power supply solution based on load management, in this context.