Higinio Mora-Mora

Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services.

The Internet of Things (IoT) has made it possible for devices around the world to acquire information and store it, in order to be able to use it at a later stage. However, this potential opportunity is often not exploited because of the excessively big interval between the data collection and the capability to process and analyse it. In this paper, we review the current IoT technologies, approaches and models in order to discover what challenges need to be met to make more sense of data. The main goal of this paper is to review the surveys related to IoT in order to provide well integrated and context aware intelligent services for IoT. Moreover, we present a state-of-the-art of IoT from the context aware perspective that allows the integration of IoT and social networks in the emerging Social Internet of Things (SIoT) term.

A Computational Architecture Based on RFID Sensors for Traceability in Smart Cities

Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal.

Real-time arithmetic unit

In this paper we discuss the paradigm of real-time processing on the lower level of computing systems. An arithmetical unit based on this principle containing addition, multiplication, division and square root operations is described. The development of the computation operators model is based on the imprecise computation paradigm and defines the concept of the adjustable calculation of a function that manages delay and the precision of the results as an inherent and parameterized characteristic. The arithmetic function design is based on well-known algorithms and offers progressive improvement in the results. Advantages in the predictability of calculations are obtained by means of processing groups of k-bits atomically and by using look-up tables. We report an evaluation of the operations in path time, delay and computation error. Finally, we present an example of our real-time architecture working in a realistic context.

µ-MAR

Many applications including object reconstruction, robot guidance, and scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown an it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the Signal-to-Noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a ∗Corresponding author ∗∗Principal corresponding author Email addresses: msaval@dtic.ua.es (Marcelo Saval-Calvo), jazorin@dtic.ua.es (Jorge Azoŕın-López), fuster@dtic.ua.es (Andrés Fuster-Guilló), hmora@dtic.ua.es (Higinio Mora-Mora) Preprint submitted to Elsevier ar X iv :1 70 8. 01 40 5v 1 [ cs .C V ] 4 A ug 2 01 7 common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Mathematical model of stored logic based computation

Emerging VLSI and ULSI integration technologies provide new possibilities for developing computational paradigms based on memories with pre-calculated data. A memory can behave like a processorwith complete functionality by simulating a classic Turingmachine. By means of this stored logic based architecture, the processor adopts a simple and regular internal organization. In addition, it makes the most of the inherent features in the memories and offers the possibility of reconfiguration by writing new results inside of it. This paper reviewsdifferent possibilities to usememory elements to performcomputations that would replace combinational logic processing of a given function. In this research, a computational model based on stored logic is described and interesting issues concerned withmemory utilization in processing are analyzed. A small functional unit based on these notions is presented.

Partial product reduction by using look-up tables for M×N multiplier

In this paper we present a new technique for partial product reduction in multiplication operations. The method is based on the construction of counter elements by means of look-up tables. The organization of these counters into reduction trees takes advantage of the inherent benefits of the integration of the memories and provides an alternative to classic operation methods. We show several reduction schemes that illustrate the proposed technique and describe hybrid examples that combine stored logic with classic combinational counters in order to adapt them better to each scheme. Our approach outperforms other schemes used for comparison. In this sense, not only an independent technology model has been established, but also an FPGA approximation has been implemented to measure such factors in a real-life technology platform.

Interpreting human activity from electrical consumption data using reconfigurable hardware and hidden Markov models

Human activity recognition is a promising research field in a wide variety of areas: ambient assisted living, pervasive and mobile computing, surveillance based security and context aware computing are some examples. In domestic environment, daily and frequent people activities use all kind of electric devices (appliances). Appliances connection or disconnection can provide useful data to know patterns of use, usual or unusual events and people behaviour, but smart meters only provide aggregated consumption data and cannot be used by the consumers to monitor individual actions or to know people behaviour. Furthermore, specialised systems for power load and monitoring are costly to install. This work proposes the design and development of low cost and embedded hardware tools to obtain disaggregated power consumption with the aim to interpret human activity. Non-intrusive load monitoring, design based on Wavelet Transform processing and Field Programmable Gate Arrays hardware implementation provide the necessary support to develop this kind of embedded systems. Human activity is classified using Hidden Markov models.

Function approximation on decimal operands

CORDIC is a well-known method to approximate mathematical functions. It basically works as an iterative algorithm for approximating rotation of a two-dimensional vector using only shift and add operations. The method has been widely applied in the design of digital signal processors and in the computation of typical signal processing functions. It was specifically developed to process data expressed in radix-2. On the other hand, decimal computation has been gaining renewed interest over the last few years, and high performance decimal computation systems are being required on different scopes. In this paper, an improved CORDIC-based method so as to approximate functions on decimal operands is proposed. The algorithm will work with BCD operands, so no conversion to/from radix-2 is needed. An important reduction in the number of iterations in comparison to other CORDIC methods is achieved. The new algorithm is implemented on an FPGA so as to obtain results on delay and hardware resources. The experiments showing the advantages of the new method, with regard to both delay and precision, are described.

Using virtual reality for industrial design learning: a methodological proposal

ABSTRACT Nowadays, the different computer tools available enable designers to create complex industrial prototypes. The use of these tools is constrained by the limitations imposed by common devices, such as screens and displays. Recently emerged virtual and augmented reality techniques have started being used as supports in many learning and industrial environments. Beyond the new possibilities that these tools offer for designing industrial objects, the underlying question is whether these new technologies could improve the creativity of designers to enable them to get a better understanding of the designing process itself. This paper presents a methodological proposal for the deployment of an industrial design engineering course aimed not only at learning different design techniques, but also at assessing the creativity skills of students. The practical contents include the use of virtual reality devices, to help the designer overcome the limitations of prototype visualisation and make better designing decisions. Moreover, a creativity test will be performed at the beginning and at the end of the course to assess the changes in creativity skills taking place within the experiment group versus the changes in a traditional learning (control) group.

Jaya optimization algorithm with GPU acceleration

Optimization methods allow looking for an optimal value given a specific function within a constrained or unconstrained domain. These methods are useful for a wide range of scientific and engineering applications. Recently, a new optimization method called Jaya has generated growing interest because of its simplicity and efficiency. In this paper, we present the Jaya GPU-based parallel algorithms we developed and analyze both parallel performance and optimization performance using a well-known benchmark of unconstrained functions. Results indicate that parallel Jaya implementation achieves significant speed-up for all benchmark functions, obtaining speed-ups of up to