Jerónimo Mora-Pascual

Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture

The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched.

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.

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.

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.).

A Quantitative Comparison of Calibration Methods for RGB-D Sensors Using Different Technologies

RGB-D (Red Green Blue and Depth) sensors are devices that can provide color and depth information from a scene at the same time. Recently, they have been widely used in many solutions due to their commercial growth from the entertainment market to many diverse areas (e.g., robotics, CAD, etc.). In the research community, these devices have had good uptake due to their acceptable level of accuracy for many applications and their low cost, but in some cases, they work at the limit of their sensitivity, near to the minimum feature size that can be perceived. For this reason, calibration processes are critical in order to increase their accuracy and enable them to meet the requirements of such kinds of applications. To the best of our knowledge, there is not a comparative study of calibration algorithms evaluating its results in multiple RGB-D sensors. Specifically, in this paper, a comparison of the three most used calibration methods have been applied to three different RGB-D sensors based on structured light and time-of-flight. The comparison of methods has been carried out by a set of experiments to evaluate the accuracy of depth measurements. Additionally, an object reconstruction application has been used as example of an application for which the sensor works at the limit of its sensitivity. The obtained results of reconstruction have been evaluated through visual inspection and quantitative measurements.

Mathematical model and implementation of rational processing

Precision in computations is a considerable challenge to adequately addressing many current scientific or engineering problems. The way in which the numbers are represented constitutes the first step to compute them and determines the validity of the results. The aim of this research is to provide a formal framework and a set of computational primitives to address high precision problems of mathematical calculation in engineering and numerical simulation. The main contribution of this research is a mathematical model to build an exact arithmetical unit able to represent without error rational numbers in positional notation system. The functions under consideration are addition and multiplication because they form an algebraic commutative ring which contains a multiplicative inverse for every non-zero element. This paper reviews other specialized arithmetic units based on existing formats to show ways to make high precision computing. It is proposed a formal framework of the whole arithmetic architecture in which the operators are based. Then, the design of the addition operation is detailed and its hardware implementation is described. Finally, extensive evaluation of this operator is performed to prove its ability for exact processing. It is introduced a formal framework for processing rational numbers.A representation system based on positional notation system is described.A method for calculating the addition function is detailed.Experiments and application example have been made to validate the model.

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.

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.

Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm

The Iterative Closest Point (ICP) algorithm is currently one of the most popular methods for rigid registration so that it has become the standard in the Robotics and Computer Vision communities. Many applications take advantage of it to align 2D/3D surfaces due to its popularity and simplicity. Nevertheless, some of its phases present a high computational cost thus rendering impossible some of its applications. In this work, it is proposed an efficient approach for the matching phase of the Iterative Closest Point algorithm. This stage is the main bottleneck of that method so that any efficiency improvement has a great positive impact on the performance of the algorithm. The proposal consists in using low computational cost point-to-point distance metrics instead of classic Euclidean one. The candidates analysed are the Chebyshev and Manhattan distance metrics due to their simpler formulation. The experiments carried out have validated the performance, robustness and quality of the proposal. Different experimental cases and configurations have been set up including a heterogeneous set of 3D figures, several scenarios with partial data and random noise. The results prove that an average speed up of 14% can be obtained while preserving the convergence properties of the algorithm and the quality of the final results.