In this paper, we propose to implement a meteorological monitoring station using embedded systems. This model is possible thanks to different sensors that enable us to measure several environmental parameters, such as i) relative humidity, ii) average ambient temperature, iii) soil humidity, iv) rain occurrence, and v) light intensity. The proposed system is based on a field-programmable gate array device (FPGA). The proposed design aims at ensuring high-resolution data acquisition and at predicting samples with precision and accuracy in real-time. To present the collected data, we develop also a web application with a simple and friendly user interface.

FPGA Based Meteorological Monitoring Station

Learning-based Energy Consumption Prediction

BCI System using a Novel Processing Technique Based on Electrodes Selection for Hand Prosthesis Control

The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the controller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse-Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.

/pdf/monitoring-a-turkey-hatchery-based-on-a-cyber-physical-13d28956rt.pdf

Monitoring a turkey hatchery based on a cyber-physical system

Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.

Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA

At this moment in the field of FPGA, only RAM tests have been carried out to evaluate its performance but these works have not focused on tracking memory usage in real time, this paper proposes a design for monitoring the memory of an embedded system, in the logical part, making use of the communication between the FPGA and the HPS. In addition, the HPS has implemented a web service that allows to visualize a graph of the monitoring in real time. The proposed design can be an introduction to the development of applications that can be specifically monitored for a component of the embedded system in FPGA, because FPGA is currently being used for different purposes such as machine learning, real-time image processing, mining of Bitcoins, among others. These applications are quite robust, which implies a high demand for processing for the embedded system.

/pdf/monitoring-of-system-memory-usage-embedded-in-fpga-52a4wodq26.pdf

Luis Macas Lopez

Papers

Monitoring of system memory usage embedded in FPGA