Real-time performance of an open-source protocol stack for low-cost, embedded systems

ETFA2011 ◽  
2011 ◽  
Author(s):  
Ivan Cibrario Bertolotti ◽  
Tingting Hu
Keyword(s):  
Embedded Systems ◽  
Open Source ◽  
Real Time ◽  
Low Cost ◽  
Protocol Stack ◽  
Time Performance

scholarly journals Arduino based platform for process control learning

2020 ◽  
Vol 6 (5) ◽  
pp. 0585-0593
Author(s):  
Bruna Couto Molinar Henrique ◽  
Leonardo Couto Molinar Henrique ◽  
Humberto Molinar Henrique
Keyword(s):  
Open Source ◽  
Real Time ◽  
Low Cost ◽  
Control Unit ◽  
Absolute Error ◽  
Internal Model Control ◽  
Pid Controllers ◽  
Experimental Unit ◽  
Source Codes ◽  
Model Control

This work deals with implementation of an experimental flowrate control unit using free and low-cost hardware and software. The open-source software Processing was used to develop the source codes and user graphical interface and the open-source electronic prototyping platform Arduino was used to acquire data from an experimental unit. Work presents descriptions of the experimental setup, the real-time PID controllers used and theoretical/conceptual issues of Arduino. PID controllers based on internal model control, minimization of the integral of time-weighted absolute error, Ziegler-Nichols, and others were tuned for setpoint and load changes and real-time runs were carried out in order to make real-time use of  control theory learned in academy. Results showed the developed platform proved to be suitable for use in experimental setups allowing users compare their ideas and expectations with the experimental evidence in a real and low-cost fashion. In addition, the instrumentation is simple to configure with acceptable level noise and particularly useful for control/automation learning with educational purposes.

scholarly journals Open source modules for tracking animal behavior and closed-loop stimulation based on Open Ephys and Bonsai

2018 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Mikkel Elle Lepperød ◽  
Svenn-Arne Dragly ◽  
Philipp Häfliger ◽  
Marianne Fyhn ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Closed Loop ◽  
Low Cost ◽  
Data Formats ◽  
Behavioral Tracking ◽  
Real Time Tracking ◽  
Set Up ◽  
And Behavior ◽  
Closed Loop Stimulation

AbstractObjectiveA major goal in systems neuroscience is to determine the causal relationship between neural activity and behavior. To this end, methods that combine monitoring neural activity, behavioral tracking, and targeted manipulation of neurons in closed-loop are powerful tools. However, commercial systems that allow these types of experiments are usually expensive and rely on non-standardized data formats and proprietary software which may hinder user-modifications for specific needs. In order to promote reproducibility and data-sharing in science, transparent software and standardized data formats are an advantage. Here, we present an open source, low-cost, adaptable, and easy to set-up system for combined behavioral tracking, electrophysiology and closed-loop stimulation.ApproachBased on the Open Ephys system (www.open-ephys.org) we developed multiple modules to include real-time tracking and behavior-based closed-loop stimulation. We describe the equipment and provide a step-by-step guide to set up the system. Combining the open source software Bonsai (bonsai-rx.org) for analyzing camera images in real time with the newly developed modules in Open Ephys, we acquire position information, visualize tracking, and perform tracking-based closed-loop stimulation experiments. To analyze the acquired data we provide an open source file reading package in Python.Main resultsThe system robustly visualizes real-time tracking and reliably recovers tracking information recorded from a range of sampling frequencies (30-1000Hz). We combined electrophysiology with the newly-developed tracking modules in Open Ephys to record place cell and grid cell activity in the hippocampus and in the medial entorhinal cortex, respectively. Moreover, we present a case in which we used the system for closed-loop optogenetic stimulation of entorhinal grid cells.SignificanceExpanding the Open Ephys system to include animal tracking and behavior-based closed-loop stimulation extends the availability of high-quality, low-cost experimental setup within standardized data formats serving the neuroscience community.

scholarly journals Open-Source FPGA Coprocessor for the Doppler Emulation of Moving Fluids

Micromachines ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1549
Author(s):  
Stefano Ricci
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Open Source ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Synthetic Signal ◽  
Doppler System ◽  
Wide Range ◽  
Field Programmable ◽  
Moving Fluid

Embedded systems are nowadays employed in a wide range of application, and their capability to implement calculation-intensive algorithms is growing quickly and constantly. This result is obtained by the exploitation of powerful embedded processors that are often connected to coprocessors optimized for a particular application. This work presents an open-source coprocessor dedicated to the real-time generation of a synthetic signal that mimics the echoes produced by a moving fluid when investigated by ultrasounds. The coprocessor is implemented in a Field Programmable Gate Array (FPGA) device and integrated in an embedded system. The system can replace the complex and inaccurate flow-rigs employed in laboratorial tests of Doppler ultrasound systems and methods. This paper details the coprocessor and its standard interfaces, and shows how it can be integrated in the wider architecture of an embedded system. Experiments showed its capability to emulate a fluid flowing in a pipe when investigated by an echographic Doppler system.

scholarly journals DSCBlocks: An Open-Source Platform for Learning Embedded Systems Based on Algorithm Visualizations and Digital Signal Controllers

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 228 ◽  
Author(s):  
Jonathan Álvarez Ariza
Keyword(s):  
Operating System ◽  
Embedded Systems ◽  
Open Source ◽  
Real Time ◽  
Processing Speed ◽  
Digital Signal ◽  
C Language ◽  
Real Time Operating System ◽  
Models Of Development ◽  
Educational Methodology

DSCBlocks is an open-source platform in hardware and software developed in JavaFX, which is focused on learning embedded systems through Digital Signal Controllers (DSCs). These devices are employed in industrial and educational sectors due to their robustness, number of peripherals, processing speed, scalability and versatility. The platform uses graphical blocks designed in Google’s tool Blockly that can be used to build different Algorithm Visualizations (AVs). Afterwards, the algorithms are converted in real-time to C language, according to the specifications of the compiler for the DSCs (XC16) and they can be downloaded in one of the two models of development board for the dsPIC 33FJ128GP804 and dsPIC 33FJ128MC802. The main aim of the platform is to provide a flexible environment, drawing on the educational advantages of the AVs with different aspects concerning the embedded systems, such as declaration of variables and functions, configuration of ports and peripherals, handling of Real-Time Operating System (RTOS), interrupts, among others, that are employed in several fields such as robotics, control, instrumentation, etc. In addition, some experiments that were designed in the platform are presented in the manuscript. The educational methodology and the assessment provided by the students (n = 30) suggest that the platform is suitable and reliable to learn concepts relating to embedded systems.

scholarly journals Research on a Low-Cost, Open-Source, and Remote Monitoring Data Collector to Predict Livestock’s Habits Based on Location and Auditory Information: A Case Study from Vietnam

Agriculture ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 180 ◽  
Author(s):  
Ha Quang Thinh Ngo ◽  
Thanh Phuong Nguyen ◽  
Hung Nguyen
Keyword(s):  
Open Source ◽  
Real Time ◽  
High Speed ◽  
High Reliability ◽  
Low Cost ◽  
Monitoring Data ◽  
Farm Animals ◽  
Auditory Information ◽  
Fast Tracking ◽  
Data Collector

The supervision and feeding of grazing livestock are always difficult missions. Since animals act based on habits, the real-time monitoring data logger has become an indispensable instrument to assist farmers in recognizing the status of livestock. Position-tracked and acoustic monitoring have become commonplace as two of the best methods to characterize feeding performance in ruminants. Previously, the existing methods were limited to desktop computers and lacked a sound-collecting function. These restrictions impacted the late interventions from feeders and required a large-sized data memory. In this work, an open-source framework for a data collector that autonomously captures the health information of farm animals is introduced. In this portable hardware, a Wireless Location Acoustic Sensing System (WiLASS) is integrated to infer the health status through the activities and abnormal phenomena of farming livestock via chew–bite sound identification. WiLASS involves the open modules of ESP32-WROOM, GPS NEO-6M, ADXL335 accelerometer, GY-MAX4466 amplifier, temperature sensors, and other signal processing circuits. By means of wireless communication, the ESP32-WROOM Thing micro-processor offers high speed transmission, standard protocol, and low power consumption. Data are transferred in a real-time manner from the attached sensing modules to a digital server for further analysis. The module of GPS NEO-6M Thing brings about fast tracking, high precision, and a strong signal, which is suitable for highland applications. Some computations are incorporated into the accelerometer to estimate directional movement and vibration. The GY-MAX4466 Thing plays the role of microphone, which is used to store environmental sound. To ensure the quality of auditory data, they are recorded at a minimum sampling frequency of 10 KHz and at a 12-bit resolution. Moreover, a mobile software in pocket devices is implemented to provide extended mobility and social convenience. Converging with a cloud-based server, the multi-Thing portable platform can provide access to simultaneously supervise. Message Queuing Telemetry Transport (MQTT) protocol with low bandwidth, high reliability, and bi-direction, and which is appropriate for most operating systemsOS, is embedded into the system to prevent data loss. From the experimental results, the feasibility, effectiveness, and correctness of our approach are verified. Under the changes of climate, the proposed framework not only supports the improvement of farming techniques, but also provides a high-quality alternative for poor rural areas because of its low cost and its ability to carry out a proper policy for each species.

scholarly journals An open source Real Time IOT based environmental sensor monitoring system

10.29007/q4cf ◽  
2018 ◽  
Author(s):  
Ronak Vithlani ◽  
Siddharth Fultariya ◽  
Mahesh Jivani ◽  
Haresh Pandya
Keyword(s):  
Embedded System ◽  
Open Source ◽  
Real Time ◽  
Monitoring System ◽  
Information Structure ◽  
Low Cost ◽  
Environmental Parameters ◽  
Test Bed ◽  
Network Construction ◽  
Embedded Sensing

In this paper, we have described an operative prototype for Internet of Things (IoT) used for consistent monitoring various environmental sensors by means of low cost open source embedded system. The explanation about the unified network construction and the interconnecting devices for the consistent measurement of environmental parameters by various sensors and broadcast of data through internet is being presented. The framework of the monitoring system is based on a combination of embedded sensing units, information structure for data collection, and intellectual and context responsiveness. The projected system does not involve a devoted server computer with respect to analogous systems and offers a light weight communication protocol to monitor environment data using sensors. Outcomes are inspiring as the consistency of sensing information broadcast through the projected unified network construction is very much reliable. The prototype was experienced to create real-time graphical information rather than a test bed set-up.

scholarly journals Machine-learning-based children’s pathological gait classification with low-cost gait-recognition system

2021 ◽  
Author(s):  
Linghui Xu ◽  
Jiansong Chen ◽  
Fei Wang ◽  
Yuting Chen ◽  
Wei Yang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Plantar Pressure ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Gait Recognition ◽  
Recognition System ◽  
Experimental Results ◽  
Time Performance ◽  
Pathological Gait

Abstract Background: Pathological gaits of children may lead to terrible diseases, such as osteoarthritis or scoliosis. By monitoring the gait pattern of a child, proper therapeutic measures can be recommended to avoid the terrible consequence. However, low-cost systems for pathological gait recognition of children automatically have not been on market yet. Our goal was to design a low-cost gait-recognition system for children with only pressure information.Methods: In this study, we design a pathological gait-recognition system (PGRS) with an 8 × 8 pressure-sensor array. An intelligent gait-recognition method (IGRM) based on machine learning and pure plantar pressure information is also proposed in static and dynamic sections to realize high accuracy and good real-time performance. To verifying the recognition effect, a total of seventeen children were recruited in the experiments wearing PGRS to recognize three pathological gaits (toe in, toe out, and flat) and normal gait. Children are asked to walk naturally on level ground in the dynamic section or stand naturally and comfortably in the static section. The evaluation of the performance of recognition results included stratified 10-fold cross-validation with recall, precision, and a time cost as metrics.Results: The experimental results show that all of the IGRMs have been identified with a practically applicable degree of average accuracy either in the dynamic or static section. Experimental results indicate that the IGRM has 92.41% and 97.79% recognition accuracy respectively in the static and dynamic sections. And we find methods in the static section have less recognition accuracy due to the unnatural gesture of children when standing.Conclusions: In this study, a low-cost PGRS has been verified and realize feasibility, highly average precision, and good real-time performance of gait recognition. The experimental results reveal the potential for the computer supervision of non-pathological and pathological gaits in the plantar-pressure patterns of children and for providing feedback in the application of gait-abnormality rectification.

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