scholarly journals Development of a Low-Cost Data Acquisition System for Very Short-Term Photovoltaic Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6075
Author(s):  
Guilherme Fonseca Bassous ◽  
Rodrigo Flora Calili ◽  
Carlos Hall Barbosa
Keyword(s):  
Low Cost ◽  
Renewable Energy Sources ◽  
Relevant Information ◽  
Acquisition System ◽  
Time Operation ◽  
Detection Point ◽  
Real Time Operation ◽  
Forecast Models ◽  
Input Variables ◽  
Power Forecasting

The rising adoption of renewable energy sources means we must turn our eyes to limitations in traditional energy systems. Intermittency, if left unaddressed, may lead to several power-quality and energy-efficiency issues. The objective of this work is to develop a working tool to support photovoltaic energy forecast models for real-time operation applications. The current paradigm of intra-hour solar-power forecasting is to use image-based approaches to predict the state of cloud composition for short time horizons. Since the objective of intra-minute forecasting is to address high-frequency intermittency, data must provide information on and surrounding these events. For that purpose, acquisition by exception was chosen as the guiding principle. The system performs power measurements at 1 Hz frequency, and whenever it detects variations over a certain threshold, it saves the data 10 s before and 4 s after the detection point. A multilayer perceptron neural network was used to determine its relevance to the forecasting problem. With a thorough selection of attributes and network structures, the results show very low error with R2 greater than 0.93 for both input variables tested with a time horizon of 60 s. In conclusion, the data provided by the acquisition system yielded relevant information for forecasts up to 60 s ahead.

scholarly journals Development of Low-Cost ECG System for Comprehensive Monitoring Heart Function

2021 ◽  
Author(s):  
prihatin oktivasari ◽  
Ishartati Ishartati ◽  
Riandini Riandini ◽  
Amy Hamidah Salman ◽  
Freddy Haryanto ◽  
...  
Keyword(s):  
Heart Function ◽  
Low Cost ◽  
Integrated System ◽  
Ecg Signal ◽  
Analog To Digital ◽  
Rr Interval ◽  
Time Operation ◽  
The Status ◽  
Real Time Operation ◽  
Research And Education

Abstract A simple system, a low-cost, fully automated, and design for monitoring RR interval Electrocardiography (ECG) signal described in this paper. The platform, named Simple Low-Cost Electrocardiography System (SLES), is capable of monitoring RR interval and R peaks in 3 lead standards. The system is in .exe format, so it can be easily installed on a computer. The system's goal is to design a fully integrated system for measuring a characteristic of Heart Rate Variability (HRV) parameters for various applications in heart signal research and education. The ECG signal is analog filtered and amplified and processed from analog to digital. Eventually, the ECG signal will be shown on the monitor after digital filtering. The data obtained from the ECG will accurately reflect the status of human heart health. The system has the benefits of small volume, low power consumption, low cost, and real-time operation. All design and development reports, files, and system software will be given non-commercial use online on https://github.com/oktivasari.

Enhancing the Path Planning Generation of a Five DOF Manipulator Using Low-Cost Camera-Laser Triangulation Technique

2018 ◽  
Author(s):  
Maged M. Abou Elyazed ◽  
Ahmed Y. AbdelHamid ◽  
Mootaz E. Abo Elnor ◽  
Mohamed H. Mabrouk
Keyword(s):  
Path Planning ◽  
Low Cost ◽  
Laser Triangulation ◽  
Circular Path ◽  
Positioning System ◽  
Robotic Arms ◽  
Time Operation ◽  
Real Time Operation ◽  
Positioning Technique ◽  
To Receive

Robot path planning is considered one of the most significant tasks for industrial robotic arms, especially for those manipulators need to follow a specific path such as welding manipulators. In this work, a low cost camera-laser triangulation technique (CLTT) is implemented to facilitate the process of contact-less path acquiring. A graphical user interface (GUI) under MATLAB® is developed to receive the dominant path points locations from the proposed positioning system and sending the generated path to the robot actuators. the introduced positioning technique (CLTT) is applied practically to develop linear and circular path for a “5-DOF Mitsubishi MELFA RV-2AJ” manipulator. The results show the effectiveness of (CLTT) to achieve fast and accurate positioning system with contact-less target for real time operation.

scholarly journals A Simplified Sounding System for Finding NVIS Channel Availability to Support Government Radio Networks in Indonesia

2019 ◽  
Vol 7 (1) ◽  
pp. 326-342 ◽  
Author(s):  
Titon Dutono ◽  
Zulmi Zakariyah ◽  
Tribudi Santoso ◽  
Denny Setiawan
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Disaster Mitigation ◽  
Computer Hardware ◽  
Radio Link ◽  
Radio Communication ◽  
Transmitter Power ◽  
Time Operation ◽  
Regulatory Status ◽  
Real Time Operation

Mostly  natural disasters in Java Island such as landslides are within the vicinity of not more than 200 Km from the district capital. Cellular communications require complex systems and rather vulnerable  to cope with disasters. NVIS mode is considered as a simple radio link during disaster mitigation initiation process. It needs a valid estimation to figure out the condition of the ionosphere. There are two purposes of this study, the first of which is an attempt to find out a fact the existences of authorized HF users who still work in the band of 3 MHz – 10 MHz.  The second is to integrate low cost HF radio communication, commonly available small single board computer hardware, and opensource software, to build a sounding system to evaluate the quality of NVIS channels. Prediction system such VOACAP give hourly prediction data, however it has an inherent limitation because of   nature the underlying databases is monthly average based, therefore, the estimation could not be made in a daily bases. However, a real-time channel evaluation (RTCE)  able to purify maximum observed frequency (MOF) estimation, and consequently, its able to select the best available frequency for short term  and real time operation. In this study, we used WSPR to perform a simple RTCE technique. Furthermore, we also reviewed the current regulatory status regarding  the availability of sub-10 MHz band for NVIS radio operation. The results show that discrepancies between simulation and measurement are occurred mainly because of sporadic data in the band of 60m and 80m. However, all of the measurement results and simulations almost have the same agreement regarding the quiet period between local midnight and local sunrise. The results of measurements show that 60m band is the most reliable NVIS channel between local sunrise and local midnight. Furthermore, 100 watts is a proper transmitter power to reach the required SNR for reliable voice communication. 

scholarly journals A Digital Protein Microarray for COVID-19 Cytokine Storm Monitoring

2020 ◽  
Author(s):  
Yujing Song ◽  
Yuxuan Ye ◽  
Shiuan-Haur Su ◽  
Andrew Stephens ◽  
Tao Cai ◽  
...  
Keyword(s):  
Critically Ill ◽  
Low Cost ◽  
Protein Microarray ◽  
High Sensitivity ◽  
Microarray Platform ◽  
Optical Scanner ◽  
Clinical Biomarkers ◽  
Time Operation ◽  
Cytokine Analysis ◽  
Real Time Operation

AbstractDespite widespread concern for cytokine storms leading to severe morbidity in COVID-19, rapid cytokine assays are not routinely available for monitoring critically ill patients. We report the clinical application of a machine learning-based digital protein microarray platform for rapid multiplex quantification of cytokines from critically ill COVID-19 patients admitted to the intensive care unit (ICU) at the University of Michigan Hospital. The platform comprises two low-cost modules: (i) a semi-automated fluidic dispensing/mixing module that can be operated inside a biosafety cabinet to minimize the exposure of technician to the virus infection and (ii) a 12-12-15 inch compact fluorescence optical scanner for the potential near-bedside readout. The platform enabled daily cytokine analysis in clinical practice with high sensitivity (<0.4pg/mL), inter-assay repeatability (∼10% CV), and near-real-time operation with a 10min assay incubation. A cytokine profiling test with the platform allowed us to observe clear interleukin −6 (IL-6) elevations after receiving tocilizumab (IL-6 inhibitor) while significant cytokine profile variability exists across all critically ill COVID-19 patients and to discover a weak correlation between IL-6 to clinical biomarkers, such as Ferritin and CRP. Our data revealed large subject-to-subject variability in a patient’s response to anti-inflammatory treatment for COVID-19, reaffirming the need for a personalized strategy guided by rapid cytokine assays.

scholarly journals Human Body Parts Proximity Measurement Using Distributed Tactile Robotic Skin

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2138
Author(s):  
Jan Klimaszewski ◽  
Michał Władziński
Keyword(s):  
Real Time ◽  
Human Body ◽  
Low Cost ◽  
Body Part ◽  
Human Robot Interaction ◽  
Body Parts ◽  
Cooperative Robots ◽  
Time Operation ◽  
The Matrix ◽  
Real Time Operation

Safety in human–machine cooperation is the current challenge in robotics. Safe human–robot interaction requires the development of sensors that detect human presence in the robot’s workspace. Detection of this presence should occur before the physical collision of the robot with the human. Human to robot proximity detection should be very fast, allowing machine elements deceleration to velocities safe for human–machine collision. The paper presents a new, low-cost design of distributed robotic skin, which allows real-time measurements of the human body parts proximity. The main advantages of the proposed solution are low cost of its implementation based on comb electrodes matrix and real-time operation due to fast and simple electronic design. The main contribution is the new idea of measuring the distance to human body parts by measuring the operating frequency of a rectangular signal generator, which depends on the capacity of the open capacitor. This capacitor is formed between the comb electrodes matrix and a reference plate located next to the matrix. The capacitance of the open capacitor changes if a human body part is in vicinity. The application of the developed device can be very wide. For example, in the field of cooperative robots, it can lead to the improvement of human–machine interfaces and increased safety of human–machine cooperation. The proposed construction can help to meet the increasing requirements for cooperative robots.

scholarly journals Tactile Robotic Skin with Pressure Direction Detection

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4697 ◽  
Author(s):  
Jan Klimaszewski ◽  
Daniel Janczak ◽  
Paweł Piorun
Keyword(s):  
Real Time ◽  
External Force ◽  
Low Cost ◽  
Pressure Sensors ◽  
Correlation Method ◽  
Phase Correlation ◽  
Human Machine Interfaces ◽  
Time Operation ◽  
Real Time Operation ◽  
Direction Detection

Tactile sensing is the current challenge in robotics and object manipulation by machines. The robot’s agile interaction with the environment requires pressure sensors to detect not only location and value, but also touch direction. The paper presents a new, two-layer construction of artificial robotic skin, which allows measuring the location, value, and direction of pressure from external force. The main advantages of the proposed solution are its low cost of implementation based on two FSR (Force Sensitive Resistor) matrices and real-time operation thanks to direction detection using fast matching algorithms. The main contribution is the idea of detecting the pressure direction by determining the shift between the pressure maps of the skin’s upper and lower layers. The pressure map of each layer is treated as an image and registered using a phase correlation (POC–Phase Only Correlation) method. The use of the developed device can be very wide. For example, in the field of cooperative robots, it can lead to the improvement of human machine interfaces and increased security of human–machine cooperation. The proposed construction can help meet the increasing requirements for robots in cooperation with humans, but also enable agile manipulation of objects from their surroundings.

scholarly journals Stochastic Computing Emulation of Memristor Cellular Nonlinear Networks

2021 ◽  
Author(s):  
Oscar Camps ◽  
Mohamed-Moner al Chawa ◽  
Stavros G. Stavrinides ◽  
Rodrigo Picos
Keyword(s):  
Real Time ◽  
Color Image ◽  
Low Cost ◽  
Approximate Computing ◽  
Nonlinear Networks ◽  
Processing Elements ◽  
Stochastic Computing ◽  
Time Operation ◽  
Real Time Operation ◽  
Image Edge

Cellular Nonlinear Networks (CNN) are a concept introduced in 1988 by Leon Chua and Lin Yang as a bio-inspired architecture, capable of massively parallel computation. Later on, CNN have been enhanced by incorporating designs that incorporate memristors to profit from their processing and memory capabilities. In addition, Stochastic Computing (SC) can be used to optimize the quantity of required processing elements; thus it provides a lightweight approximate computing framework, quite accurate and effective, though. In this work, we propose utilization of SC in designing and implementing a memristor-based CNN. As a proof of the proposed concept, an example of application is presented. This application combines Matlab and a FPGA in order to create the CNN. The implemented CNN has then been used to perform three different real-time applications on a 512x512 gray-scale and a 768x512 color image: storage of the image, edge detection, and image sharpening. It has to be pointed out that the same CNN has been used for the three different tasks, with the sole change of some programmable parameters. Results show an excellent capability with significant accompanying advantages, like the low number of needed elements further allowing for a low cost FPGA-based system implementation, something confirming the system’s ability for real time operation.

scholarly journals Stochastic Computing Emulation of Memristor Cellular Nonlinear Networks

Micromachines ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Oscar Camps ◽  
Mohamad Moner Al Chawa ◽  
Stavros G. Stavrinides ◽  
Rodrigo Picos
Keyword(s):  
Real Time ◽  
Color Image ◽  
Low Cost ◽  
Approximate Computing ◽  
Nonlinear Networks ◽  
Processing Elements ◽  
Stochastic Computing ◽  
Time Operation ◽  
Real Time Operation ◽  
Image Edge

Cellular Nonlinear Networks (CNN) are a concept introduced in 1988 by Leon Chua and Lin Yang as a bio-inspired architecture capable of massively parallel computation. Since then, CNN have been enhanced by incorporating designs that incorporate memristors to profit from their processing and memory capabilities. In addition, Stochastic Computing (SC) can be used to optimize the quantity of required processing elements; thus it provides a lightweight approximate computing framework, quite accurate and effective, however. In this work, we propose utilization of SC in designing and implementing a memristor-based CNN. As a proof of the proposed concept, an example of application is presented. This application combines Matlab and a FPGA in order to create the CNN. The implemented CNN was then used to perform three different real-time applications on a 512 × 512 gray-scale and a 768 × 512 color image: storage of the image, edge detection, and image sharpening. It has to be pointed out that the same CNN was used for the three different tasks, with the sole change of some programmable parameters. Results show an excellent capability with significant accompanying advantages, such as the low number of needed elements further allowing for a low cost FPGA-based system implementation, something confirming the system’s capacity for real time operation.

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