scholarly journals DALI LED Driver Control System for Lighting Operations Based on Raspberry Pi and Kernel Modules

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1021 ◽  
Author(s):  
Adam
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Performance Testing ◽  
Raspberry Pi ◽  
Led Driver ◽  
Real Time Processing ◽  
Lighting Control ◽  
Kernel Module ◽  
And Control ◽  
Led Drivers

Light emitting diodes (LEDs) as an efficient low-consumption lighting technology are being used increasingly in many applications. The move to LED lighting is also changing the way the lighting control systems are designed. Currently, most electronic ballasts and other digital lighting devices implement the Digital Addressable Lighting Interface (DALI) standard. This paper presents a low-cost, low-power effective DALI LED driver controller, based on open-source Raspberry Pi3 microcontroller prototyping platform. The control software is developed as a Linux kernel module under UBUNTU 18.04.2 LTS patched with PREEMPT_RT (Preemptive Real-time) for real-time processing. This dynamically loaded kernel module performs all the processing, communication and control operations of the Raspberry Pi3-based DALI controller with the DALI LED driver and LED luminaire. Software applications written in C and Python were developed for performance testing purposes. The experimental results showed that the proposed system could efficiently and effectively manage DALI LED drivers and perform lighting operations (e.g. dimming). The system can be used for a variety of purposes from personal lighting control needs and experimental research in control of electronic ballasts and other control gears, devices and sensors, to advanced requirements in professional buildings, including energy management, lighting maintenance and usage.

scholarly journals Designing of an Advanced Compression Bioreactor with an Implementation of a Low-Cost Controlling System Connected to a Mobile Application

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 915
Author(s):  
Gözde Dursun ◽  
Muhammad Umer ◽  
Bernd Markert ◽  
Marcus Stoffel
Keyword(s):  
Mobile Application ◽  
Low Cost ◽  
Experimental Information ◽  
Raspberry Pi ◽  
Tissue Constructs ◽  
Cost Controlling ◽  
Controlling System ◽  
And Control ◽  
Tissue Models

(1) Background: Bioreactors mimic the natural environment of cells and tissues by providing a controlled micro-environment. However, their design is often expensive and complex. Herein, we have introduced the development of a low-cost compression bioreactor which enables the application of different mechanical stimulation regimes to in vitro tissue models and provides the information of applied stress and strain in real-time. (2) Methods: The compression bioreactor is designed using a mini-computer called Raspberry Pi, which is programmed to apply compressive deformation at various strains and frequencies, as well as to measure the force applied to the tissue constructs. Besides this, we have developed a mobile application connected to the bioreactor software to monitor, command, and control experiments via mobile devices. (3) Results: Cell viability results indicate that the newly designed compression bioreactor supports cell cultivation in a sterile environment without any contamination. The developed bioreactor software plots the experimental data of dynamic mechanical loading in a long-term manner, as well as stores them for further data processing. Following in vitro uniaxial compression conditioning of 3D in vitro cartilage models, chondrocyte cell migration was altered positively compared to static cultures. (4) Conclusion: The developed compression bioreactor can support the in vitro tissue model cultivation and monitor the experimental information with a low-cost controlling system and via mobile application. The highly customizable mold inside the cultivation chamber is a significant approach to solve the limited customization capability of the traditional bioreactors. Most importantly, the compression bioreactor prevents operator- and system-dependent variability between experiments by enabling a dynamic culture in a large volume for multiple numbers of in vitro tissue constructs.

scholarly journals Digital Vein Mapping Using Augmented Reality

2020 ◽  
Vol 13 (6) ◽  
pp. 512-521
Author(s):  
Mohamed Taha ◽  
◽  
Mohamed Ibrahim ◽  
Hala Zayed ◽  
◽  
...  
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Infrared Radiation ◽  
Low Cost ◽  
Economic Cost ◽  
Frame Rate ◽  
Infrared Light ◽  
Real Time Processing ◽  
And Gender ◽  
Time Systems

Vein detection is an important issue for the medical field. There are some commercial devices for detecting veins using infrared radiation. However, most of these commercial solutions are cost-prohibitive. Recently, veins detection has attracted much attention from research teams. The main focus is on developing real-time systems with low-cost hardware. Systems developed to reduce costs suffer from low frame rates. This, in turn, makes these systems not suitable for real-world applications. On the other hand, systems that use powerful processors to produce high frame rates suffer from high costs and a lack of mobility. In this paper, a real-time vein mapping prototype using augmented reality is proposed. The proposed prototype provides a compromised solution to produce high frame rates with a low-cost system. It consists of a USB camera attached to an Android smartphone used for real-time detection. Infrared radiation is employed to differentiate the veins using 20 Infrared Light Emitting Diodes (LEDs). The captured frames are processed to enhance vein detection using light computational algorithms to improve real-time processing and increase frame rate. Finally, the enhanced view of veins appears on the smartphone screen. Portability and economic cost are taken into consideration while developing the proposed prototype. The proposed prototype is tested with people of different ages and gender, as well as using mobile devices of different specifications. The results show a high vein detection rate and a high frame rate compared to other existing systems.

scholarly journals A Portable Fuzzy Driver Drowsiness Estimation System

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4093
Author(s):  
Alimed Celecia ◽  
Karla Figueiredo ◽  
Marley Vellasco ◽  
René González
Keyword(s):  
Real Time ◽  
Traffic Accidents ◽  
Fuzzy Inference ◽  
Low Cost ◽  
Raspberry Pi ◽  
Inference System ◽  
Visual Occlusion ◽  
Computational Performance ◽  
Estimation System ◽  
Definition Of

The adequate automatic detection of driver fatigue is a very valuable approach for the prevention of traffic accidents. Devices that can determine drowsiness conditions accurately must inherently be portable, adaptable to different vehicles and drivers, and robust to conditions such as illumination changes or visual occlusion. With the advent of a new generation of computationally powerful embedded systems such as the Raspberry Pi, a new category of real-time and low-cost portable drowsiness detection systems could become standard tools. Usually, the proposed solutions using this platform are limited to the definition of thresholds for some defined drowsiness indicator or the application of computationally expensive classification models that limits their use in real-time. In this research, we propose the development of a new portable, low-cost, accurate, and robust drowsiness recognition device. The proposed device combines complementary drowsiness measures derived from a temporal window of eyes (PERCLOS, ECD) and mouth (AOT) states through a fuzzy inference system deployed in a Raspberry Pi with the capability of real-time response. The system provides three degrees of drowsiness (Low-Normal State, Medium-Drowsy State, and High-Severe Drowsiness State), and was assessed in terms of its computational performance and efficiency, resulting in a significant accuracy of 95.5% in state recognition that demonstrates the feasibility of the approach.

OBD-II and raspberry Pi technology to diagnose car’s machine current condition: study literature

2017 ◽  
Vol 34 (10) ◽  
pp. 15-21 ◽  
Author(s):  
Sonya Rapinta Manalu ◽  
Jurike Moniaga ◽  
Dionisius Andrian Hadipurnawan ◽  
Firda Sahidi
Keyword(s):  
Real Time ◽  
Mobile Technology ◽  
Design Methodology ◽  
Low Cost ◽  
Raspberry Pi ◽  
Data Link ◽  
Content Type ◽  
History Of ◽  
To Receive ◽  
Technology Comparison

Purpose Low-cost microcomputers such as the Raspberry Pi are common in library makerspaces. This paper aims to create an OBD-II technology to diagnose a vehicle’s condition. Design/methodology/approach An OBD-II scanner plugged into the OBD-II port or usually called the data link connector (DLC), sends diagnostics to the Raspberry Pi. Findings Compared with other microcontrollers such as Arduino, the Raspberry Pi was chosen because it sustains the application to receive real-time diagnostics, process the diagnostics and send commands to automobiles at the same time, rather than Arduino that must wait for another process finished to run another process. Originality/value This paper also represents the history of mobile technology and OBD-II technology, comparison between Arduino and Raspberry Pi and Node.

scholarly journals Artificial vision system for object classification in real time using Raspberry Pi and a Web camera

2021 ◽  
pp. 20-25
Author(s):  
Tomás Serrano-Ramírez ◽  
Ninfa del Carmen Lozano-Rincón ◽  
Arturo Mandujano-Nava ◽  
Yosafat Jetsemaní Sámano-Flores
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Vision System ◽  
Low Cost ◽  
Artificial Vision ◽  
Maintenance Cost ◽  
Raspberry Pi ◽  
Smart Cameras ◽  
Suggested Technique ◽  
Web Camera

Computer vision systems are an essential part in industrial automation tasks such as: identification, selection, measurement, defect detection and quality control in parts and components. There are smart cameras used to perform tasks, however, their high acquisition and maintenance cost is restrictive. In this work, a novel low-cost artificial vision system is proposed for classifying objects in real time, using the Raspberry Pi 3B + embedded system, a Web camera and the Open CV artificial vision library. The suggested technique comprises the training of a supervised classification system of the Haar Cascade type, with image banks of the object to be recognized, subsequently generating a predictive model which is put to the test with real-time detection, as well as the calculation for the prediction error. This seeks to build a powerful vision system, affordable and also developed using free software.

scholarly journals High-availability on-site deployment to heterogeneous architectures for Project 8 and ADMX

2020 ◽  
Vol 245 ◽  
pp. 07029
Author(s):  
Benjamin LaRoque
Keyword(s):  
Coupling Parameter ◽  
Low Cost ◽  
Rapid Development ◽  
High Availability ◽  
Raspberry Pi ◽  
Development Environment ◽  
Heterogeneous Architectures ◽  
Active Research ◽  
Support Software ◽  
And Control

Project 8 is applying a novel spectroscopy technique to make a precision measurement of the tritium beta-decay spectrum, resulting in either a measurement of or further constraint on the effective mass of the electron antineutrino. ADMX is operating an axion haloscope to scan the mass-coupling parameter space in search of dark matter axions. Both collaborations are executing medium-scale experiments, where stable operations last for three to nine months and the same system is used for development and testing between periods of operation. It is also increasingly common to use low-cost computing elements, such as the Raspberry Pi, to integrate computing and control with custom instrumentation and hardware. This leads to situations where it is necessary to support software deployment to heterogeneous architectures on rapid development cycles while maintaining high availability. Here we present the use of docker containers to standardize packaging and execution of control software for both experiments and the use of kubernetes for management and monitoring of container deployment in an active research and development environment. We also discuss the advantages over more traditional approaches employed by experiments at this scale, such as detached user execution or custom control shell scripts.

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