scholarly journals Vision Controlled Automated Robotic Vehicle using Raspberry Pi

2019 ◽  
Vol 8 (4) ◽  
pp. 5539-5542
Keyword(s):  
Autonomous Vehicles ◽  
Red Light ◽  
Green Light ◽  
Ultrasonic Sensor ◽  
Raspberry Pi ◽  
Small Scale ◽  
Central Processor ◽  
Traffic Lights ◽  
Camera Module ◽  
Self Driving Cars

The automobile industries are concentrating to develop the design for self-driving cars. Nowadays they are many possibilities to implement the automated vehicle, but the drawbacks for implementing are also very high. In this paper, the miniature model of self-driving robot is created and demonstrated using the Raspberry pi with supporting sensors and motor drivers. So, this was mainly because of the security concerns that have raised in the initial testing stages. So, this paper could best describe an application that deals with the safety measures of the autonomous vehicles that are going to be dealt with in the nearer future. This paper tells us about how an application can be implemented using Raspberry Pi, camera module and the ultrasonic Sensor. Considering the different features and the cost, on a small scale a two-wheel vehicular robotic prototype has been designed. In the Autonomous car Raspberry pi is the central processor. Different type of images are captured by the camera module, and if these images have captured the color of traffic lights, then if the captured image is of the Red light then the motors of the vehicle should stop such that breaks of the car in real world should work. If the captured image is of Green light then the motors of the car should run and the vehicle should start to move in the direction it want to move and also using the Ultrasonic sensor if any of the objects that are nearby to the vehicle, then the vehicle should change the direction from which it is moving and this is well described throughout the paper.

Perancangan Sistem Kontrol Lampu Lalulintas Cerdas Dengan Menggunakan Mikrokontroler dan Kamera

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 200
Author(s):  
Tjerie Pangemanan ◽  
Arnold Rondonuwu
Keyword(s):  
Real Time ◽  
Digital Image ◽  
Red Light ◽  
Green Light ◽  
Processing Method ◽  
Traffic Lights ◽  
Traffic System ◽  
Road Users ◽  
Adjustment System ◽  
System Time

Masalah lalu lintas  merupakan salah satu  masalah yang sangat sulit diatasi dengan hanya menggunakan system waktu (timer). Oleh sebab itu diperlukan suatu system pengaturan otomatis yang bersifat real-time sehingga waktu pengaturan lampu lalu lintas dapat disesuaikan dnegan keadaan di lapangan. Penelitian ini bertujuan mengembangkan suatu simulasi sistem yang mampu mengestimasi panjang antrian kendaraan menggunakan metoda pengolahan citra digital hanya dengan menggunakan satu kamera untuk dijadikan parameter masukan  dalam menghitung lama waktu nyala lampu merah dan lampu hijau. Oleh karena itu, sistem lalulintas sangatlah diperlukan, sebagai sarana dan prasarana untuk menjadikan lalulintas lancar, aman, bahkan sebagai media pembelajaran disiplin bagi masyarakat pengguna jalan raya. Penelitian ini penulis menggunakan sistem pengontrolan berbasis citra digital dimana camera sebagai sensor. Untuk aplikasi dari  semua metode dalam penelitian ini digunakan Microcontroller AurdinoTraffic problems is one of the problems that is very difficult to overcome by only using the system time (timer). Therefore we need an automatic real-time adjustment system so that the time settings for traffic lights can be adjusted according to the conditions on the ground. This study aims to develop a system simulation that is able to estimate the length of the vehicle queue using a digital image processing method using only one camera to be used as input parameters in calculating the length of time the red light and green light. Therefore, the traffic system is very necessary, as a means and infrastructure to make traffic smooth, safe, even as a medium for disciplined learning for road users. In this study the authors used a digital image-based control system where the camera as a sensor. For the application of all methods in this study, Aurdino Microcontroller is used

scholarly journals Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gerardo Hernandez-Oregon ◽  
Mario E. Rivero-Angeles ◽  
Juan C. Chimal-Eguía ◽  
Arturo Campos-Fentanes ◽  
Jorge G. Jimenez-Gallardo ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Low Cost ◽  
Red Light ◽  
Green Light ◽  
Mathematical Expression ◽  
Traffic Light ◽  
Safe Driving ◽  
Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

scholarly journals Optimization of Traffic Flow On KS Tubun Street using Greenberg Model

2019 ◽  
Vol 8 (2S7) ◽  
pp. 83-86
Keyword(s):  
Traffic Flow ◽  
Red Light ◽  
Green Light ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
The Road ◽  
Road Users ◽  
Time Parameters

KS Tubun Street is a street in Bogor, which has a fairly high vehicle volume and become one of a high-traffic jam area. This is caused by KS Tubun Street is the main road for road users from Jakarta and Bogor. Traffic jam problem that occurs due to the confluence interchange of traffic flow and traffic lights settings that are not proportional to the volume of vehicles across the road. Optimization of traffic flow at KS Tubun Street performed by the stages of forming a model of traffic flow, determining the density and velocity of the vehicle is based on the Greenberg model, and determining the length of the traffic lights to avoid a buildup of vehicles. The result is a traffic flow model with distance and time parameters. The density of vehicles that occurs on the streets of KS. Tubun street based on the Greenberg model between 180 to 240 unit car of passanger (ucp) with the average velocity of vehicles 15 to 19.5 km per hour. The density of vehicles on KS. Tubun street can be break down by increasing time. Traffic light cycle time can be reduced for 8 seconds with the red light glowing time is 80 seconds and the green light glowing time is 62 seconds.

scholarly journals Density Controlled Traffic Lights System using Aurdino Mega 2560

2020 ◽  
Vol 9 (5) ◽  
pp. 392-394
Keyword(s):  
Traffic Control ◽  
Urban Areas ◽  
Red Light ◽  
Green Light ◽  
Fixed Time ◽  
Traffic Density ◽  
Traffic Light ◽  
Traffic Lights ◽  
Choice Making ◽  
Control Authority

We have proposed the enhancement of Traffic Light Controller utilizing ultrasonic sensor and microcontroller. The Paper is planned for structuring a thickness based dynamic traffic signal framework where the planning of signal will change consequently on detecting the traffic density at any road junction. Traffic jams are an extreme issue in many urban areas over the world and thusly the time has come to move progressively manual mode or fixed clock mode to a robotized framework with choice making abilities. Present day traffic control framework is fixed time based which may render wasteful on the off chance that one path is operational than the others. To solve this issue, we have made a structure for a clever traffic control system. Some of the time higher traffic density at one side of the intersection requires longer green light time when compared with standard green light time. We, consequently propose here a component where the time of green light and red light is allotted based on the thickness of the traffic present around then. This is accomplished by utilizing ultrasonic sensors which are available on Top of the street.Sometime, in specific intersection of the street junctions extended periods of Red Traffic Light. In instance of any vehicle in crisis circumstance or on the other hand in emergency like VVIPs,a SMS is send to Traffic Control Authority, who has the control of microcontroller empowers microcontroller to change traffic light green for specific time on need premise.

scholarly journals Antimicrobial and Antioxidant Potential of Scenedesmus obliquus Microalgae in the Context of Integral Biorefinery Concept

Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 519
Author(s):  
Maya Margaritova Zaharieva ◽  
Dimitrina Zheleva-Dimitrova ◽  
Snezhana Rusinova-Videva ◽  
Yana Ilieva ◽  
Anna Brachkova ◽  
...  
Keyword(s):  
Scenedesmus Obliquus ◽  
Red Light ◽  
Green Light ◽  
Initial Step ◽  
In Vitro Cytotoxicity ◽  
Antioxidant Potential ◽  
Small Scale ◽  
Microalgal Biomass ◽  
Oregano Essential Oil

Small-scale photobioreactors (PBRs) in the inoculum stage were designed with internal (red or green) and external white LED light as an initial step of a larger-scale installation aimed at fulfilling the integral biorefinery concept for maximum utilization of microalgal biomass in a multifunctional laboratory. The specific growth rate of Scenedesmus obliquus (Turpin) Kützing biomass for given cultural conditions was analyzed by using MAPLE software. For the determination of total polyphenols, flavonoids, chlorophyll “a” and “b”, carotenoids and lipids, UHPLC-HRMS, ISO-20776/1, ISO-10993-5 and CUPRAC tests were carried out. Under red light growing, a higher content of polyphenols was found, while the green light favoured the flavonoid accumulation in the biomass. Chlorophylls, carotenoids and lipids were in the same order of magnitude in both samples. The dichloromethane extracts obtained from the biomass of each PBR synergistically potentiated at low concentrations (0.01–0.05 mg/mL) the antibacterial activity of penicillin, fluoroquinolones or oregano essential oil against the selected food-borne pathogens (Staphylococcus aureus, Escherichia coli and Salmonella typhimurium) without showing any in vitro cytotoxicity. Both extracts exhibited good cupric ion-reducing antioxidant capacity at concentrations above 0.042–0.08 mg/mL. The UHPLC-HRMS analysis revealed that both extracts contained long chain fatty acids and carotenoids thus explaining their antibacterial and antioxidant potential. The applied engineering approach showed a great potential to modify microalgae metabolism for the synthesis of target compounds by S. obliquus with capacity for the development of health-promoting nutraceuticals for poultry farming.

scholarly journals Modeling Energy LED Light Consumption Based on an Artificial Intelligent Method Applied to Closed Plant Production System

2021 ◽  
Vol 11 (6) ◽  
pp. 2735
Author(s):  
Ernesto Olvera-Gonzalez ◽  
Martín Montes Rivera ◽  
Nivia Escalante-Garcia ◽  
Eduardo Flores-Gallegos
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Nonlinear Models ◽  
Light Emitting Diode ◽  
Red Light ◽  
Green Light ◽  
Plant Production ◽  
Production Plant ◽  
Light Component ◽  
Gp Model

Artificial lighting is a key factor in Closed Production Plant Systems (CPPS). A significant light-emitting diode (LED) technology attribute is the emission of different wavelengths, called light recipes. Light recipes are typically configured in continuous mode, but can also be configured in pulsed mode to save energy. We propose two nonlinear models, i.e., genetic programing (GP) and feedforward artificial neural networks (FNNs) to predict energy consumption in CPPS. The generated models use the following input variables: intensity, red light component, blue light component, green light component, and white light component; and the following operation modes: continuous and pulsed light including pulsed frequency, and duty cycle as well energy consumption as output. A Spearman's correlation was applied to generate a model with only representative inputs. Two datasets were applied. The first (Test 1), with 5700 samples with similar input ranges, was used to train and evaluate, while the second (Test 2), included 160 total datapoints in different input ranges. The metrics that allowed a quantitative evaluation of the model's performance were MAPE, MSE, MAE, and SEE. Our implemented models achieved an accuracy of 96.1% for the GP model and 98.99% for the FNNs model. The models used in this proposal can be applied or programmed as part of the monitoring system for CPPS which prioritize energy efficiency. The nonlinear models provide a further analysis for energy savings due to the light recipe and operation light mode, i.e., pulsed and continuous on artificial LED lighting systems.

scholarly journals An Intelligent Task Scheduling Mechanism for Autonomous Vehicles via Deep Learning

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1788
Author(s):  
Gomatheeshwari Balasekaran ◽  
Selvakumar Jayakumar ◽  
Rocío Pérez de Prado
Keyword(s):  
Execution Time ◽  
Autonomous Vehicles ◽  
Rapid Development ◽  
Single Layer ◽  
Battery Life ◽  
Learning Approaches ◽  
Task Management ◽  
Inference System ◽  
Safe Driving ◽  
Self Driving Cars

With the rapid development of the Internet of Things (IoT) and artificial intelligence, autonomous vehicles have received much attention in recent years. Safe driving is one of the essential concerns of self-driving cars. The main problem in providing better safe driving requires an efficient inference system for real-time task management and autonomous control. Due to limited battery life and computing power, reducing execution time and resource consumption can be a daunting process. This paper addressed these challenges and developed an intelligent task management system for IoT-based autonomous vehicles. For each task processing, a supervised resource predictor is invoked for optimal hardware cluster selection. Tasks are executed based on the earliest hyper period first (EHF) scheduler to achieve optimal task error rate and schedule length performance. The single-layer feedforward neural network (SLFN) and lightweight learning approaches are designed to distribute each task to the appropriate processor based on their emergency and CPU utilization. We developed this intelligent task management module in python and experimentally tested it on multicore SoCs (Odroid Xu4 and NVIDIA Jetson embedded platforms).Connected Autonomous Vehicles (CAV) and Internet of Medical Things (IoMT) benchmarks are used for training and testing purposes. The proposed modules are validated by observing the task miss rate, resource utilization, and energy consumption metrics compared with state-of-art heuristics. SLFN-EHF task scheduler achieved better results in an average of 98% accuracy, and in an average of 20–27% reduced in execution time and 32–45% in task miss rate metric than conventional methods.

scholarly journals Artificial complementary chromatic acclimation gene expression system in Escherichia coli

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Dwi Ariyanti ◽  
Kazunori Ikebukuro ◽  
Koji Sode
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Light Exposure ◽  
Expression System ◽  
Red Light ◽  
Green Light ◽  
Light Illumination ◽  
Multiple Gene ◽  
Gene Expression System ◽  
Chromatic Acclimation

Abstract Background The development of multiple gene expression systems, especially those based on the physical signals, such as multiple color light irradiations, is challenging. Complementary chromatic acclimation (CCA), a photoreversible process that facilitates the control of cellular expression using light of different wavelengths in cyanobacteria, is one example. In this study, an artificial CCA systems, inspired by type III CCA light-regulated gene expression, was designed by employing a single photosensor system, the CcaS/CcaR green light gene expression system derived from Synechocystis sp. PCC6803, combined with G-box (the regulator recognized by activated CcaR), the cognate cpcG2 promoter, and the constitutively transcribed promoter, the PtrcΔLacO promoter. Results One G-box was inserted upstream of the cpcG2 promoter and a reporter gene, the rfp gene (green light-induced gene expression), and the other G-box was inserted between the PtrcΔLacO promoter and a reporter gene, the bfp gene (red light-induced gene expression). The Escherichia coli transformants with plasmid-encoded genes were evaluated at the transcriptional and translational levels under red or green light illumination. Under green light illumination, the transcription and translation of the rfp gene were observed, whereas the expression of the bfp gene was repressed. Under red light illumination, the transcription and translation of the bfp gene were observed, whereas the expression of the rfp gene was repressed. During the red and green light exposure cycles at every 6 h, BFP expression increased under red light exposure while RFP expression was repressed, and RFP expression increased under green light exposure while BFP expression was repressed. Conclusion An artificial CCA system was developed to realize a multiple gene expression system, which was regulated by two colors, red and green lights, using a single photosensor system, the CcaS/CcaR system derived from Synechocystis sp. PCC6803, in E. coli. The artificial CCA system functioned repeatedly during red and green light exposure cycles. These results demonstrate the potential application of this CCA gene expression system for the production of multiple metabolites in a variety of microorganisms, such as cyanobacteria.

scholarly journals AB0612 THE FRACTURE PREVENTION UNIT OF THE VIRGEN MACARENA HOSPITAL REDUCES THE GAP IN THE MANAGEMENT OF OP, PARTICULARLY IN MALES AND MEETS IOF/ESCEO QUALITY STANDARDS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1341.2-1341
Author(s):  
B. Hernández-Cruz ◽  
F. J. Olmo Montes ◽  
M. J. Miranda García ◽  
M. D. Jimenez Moreno ◽  
M. A. Vázquez Gómez ◽  
...  
Keyword(s):  
Fragility Fracture ◽  
Red Light ◽  
Green Light ◽  
Quality Standards ◽  
Type A ◽  
Traffic Light ◽  
Patient Identification ◽  
Reference Time ◽  
Fracture Liaison

Background:The Virgen Macarena University Hospital belongs to the Public Health System of Andalusia and serves 481,296 inhabitants in Seville, Spain. In 2018 the Fracture Liaison Service switched to a multidisciplinary unit.Objectives:To describe FLS, to know the characteristics of patients with emphasis on gender differences and to know the completion of International Osteoporosis Foundation quality standards.Methods:Prospective, observational, analytical, research of usual clinical practice. All the consecutive patients attended from May 2018 to October 2019, ≥50 years, with a fragility fracture (occurred in the previous 24 months) were included. The study was approved by the Ethics Committee, Code 1084-N-16.Results:Our FLS is a type A multidisciplinary Unit, with a high level of intervention in the evaluation, estimation of fracture risk and fall risk, treatment prescription and follow-up of the patients. We included 408 patients, 80% females, one third with ≥80 years. Fragility fractures recorded in 328 women were hip (132, 40%), clinical vertebral (81, 25%) and no hip no vertebral (115, 35%). Those recorded in 82 males were hip (53, 66%), clinical vertebral (20, 24%) and no hip no vertebral (9, 10%), p=0.0001. Males had a higher rate of secondary causes of OP, drinker, and smoking. The most relevant gender difference was the low percentage of patients receiving pre-FF OP treatment. Forty-nine (16%) women versus 9 (7%) males had received it at some point in their life, p=0.04. Two hundred and seventy-one (86%) women vs 48 males (63%) had received it at after their FF in their reference unit, and all them were treated after the FLS evaluation. The probability of a male not receiving prior treatment was 2.5 (95% CI 1.01- 6.51); p=0,04. This probability was 0.64 (0.38-1.09) after the FF. After twelve months of follow-up in FLs, 96% continued treatment, with no differences between men and women. The completion of IOF quality standards was bad (red light) for patient identification items and FLS reference time. It was poor (amber traffic light) for initial OP screening standard and was good (green light) for the remaining 10 indicators. The completion of IOF quality standards was bad (red light) for patient identification items and FLS reference time. It was poor (amber traffic light) for initial OP screening standard and was good (green light) for the remaining 10 indicators (Figure 1).Figure 1.Figure 1.Conclusion:The FLS is a multidisciplinary type A. Its operation has narrowed the gap in diagnosis, treatment, and follow-up of FF patients, especially males. It is essential to improve patient recruitment, reduce referral times and increase the overall assessment of the patients.References:[1]Ganda K. et al. Models of care for the secondary prevention of osteoporotic fractures: a systematic review and meta-analysis, Osteoporos Int 2013;24:293-406.[2]Javaid MK et al. A patient-level key performance indicator set to measure the effectiveness of fracture liaison services and guide quality improvement: a position paper of the IOF Capture the Fracture Working Group, National Osteoporosis Foundation and Fragility Fracture Network. Osteoporos Int. 2020 Jul;31(7):1193-1204.Acknowledgements:Spanish Society of Research in Mineral and Bone Metabolism for its support through the competitive project FLS Excellence 2018 to obtain a training grant from the case management nurse.Disclosure of Interests:Blanca Hernández-Cruz Speakers bureau: Sociedad Española de Reumatología, Abbvie, Roche, Bristol, MSD, Lilly, Pfizer, Amgen, Sanofi, Consultant of: Abbvie, Lilly, Sanofi, STADA, UCB, Amgen, Galapagos., Grant/research support from: Fundación para la Investigación Sevilla, Junta de AndalucíaFundación Andaluza de Reumatología, Sociuedad Española de Reumatología., Francisco Jesús Olmo Montes: None declared., Maria José Miranda García: None declared., María Dolores Jimenez Moreno: None declared., María Angeles Vázquez Gómez: None declared., Mercedes Giner García: None declared., Miguel Angel Colmenero Camacho: None declared., José Javier Pérez Venegas: None declared., María José Montoya García: None declared.

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