International Research Conference of UWU-2021

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Browsing International Research Conference of UWU-2021 by Subject "Automated"

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    Analysis of Traffic Sign Detection and Recognition Techniques
    (Uva Wellassa University of Sri Lanka, 2021) Shanmugam, S.; Tharmaratnam, B.; Sandradeva, T.; Mehendran, Y.
    Automated Traffic Sign Detection and Recognition (ATSDR) is a trending research field in this current decade. It is a very important part of the intelligent transportation system as traffic signs assist the drivers to drive more carefully. This paper provides a review of three major steps in the ATSDR system; video segmentation, detection, and recognition. There are many techniques used for the detection and recognition process. However, those techniques are affected by different internal and external conditions like camera quality(fps), lighting conditions, time periods, etc. The main objectives are; to identify the different traffic sign detection and recognition techniques, develop the ATSDR system by using those selected technologies and analyze the performance of those techniques in different lighting conditions and time periods in Sri Lanka. Real time video sequences of traffic signs were collected and partitioned into single frames using video segmentation. The traffic signs were detected using shape-based and color-based features along with learning-based methods (Convolutional Neural Networks (CNN)). Subsequently, the signs were recognized using selected techniques such as Random forest method, CNN, and Support Vector Machine (SVM). Selected techniques were applied to the 10 varieties of traffic signs in Sri Lanka in different conditions, each having 1000 samples. Experimental results show that the approach obtained the desired results effectively. CNN method obtained 74.16% overall accuracy, SVM method obtained 63.5% overall accuracy and Random forest method obtained 58.6% overall accuracy. In the future, accuracy can be improved by testing the technologies in different internal factors like different camera quality (fps) and different computing power, as well as high-resolution images and a large number of training images should be used for the analysis. The experimental results showed that CNN is the most suitable technology to detect and recognize traffic signs based on the Sri Lankan traffic signs database Keywords: Traffic sign detection and recognition; Convolutional Neural Network; Support Vector Machine; Shape based methods; Color based methods; Random forest
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    Automated Farming Robot
    (Uva Wellassa University of Sri Lanka, 2021) Fazil, N.M.; Hiroshaan, V.
    Robotics is a fascinating field of engineering that provides many opportunities for research. In addition, the evolution of technology in recent years has led to intelligent mobile robots. As farms grow in size, together with the size of the equipment used on them, there is a need for ways to automate processes, previously performed by the farmer himself, such as handling the equipments himself to perform the task. The control of these robots, however, is a difficult task that involves knowledge in different areas such as robotics, automation, programming, electronics, etc. The objective of this research is to technically develop the new agricultural technologies to savings in terms of both cost and time, to optimize production efficiency, declining availability of manpower, minimize production-associated risks. Hence automation is the ideal solution to overcome all the shortcomings by creating machines that perform the operations and automating it to increase yield on a large scale. In this the robots are developed to concentrate in an efficient manner and also it is expected to perform the operations autonomously such as Drilling (for plantations of seeds), seed dispensing and watering. For manual control the robot uses the Bluetooth pairing app as control device and helps in the navigation of the robot outside the field Keywords: Farming Robot; Bluetooth module; Arduino;Agriculture; Water pump
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    Automated Powder Dispensing System for Manufacturing Industry
    (Uva Wellassa University of Sri Lanka, 2021) Pathiraja, P.M.D.K.; Isuranga, M.P.U.
    In many manufacturing industries, powders should be weighed and dispensed as a part of the routine production process. In these scenarios, workers must prepare power batches based on the material requirement manually. This manual process reduces the efficiency of overall production. Existing powder dispensing systems have issues including material and time wastage, human errors in the measurements. Since some powders are toxic to humans, works should avoid direct contact with the material. This study proposes a system to address these issues which are equipped with a screw conveyor and electronic weighing measurement. Also, the proposed system has features including automatic quantitative, Speed control. Further, Screw conveyors have an agitator to give vibration motion to the screw conveyor to ensure the Powder quickly comes to the screw conveyor. A valve is installed at the point where the powder exists, and the valve opens. Then the Powder comes out to the screw conveyor the Powder starts to dispense into the container. The load cell system collects data and measures the amount of powder that falls through the conveyer. PID unit is used to control the speed of the conveyor. The powder measuring machine is suitable for food additives, flavors and fragrances, flour, milk powder, protein powder, solid drink, sugar, monosodium glutamate, pesticides, veterinary drugs, detergents, enzymes, chemicals, and other powder (powder, super fine powder). The dispensing system is having 85% efficient 90% accurate than the conventional methods used in local manufacturing facilities. Keywords: Powder; Screw conveyor; Dispenser; Weight measurement; Loadcell
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    Automated Traffic Violation Detection
    (Uva Wellassa University of Sri Lanka, 2021) Ruwan, A.D.; Vithanage, D.S.
    One of the most serious health risks has been and will continue to be road accidents. The number of deaths and injuries caused by traffic accidents has been proven statistically. Road accident is a most unwanted thing to happen, especially on the pedestrian crossings to a road user, though they happen quite often. Some reasons for the accidents and crashes are due to human errors such as drunk driving, high speed, red light jumping and overtaking on the pedestrian crossing, etc. Among these reasons, especially an overtaking on the pedestrian crossing is one of the most common traffic rules violations in Sri Lanka, and the accidents associate with this violation cause a huge loss to life and property. Although automated techniques for detecting some traffic offenses exist, such as detection of the speed limit and drunk drivers, currently there is no automatic mechanism for the detection of the vehicles which are overtaking on pedestrian crossings. Manual identification of overtaking vehicles on the pedestrian crossing is more critical than anything else because detection of moving vehicles, then tracking and classifying them in real-time in a complicated environment, is extremely tough. Therefore, an accurate and efficient automatic method for detecting traffic violations is a very useful tool for road safety. This paper describes an automatic detection of traffic violation offender on pedestrian crossings. This paper proposed an improved dynamic background-updating approach and a feature-based tracking method to detect overtaking vehicles on the pedestrian crossing. This can fill the gap of manual detection with automatic detection and no labour costs. Thus, it is beneficial in various ways such as the confirmation of road safety. The application is proposed as a mobile application. A complete traffic violation detection system is realized in C++ with Open CV libraries. The accuracy of the system was found as above 73% after the train and validate the model. In conclusion, the developed method can help to detect vehicles that have violated the traffic rules on the pedestrian crossing accurately. Keywords: Traffic Violation; Road Safety; Mobile Application; Manual Detection;
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    Development a Self-Driving Golf Cart Using Kinect Sensor and Robot Operating System (ROS)
    (Uva Wellassa University of Sri Lanka, 2021) Thilakarathna, M.M.R.U.; Bandara, T.U.K.S.; Ekanayake, R.M.T.C.B.; Mark, R.A.D.R.K.; Gunasekara, L.K.I.K.
    An automated guided vehicle (AGV), in general, follows markings or wires on the floor or uses vision or laser sensors for its navigation. AGVs have been applied for flexible manufacturing systems, storage systems, delivery systems and in many similar situations in the industry mainly to move materials around a manufacturing facility or a warehouse. They are programmable mobile vehicles. AGVs are advantageous over conventional material transportation methods because its repeatability and economic savings because of the absence of labor. The aim of this paper is to develop an automated golf cart for human transportation. To date, in Sri Lanka, there is no self- driving system for human transportation. Hence, by introducing an electrical self-driving solution for the Sri Lankan transportation system, environmental impacts and exhaust emissions can be reduced which are generated by fossil fuel consumption. The price of petrol is increasing due to shortage in supplying crude oil. If there is an electric self-driving system, the shortage of fuel can be overcome. This AGV system can be used in large factories, hotels, gardens and parks for human transportation. This self-driving technology may create new industries and job opportunities for thousands of employees in Sri Lanka. Paper presents an autonomous navigation AGV system based on a Robot Operating System (ROS) for indoor and outdoor navigation tasks. This system uses a Kinect sensor for map building of its environment. First, the system was developed and simulated using the ROS platform. Then, this self-navigation system was applied to a real golf cart by updating its control and drive system to match with the new self-navigation system. In this update, the Ackerman steering system and the braking system of the golf cart was automated to work in parallel with the new controller. This innovative system can carry up to four persons at a time. Experimental trials showed the ability of the AGV to move loads and people to their target locations. Keywords: AGV; ROS; Kinect Sensor; Ackerman Steering System; Automated Navigation
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    Smart Sun Tracking System for Solar Energy Generation
    (Uva Wellassa University of Sri Lanka, 2021) Madhushani, Y.P.L.; Chandrasiri, K.H.M.C.; Jayawickrama, J.K.A.S.M.; Lakmal, S.D.R.; Herath, H.M.C.M.
    The use of renewable energy is becoming more prevalent with the global energy crisis. Solar energy is nature's most abundant renewable energy available around the world. The main challenge with solar energy harvesting is the reduction of solar energy absorbed by the use of photovoltaic (PV) systems. Excellent performance of PV systems can be achieved when the panel is oriented perpendicular to the radiation direction of the sun. Solar tracker systems are capable of optimum positioning of the PV panels to capture maximum solar radiation. Single axis solar trackers are widely used around the globe at the present day. The single axis tracking systems produce lower energy output during sunny times and it can track the daily change of Sun’s position but not seasonally. This study proposes an automated dual axis solar tracking system considering the limitations of fixed panels and single axis trackers. This project involves the designing and developing of an automated dual axis solar tracking system for domestic energy purposes. Moreover, demonstrates a prototype of the proposed dual-axis solar tracking system. The proposed dual-axis solar tracker increased energy generation by tracking Sun rays from switching solar panels. Sun rays are detected in different directions by the LDR system with a smart solar sensor mechanism. Advanced LDR arrangement and Algorithm development enabled way to smart sun tracking. The development of an Algorithm for this sensing mechanism improves the effectiveness and accuracy of the system. It is more accurate than a fixed solar panel and single axis system. Moreover, this design can be applied to the large-scale solar energy system in practice. This project is also expected to investigate the performances of the dual axis tracking system compared to the system with a fixed mounting method. Keywords: Solar energy; Photovoltaic; Sun tracking system; Automation; Micro-controller