Real-time traffic sign detection and recognition using Raspberry Pi

Nowadays, the number of road accident in Malaysia is increasing expeditiously. One of the ways to reduce the number of road accident is through the development of the advanced driving assistance system (ADAS) by professional engineers. Several ADAS system has been proposed by taking into consideration the delay tolerance and the accuracy of the system itself. In this work, a traffic sign recognition system has been developed to increase the safety of the road users by installing the system inside the car for driver’s awareness. TensorFlow algorithm has been considered in this work for object recognition through machine learning due to its high accuracy. The algorithm is embedded in the Raspberry Pi 3 for processing and analysis to detect the traffic sign from the real-time video recording from Raspberry Pi camera NoIR. This work aims to study the accuracy, delay and reliability of the developed system using a Raspberry Pi 3 processor considering several scenarios related to the state of the environment and the condition of the traffic signs. A real-time testbed implementation has been conducted considering twenty different traffic signs and the results show that the system has more than 90% accuracy and is reliable with an acceptable delay

Multi Hop Transmission in IEEE 802.11 Low Rate Ad Hoc Network Using ARP-Route

Ad hoc networks are becoming more important in the modern complex environment. The ad hoc network can be used to instantly connect to the local or remote networks such as the Internet without the need of pre-existing infrastructure or centralized administration. The users of the network together will establish the infrastructure. The disadvantage of wireless communication is that it has limited range of radio transmission. Due to this, multiple network ‘hops’ are needed for one device to exchange data with another device across the network. In an ad hoc network, these devices will not only operate as a host but also as a router to forward the packets. There are varieties of routing protocols targeted for this environment that have been proposed and developed. However, most of them suffer from high overhead data traffic. The main purpose of this project is to implement the ad hoc network with the existing network protocol that had already been used in network environment which is the Address Resolution Protocol (ARP). ARP was designed to announce or find MAC addresses. The novelty of this study is that we have extended the usage of the ARP protocol to act as routing protocol in wireless ad hoc network. The ARP route provides two new operation types, ARP Forward Request and ARP Forward Reply to allow the multihop transmission using intermediate nodes to forward the request and reply. These two operation types only used the current operation codes which are ‘0x0001’ for request and ‘0x0002’ for reply. This work on the routing protocol creates a new operation code for the ARP forwarding scheme which is ‘0x000c’ for forwarding. We have successfully managed to create a multi hop transmission in an ad hoc network by using the current existing operation code for the ARP forwarding. The work scope focus only on proving that the method can be applied hence it is not necessarily to prove the effectiveness of this proposed method yet. Therefore, the outcome of the study shows that the data can be sent through multi hop transmission until it reaches the destination. The 802.11b test-bed has been configured and the ARP routing protocol has been implemented for multi hop transmission. The experiment in the open space provides the comparison of environment with obstacles and without obstacles. We manage to get more than 50% of packet receive at a place with no obstacles and more than 45% in a place with obstacles. The proof of method is shown by using several graphs namely in terms of time, packet loss and also throughput

Analysis Of Spinal Electromyography Signal When Lifting An Object

Lifting and swinging are daily activities that human do using the spine.Furthermore,spine provides support during standing and walking.Therefore,it is very important in everyday activities and it will be inconvenient when it is injured.Technology has provided ways to machine and human integration in helping or supporting people in their daily tasks.To make this integration successful, machines or robots need to understand the human muscle activity.To do so,electromyography (EMG) a bio signal record the electricity generated by muscle was implemented.However,the signal often influenced by the unwanted noise.In this paper,the MVC normalization method is applied to determine the spinal EMG signal on lumbar multifidus muscle when lifting an object.In order to analyze the identity of spinal EMG signal,two statistical analyses are done;1) ANOVA analysis and 2)Boxplot analysis.The signal will go through 8th order Gaussian function or Exponential Weight Moving Average Filter before being analysed.Results show that Exponential Weight Moving Average Filter gives more consistent value compared to 8th order Gaussian function which is 0.0428V RMSE based on linear fitting done from the maximum amplitude gather from the boxplot analysis done

Development of a Tool for Assessing the Kinematics and Kinetics of Pen Skills

Pen skills are essential in the learning process, as they help to develop the brain–body coordination. This development is significant for young children, as these skills will help them learn better at school. Learning pen skills will provide an advantage in presenting their knowledge. This research focused on quantifying and interpreting kinematic and kinetic data for pen-based activities. The kinematic data were quantified using a tablet computer on the basis of a stylus pen input. The kinetic data were quantified using a specially developed stylus equipped with force sensors using a MyRIO data acquisition board. A LabVIEW code was developed to provide interaction between users and the tablet. This code was also used to record the pen stylus motion and the force applied at the stylus as a function of time. Then, the pen skills performance was investigated by extracting the kinematic and kinetic parameters from the recorded signal by using an offline algorithm. This algorithm synchronised the kinematic and kinetic signals, as both the signals were quantified using two different devices. This enabled the study of the relationship between the kinematic and the kinetic parameters involved in pen-based tasks. The system was validated by comparing the pen skills performance between the dominant and the non-dominant hand of adults. The pen skills performance was also investigated for three different writing speeds (Natural, Accurate, and Fast) and two different sizes. Moreover, the pen skills performance was evaluated between the dominant and the non-dominant hand for tracing and copying tasks

Development Of Real-Time Lora-Based Air Pollution Monitoring System

Air pollution can cause long-term health effects on humans, such as heart disease, lung cancers, and respiratory disease. There are many forms of contamination induced by smoke or gas emissions due to fossil fuel burning from transportation. Furthermore, manufacturing operations also negatively impact the air quality, where the production of plastics, electronics, and rubber, has contributed to a rise in organic carbon, inorganic carbon, and dust contaminations. Therefore, in this work, a real-time air pollution monitoring system has been developed to monitor air quality considering three types of gas sensors which are MQ2, MQ7 and MQ135. Also, LoRa communication technology is used as the communication modules between the sensor node located at the site and the gateway. The system is also equipped with an additional notification system to send the monitored air concentration data to the control room via the Telegram application. For monitoring purposes, the monitored data from the sensors will be updated every 5 minutes in the server using the Node-Red platform. The performance of the developed system has been evaluated considering six different distances between the sensor node and gateway, and the results show that the system has high reliability. The results also indicate that the average received signal strength indicator (RRSI) value of the LoRa module between the sensors and gateway reduced with the increasing distance between the sensor node and gateway. However, this does not affect the performance of the developed system

Real-Time Traffic Sign Detection And Recognition Using Raspberry Pi

Nowadays, the number of road accident in Malaysia is increasing expeditiously. One of the ways to reduce the number of road accident is through the development of the advanced driving assistance system (ADAS) by professional engineers. Several ADAS system has been proposed by taking into consideration the delay tolerance and the accuracy of the system itself. In this work, a traffic sign recognition system has been developed to increase the safety of the road users by installing the system inside the car for driver’s awareness. TensorFlow algorithm has been considered in this work for object recognition through machine learning due to its high accuracy. The algorithm is embedded in the Raspberry Pi 3 for processing and analysis to detect the traffic sign from the real-time video recording from Raspberry Pi camera NoIR. This work aims to study the accuracy, delay and reliability of the developed system using a RaspberryPi 3 processor considering several scenarios related to the state of the environment and the condition of the traffic signs. A real-time testbed implementation has been conducted considering twenty different traffic signs and the results show that the system has more than 90% accuracy and is reliable with an acceptable dela

Portable Wireless Traffic Light System (PWTLS)

A Portable Wireless Traffic Light System using a microcontroller and wireless ZigBee is the best system to control the traffic flow during the road construction or maintenance. This traffic light is designed to solve the various type of hazard which may happen to the worker, flagman and also road users during the road construction. The communication between these two traffic lights is via wireless. Due to this it can be deployed anywhere because no wire is used. This system is equipped with the safety purpose where it is equipped with motion and infrared sensor to detect and count the number of vehicles to avoid any collision. This automated system can be used 24-hours in various weather conditions. This eliminate the limited working hours when using the flagman. This system is a low cost system where it uses microcontroller to control the system

PARAMETER STUDY OF STABLE WALKING GAITS FOR NAO HUMANOID ROBOT

It is a challenge to any researcher to maintain the stability of the robot while in the walking motion. This paper proposes for parameter study of a walking pattern method which is inspired by the Dip Goswami (2009). The walking pattern is generated based on three points. These points are located at ankle left and right and one at the hip of the NAO humanoid robot. By using these points the walking gaits are generated to use as a reference point while walking motion. Then, an inverse kinematics with geometric solution of a ten degree-of-freedom humanoid robot is formulated from hip until the ankle joint. By sampling period of time with ten this reference point is used to find the joint angle of each link. The NAO humanoid robot is built in with force resistive sensor (FSR) located under both feet are used to determine the walking stability by using force distributer concept. The zero moment point of the robot is calculated on the normalized value between FSR reading from right leg and left leg. The result shown based on the real time simulation environment by using Webots Robotic Software. A simulation result shows that a NAO humanoid robot successfully walks in stable condition by following five different walking parameter setting. The humanoid robot is stable if and only if the normalized value of the ZMP is between 1 and -1