Purwarupa Robot Pemadam Api Dengan Sensor Ultrasonik dan Ultraviolet Berbasis AT89S52

The fire often takes many victims. Fire detection system sometime can not prevent this from happening. Therefore, it is essential to develop a robot that can detect the present of fire as well as extinguish it. This research aimed to design a fire extinguisher robot using AT89S52 microcontroller as its controller. A DC fan controlled by a relay is utilized to put out the fire and a fire sensor (UV-Tron) is used to detect the presence of fire. The movement of the robot is driven by motor DC. The robot can detect the surrounding obstacles and possess an ultrasound-based navigation system. If the ultrasound system detects an obstacle, the robot will automatically turn without colliding the obstacle or other things around it. The result has shown that this fire extinguisher robot can be built using hardware and software controlled by an AT89S52 microcontroller. It can be concluded from the tests that the robot can detect fire as far as 5 meter distance and able to successfully put out the fire

Robot competitions trick students into learning

It has been shown in the past that robots help to bring theoretical concepts into practice, while at the same time increasing the motivation of the students. Despite these benefits, robots are hardly ever integrated in education programs and at the same time students feel that they have the competences nor the infrastructure to build a robot on their own. Therefore the workgroup electronics (WELEK) of Ghent University gives students the opportunity to build a robot by organizing workshops and competitions. Up until now, four competitions were organized in which over 200 students voluntarily participated. This paper describes our approach in the hope that it will inspire other educators to do the same thing. We also measured the effectiveness of our competitions by sending each of the participants a questionnaire. The results confirm that students acquire relevant technical competences by building a robot, learn to work as a team and are challenged to use their creativity

FIRE-FIGHTING ROBOT

Along the way with the evolvement and advancement of science and technology, human beings tend to use robot to perform their daily routine works or some dangerous tasks such as rescuing victims from hazardous sites, whereby the rescuing tasks might pose certain level of risks to human beings. In conjunction of that reason, the ultimate goal, aim and objective of this project is to develop and implement an Autonomous Fire-Fighting Mobile Platform (AFFMP) that is equipped with the basic fire-fighting knowledge that can patrol through the hazardous sites with the aim of early detection for fire and extinguish it using the built-in fire extinguishing system on the platform itself. The AFFMP is capable to patrol the building continuously via the guiding track while at the same time, it attempts to locate for fire source by using the Flame Sensors as the primary detection. The detection for the occurrence of fire source in AFFMP is also assisted by the secondary detection sensors, which are the Heat/Temperature Sensor and the Smoke Sensor as well. Once the fire source is being identified, it will move directly towards the fire source and extinguish it in the shortest time by using the fire extinguisher that is attached to its platform. In short, the project can be considered as successful as it has achieved the expected goals and objectives

FIRE-FIGHTING ROBOT

Along the way with the evolvement and advancement of science and technology, human beings tend to use robot to perform their daily routine works or some dangerous tasks such as rescuing victims from hazardous sites, whereby the rescuing tasks might pose certain level of risks to human beings. In conjunction of that reason, the ultimate goal, aim and objective of this project is to develop and implement an Autonomous Fire-Fighting Mobile Platform (AFFMP) that is equipped with the basic fire-fighting knowledge that can patrol through the hazardous sites with the aim of early detection for fire and extinguish it using the built-in fire extinguishing system on the platform itself. The AFFMP is capable to patrol the building continuously via the guiding track while at the same time, it attempts to locate for fire source by using the Flame Sensors as the primary detection. The detection for the occurrence of fire source in AFFMP is also assisted by the secondary detection sensors, which are the Heat/Temperature Sensor and the Smoke Sensor as well. Once the fire source is being identified, it will move directly towards the fire source and extinguish it in the shortest time by using the fire extinguisher that is attached to its platform. In short, the project can be considered as successful as it has achieved the expected goals and objectives

Hazardous Chemical Source Localisation in Indoor Environments Using Plume-tracing Methods

Bio-inspired chemical plume-tracing methods have been applied to mobile robots to detect chemical emissions in the form of plumes and localise the plume sources in various indoor environments. Nevertheless, it has been found from the literature that most of the research has focused on plume tracing in free-stream plumes, such as indoor plumes where the chemical sources are located away from walls. Moreover, most of the experimental and numerical studies regarding the assessment of indoor plume-tracing algorithms have been undertaken in laboratory-scale environments. Since fluid fields and chemical concentration distributions of plumes near walls can be different from those of free-stream plumes, understanding of the performance of existing plume-tracing algorithms in near-wall regions is needed. In addition, the performance of different plume-tracing algorithms in detecting and tracing wall plumes in large-scale indoor environments is still unclear. In this research, a simulation framework combining ANSYS/FLUENT, which is used for simulating fluid fields and chemical concentration distributions of the environment, and MATLAB, with which plume-tracing algorithms are coded, is applied. In general, a plume-tracing algorithm can be divided into three stages: plume sensing, plume tracking and source localisation for analysis and discussion. In the first part of this research, an assessment of the performance of sixteen widely-used plume-tracing algorithms equipped with a concentration-distance obstacle avoidance method, was undertaken in two different scenarios. In one scenario, a single chemical source is located away from the walls in a wind-tunnel-like channel and in the other scenario, the chemical source is located near a wall. It is found that normal casting, surge anemotaxis and constant stepsize together performed the best, when compared with all the other algorithms. Also, the performance of the concentration-distance obstacle avoidance method is unsatisfactory. By applying an along-wall obstacle avoidance method, an algorithm called vallumtaxis, has been proposed and proved to contribute to higher efficiencies for plume tracing especially when searching in wall plumes. The results and discussion of the first part are presented in Chapter 4 of this thesis. In the second part, ten plume-tracing algorithms were tested and compared in four scenarios in a large-scale indoor environment: an underground warehouse. In these four scenarios, the sources are all on walls while their locations are different. The preliminary testing results of five algorithms show that for most failure cases, the robot failed at source localisation stage. Consequently, with different searching strategies at source localisation stage, this research investigated five further algorithms. The results demonstrated that the algorithm with a specially-designed pseudo casting source localisation method is the best approach to localising hazardous plume sources in the underground warehouse given in this research or other similar environments, among all the tested algorithms. The second part of the study is reported in Chapter 5 of this thesis.Thesis (MPhil) -- University of Adelaide, School of Mechanical Engineering, 202