Pid Controlled Line Follower Robot Design on Indoor 3D Networks

Robots are commonly used and developed for different purposes in various areas such as research, educational, commercial, and industrial fields, also in emergency situations and space missions in today’s modern world. Robots are the machines that increasingly gain the importance with each passing day by the development of micro-electronics and micro-mechanics industry. To define a machine as a robot, it needs to have the sensors to check its environment; the mechanisms to evaluate the information received from these sensors and to transfer to the processing units.In this study, an intelligent controlled line follower robot was developed. Proportional-integral-derivative (PID) method was used for controlling. According to the information from the sensors, the method applied to the engines as Pulse Width Modulation (PWM). Online Fez Panda II embedded system board was used as the control element. This board has a 2-bit ARM 7 (Acorn RISC Machine) processor and it is suitable to .Net Micro Framework Technology. The system software was written with C# programming language in Visual Studio 2010 platform.The robot was tested on 3D indoor network, and has potential to be used for evacuation process on extraordinary sitautions in buildings. Another usage areas of this robot are factories and production lines. 3D network analyses and navigation applications could also be performed using the lines on the ground of this kind of environment

A new method for vehicles detection and tracking using information and image processing

In this article, a new method of vehicles detecting and tracking is presented: A thresholding followed by a mathematical morphology treatment are used. The tracking phase uses the information about a vehicle. An original labeling is proposed in this article. It helps to reduce some artefacts that occur at the detection level. The main contribution of this article lies in the possibility of merging information of low level (detection) and high level (tracking). In other words, it is shown that many artefacts resulting from image processing (low level) can be detected, and eliminated thanks to the information contained in the labeling (high level). The proposed method has been tested on many video sequences and examples are given illustrating the merits of our approach

Integration of CityGML and oracle spatial for implementing 3D network analysis solutions and routing simulation within 3D-GIS environment

3D navigation within a 3D-GIS environment is increasingly getting more popular and spreading to various fields. In the last decade, especially after the 9/11 disaster, evacuating the complex and tall buildings of today in case of emergency has been an important research area for scientists. Most of the current navigation systems are still in the 2D environment and that is insufficient to visualize 3D objects and to obtain satisfactory solutions for the 3D environment. Therefore, there is currently still a lack of implementation of 3D network analysis and navigation for indoor spaces in respect to evacuation. The objective of this paper is to investigate and implement 3D visualization and navigation techniques and solutions for indoor spaces within 3D-GIS. For realizing this, we have proposed a GIS implementation that is capable of carrying out 3D visualization of a building model stored in the CityGML format and perform analysis on a network model stored in Oracle Spatial. The proposed GUI also provides routing simulation on the calculated shortest paths with voice commands and visual instruction

Innovations in Smart Cities Applications Volume 4: The Proceedings of the 5th International Conference on Smart City Applications

This proceedings book is the fourth edition of a series of works which features emergent research trends and recent innovations related to smart city presented at the 5th International Conference on Smart City Applications SCA20 held in Safranbolu, Turkey. This book is composed of peer-reviewed chapters written by leading international scholars in the field of smart cities from around the world. This book covers all the smart city topics including Smart Citizenship, Smart Education, Smart Mobility, Smart Healthcare, Smart Mobility, Smart Security, Smart Earth Environment & Agriculture, Smart Economy, Smart Factory and Smart Recognition Systems.info:eu-repo/semantics/publishedVersio

kCV-B: Bootstrap with Cross-Validation for Deep Learning Model Development, Assessment and Selection

This study investigates the inability of two popular data splitting techniques: train/test split and k-fold cross-validation that are to create training and validation data sets, and to achieve sufficient generality for supervised deep learning (DL) methods. This failure is mainly caused by their limited ability of new data creation. In response, the bootstrap is a computer based statistical resampling method that has been used efficiently for estimating the distribution of a sample estimator and to assess a model without having knowledge about the population. This paper couples cross-validation and bootstrap to have their respective advantages in view of data generation strategy and to achieve better generalization of a DL model. This paper contributes by: (i) developing an algorithm for better selection of training and validation data sets, (ii) exploring the potential of bootstrap for drawing statistical inference on the necessary performance metrics (e.g., mean square error), and (iii) introducing a method that can assess and improve the efficiency of a DL model. The proposed method is applied for semantic segmentation and is demonstrated via a DL based classification algorithm, PointNet, through aerial laser scanning point cloud data

An evacuation system for extraordinary indoor air pollution disaster circumstances

The problem of evacuating the buildings through the shortest path with safety has become more important than ever in a case of indoor air pollution incidents (i.e. fire, gas leak, airlessness, smother) taken place in complex and tall buildings of today’s world. In this paper, it is aimed to present a 3D interactive human navigation and evacuation system which generates an optimum path in 3D modeled buildings and provides 3D visualization and simulation. The system ge nerates and transmits the guiding expression to the mobile devices such as PDA’s, laptops etc. via internet. In order to evaluate its performance in a case of extraordinary indoor air pollution circumstance, the system was tested on a complex building model by using GPRS and WIFI internet connections based on the web technologies

A 3D-GIS implementation for realizing 3D network analysis and routing simulation for evacuation purpose

The need for 3D visualization and navigation within 3D-GIS environment is increasingly growing and spreading to various fields. When we consider current navigation systems, most of them are still in 2D environment that is insufficient to realize 3D objects and obtain satisfactory solutions for 3D environment. One of the most important research areas is evacuating the buildings with safety as more complex building infrastructures are increasing in today’s world. The end user side of such evacuation system needs to run in mobile environment with an accurate indoor positioning while the system assist people to the destination with support of visual landscapes and voice commands. For realizing such navigation system we need to solve complex 3D network analysis. The objective of this paper is to investigate and implement 3D visualization and navigation techniques and solutions for indoor spaces within 3D-GIS. As an initial step and as for implementation a GUI provides 3D visualization of Corporation Complex in Putrajaya based on CityGML data, stores spatial data in a Geo-Database and then performs complex network analysis under some different kind of constraints. The GUI also provides a routing simulation on a calculated shortest path with voice commands and visualized instructions which are intended to be the infrastructure of a voice enabled mobile navigation system in our future work

GIS-Based Terrain Analysis of Balakot Region after Occurred Landslide Disaster in October 2005

The landslide susceptibility models require the appropriate and reliable terrain analytical based study of the landslides prone areas using SRTM (Shuttle Radar Topography Mission) data, based on certain GIS (Geographical Information Systems) and remote sensing techniques. This research paper focuses on the analysis of the terrain conditions of Balakot region. The analytical operations have been used in the different phases: (i) Extracting the study area from the large data; (ii) preparing it into grid format; (iii) developing contour lines with certain contour intervals (iv) Re-classification of it into required classes and (v) preparation of digital terrain model with its different required various supplementary models for analyzing the terrain conditions of the study area located in Mansehra district, north part of Pakistan where the great earthquake induced landslide disaster occurred in October 2005. This analytical study has notified the different sensitive issues concerning to the critical slope angles, variation in the elevation and the surface of study area. The various distinctions in the terrain phenomenon validate the occurred and probable landslides because the topography of such study area can predict the various probable landslide hazards, vulnerability and risk threats in the region again. This analytical study can be useful for the decisive authorities by becoming pro-active to rebuild the region to mitigate the expected losses from the natural disaster

SmartEscape: A Mobile Smart Individual Fire Evacuation System Based on 3D Spatial Model

We propose SmartEscape, a real-time, dynamic, intelligent and user-specific evacuation system with a mobile interface for emergency cases such as fire. Unlike past work, we explore dynamically changing conditions and calculate a personal route for an evacuee by considering his/her individual features. SmartEscape, which is fast, low-cost, low resource-consuming and mobile supported, collects various environmental sensory data and takes evacuees’ individual features into account, uses an artificial neural network (ANN) to calculate personal usage risk of each link in the building, eliminates the risky ones, and calculates an optimum escape route under existing circumstances. Then, our system guides the evacuee to the exit through the calculated route with vocal and visual instructions on the smartphone. While the position of the evacuee is detected by RFID (Radio-Frequency Identification) technology, the changing environmental conditions are measured by the various sensors in the building. Our ANN (Artificial Neural Network) predicts dynamically changing risk states of all links according to changing environmental conditions. Results show that SmartEscape, with its 98.1% accuracy for predicting risk levels of links for each individual evacuee in a building, is capable of evacuating a great number of people simultaneously, through the shortest and the safest route