Adi Wibowo

Autonomous quadcopter swarm robots for object localization and tracking

A swarm Unmanned Aerial Vehicle (UAV) or quad copter robot for object localization and tracking has been developed. The robot is potentially utilized for military purpose, i.e. doing patrol continuously especially in frontier area. In other words, the UAV is proposed to carry out patrol and exploration by exploring coverage area, find, localize and track suspicious objects. The swarm robots are equipped with Modified Particle Swarm Optimization (PSO) Algorithm for intelligent feature. PSO is an optimization algorithm where each agent of swarm will use its individual perception (local base) and community perception (global base). This swarm quad copter system was implemented using Robot Operating System (ROS) Framework. Experiment was conducted with 3 quadcopter agents and one object as the target. Two main scenarios have been exercised, i.e. a scenario with steady target and another one with moving target. Experimental result shows that Modified PSO implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.

Enhanced adaptive traffic signal control system using camera sensor and embedded system

Traffic plays an important role in social stability and community development. Without an appropriate traffic signal control system, the possibility of traffic congestion will be very high and causes various negative impacts. The traffic signal control system with video camera sensor is implemented in embedded systems using BeagleBoard-xM. The system uses Viola-Jones method and Haar Training in detecting the vehicle object from a video frame. Then, Euclidean distance and kalman filter methods are used in tracking the vehicle. The ability of kalman filter in predicting the next position of the object is a very important feature for multi-object tracking. The number of counted vehicles in each lane at the intersection then will be processed using Fuzzy Logic to determine optimal cycle time and split time.

Spatial temporal analysis of urban heat hazard in Tangerang City

Urban heat is a natural phenomenon which might caused by human activities. The human activities were represented by various types of land-use such as urban and non-urban area. The aim of this study is to identify the urban heat behavior in Tangerang City as it might threats the urban environment. This study used three types of remote sensing data namely, Landsat TM, Landsat ETM+ and Landsat OLI-TIRS, to capture the urban heat behavior and to analysis the urban heat signature of Tangerang City in 2001, 2012, 2013, 2014, 2015 and 2016. The result showed that urban heat signature change dynamically each month based on the sun radiation. The urban heat island covered only small part of Tangerang City in 2001, but it was significantly increased and reached 50% of the area in 2012. Based on the result on urban heat signature, the threshold for threatening condition is 30 oC which recognized from land surface temperature (LST). The effective temperature (ET) index explains that condition as warm, uncomfortable, increase stress due to sweating and blood flow and may causing cardiovascular disorder.

Spatial Temporal Land Use Change Detection Using Google Earth Data

Land use as representation of human activities had different type. Human activity needs land for home, food, school, work, and leisure. Land use changed depends on human activity in the world within spatial and temporal term. This study aims to identify land use change using Google Earth data spatially and temporally. To answer the aim of this research, Google Earth data within five-year used for the analysis. This technique use for detection and mapping the land use change. The result saw the spatial-temporal land use change each year. This result addressed very importance of Google Earth Data as spatial temporal land use detection for land use mapping.

Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia

In this paper, two methods to retrieve the Land Surface Temperature (LST) from thermal infrared data supplied by band 10 and 11 of the Thermal Infrared Sensor (TIRS) onboard the Landsat 8 is compared. The first is mono window algorithm developed by Qin et al. and the second is split window algorithm by Rozenstein et al. The purpose of this study is to perform the spatial distribution of land surface temperature, as well as to determine more accurate algorithm for retrieving land surface temperature by calculated root mean square error (RMSE). Finally, we present comparison the spatial distribution of land surface temperature by both of algorithm, and more accurate algorithm is split window algorithm refers to the root mean square error (RMSE) is 7.69° C.

Urban forest topographical mapping using UAV LIDAR

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng’ village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng’ village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of t...

PEMETAAN PERGERAKAN LALU LINTAS KENDARAAN DI KELURAHAN KUKUSAN KOTA DEPOK

ABSTRAK Pergerakan penduduk dari tempat asal ke tujuan sejalan dengan pergerakan kendaraan. Pergerakan penduduk dari Depok ke Jakarta berbeda di tiap daerah perbatasan, seperti di Kelurahan Kukusan. Penelitian ini bertujuan untuk mengetahui pemetaan pergerakan lalu lintas kendaraan di Kelurahan Kukusan. Untuk menjawab tujuan penelitian digunakan analisis spasial-temporal dengan unit data segmen jalan dan data primer yaitu: lebar dan arah jalan, asal-tujuan, rute, kecepatan dan volume kendaraan. Hasil pemetaan pergerakan lalu lintas kendaraan di Kelurahan Kukusan menunjukkan bahwa model jaringan jalan dengan arah selatan, timur dan barat secara umum menuju ke utara untuk pagi hari dan sebaliknya untuk sore hari. Hasil analisis pola spasial menunjukkan pola pergerakan kendaraan di Kelurahan Kukusan memusat di Jalan K. H. M. Usman. Segmen utara lebih banyak dilalui oleh lalu lintas kendaraan dari Kelurahan Kukusan, segmen tengah lebih banyak lalu lintas kendaraan dari dalam dan luar Kelurahan Kukusan dan segmen selatan lebih banyak lalu lintas kendaraan yang datang ke Kelurahan Kukusan. Analisis Spasial-temporal menunjukkan bahwa segmen yang lebih banyak dilalui oleh lalu lintas kendaraan dengan pola pagi hari di Jalan K. H. M. Usman memiliki nilai volume kendaraan 1.409,05 smp/jam adalah segmen tengah. Segmen selatan yang memiliki nilai derajat kejenuhan 0,71 lebih tinggi dari segmen tengah. Pola sore hari yang memiliki volume kendaraan tertinggi adalah segmen selatan yaitu 1.251,8 smp/jam dengan nilai derajat kejenuhan 0,79. Hasil penelitian menunjukkan bahwa segmen jalan dengan jumlah Point of Interest (POI) terbanyak memiliki derajat kejenuhan yang lebih tinggi. Kata Kunci : jaringan jalan, lalu lintas, model spasial, pola spasial-temporal ABSTRACT The movement of people from origin to destination was aligned with the movement of vehicular. Movements of people from Depok to Jakarta had different spatialy like Kukusan Village. The aim of study to determine the traffic patterns of vehicle movement on Kukusan Village. To answer this research objective used spatial-temporal analysis with unit segments and primary data were: wide and direction of the road, origin-destination, routes, speed and volume of vehicular. The map of the movement of vehicular traffic in Kukusan Village by respondents shows a model of the road network to the south, east and the west generaly headed north in the morning and vice versa for afternoon. The results of the spatial patterns indicate that movement of vehicles in Kukusan Village centered on K. H. M. Usman northern segment with more impassable by vehicle traffic from Kukusan Village, the middle segment more vehicle traffic from within and outside Kukusan Village and southern segments more traffic vehicles come to Kukusan Village. Spatial-temporal analysis shows the northern segment more impassable by vehicle traffic in the Kukusan Village, the morning patterns at K. H. M Usman had value of vehicle volume 1,409.05 upc/hour in midle segmen, although the southern segment with value of degrees saturation 0,71 more than value of midle segmen.The afternoon pattern within highest volume on southern segmen with vehicle volume 1,251.8 upc/hour with degres saturation value 0,79. These results concluded that the road segment with highest number of POI had a highest degres saturation. Keyword : road networks, traffic, spatial modeling, spatial-temporal pattern