SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING

Spatio-temporal database is a database that manages data with spatial and temporal semantics to fulfill the need for the history of an object movement. However, to be able to handle a query that include two moving objects, ordinary spatio-temporal operations cannot be used. Therefore, Sakr and Gü...

Full description

Saved in:
Bibliographic Details
Main Author: Muhammad Suria Nagara, Raihan
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/56905
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:56905
spelling id-itb.:569052021-07-22T14:53:44ZSPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING Muhammad Suria Nagara, Raihan Indonesia Final Project Spatio-temporal database INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/56905 Spatio-temporal database is a database that manages data with spatial and temporal semantics to fulfill the need for the history of an object movement. However, to be able to handle a query that include two moving objects, ordinary spatio-temporal operations cannot be used. Therefore, Sakr and Güting (2011) proposed a complex query called STP query. Yogiandra (2019) created a tool that implements STP queries. However, in this implementation, a gap appears in the generated data type which is referred to as unknown data, that has not been handled and is considered non-existent. In this final project, the handling of unknown data is carried out by looking for the crossover interval. There are two stages in the search for crosseover interval, namely the possibility searching stage which determines whether a crossing occurs in the interval and the interval division stage which performs binary division of the interval until the interval is small enough to be considered as a crossover interval. The size of the crossover interval is determined by inputting the maximum crossing distance by the user. The implementation for the distribution method is in the form of lifted function which performs type overload on the lifted function in Yogiandra (2019)'s tool. To implement this function, the UnitCheck function is formed which will look for the crossover interval between two units. The UnitCheck function will be executed for all units inputted into the lifted function and the result will be matched with the function arguments the user entered. Based on the test results using specially generated data containing all cases of possible crossovers on unknown data, this method succeeded in processing unknown data that was not processed by the STP query tool created by Yogiandra (2019). text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Spatio-temporal database is a database that manages data with spatial and temporal semantics to fulfill the need for the history of an object movement. However, to be able to handle a query that include two moving objects, ordinary spatio-temporal operations cannot be used. Therefore, Sakr and Güting (2011) proposed a complex query called STP query. Yogiandra (2019) created a tool that implements STP queries. However, in this implementation, a gap appears in the generated data type which is referred to as unknown data, that has not been handled and is considered non-existent. In this final project, the handling of unknown data is carried out by looking for the crossover interval. There are two stages in the search for crosseover interval, namely the possibility searching stage which determines whether a crossing occurs in the interval and the interval division stage which performs binary division of the interval until the interval is small enough to be considered as a crossover interval. The size of the crossover interval is determined by inputting the maximum crossing distance by the user. The implementation for the distribution method is in the form of lifted function which performs type overload on the lifted function in Yogiandra (2019)'s tool. To implement this function, the UnitCheck function is formed which will look for the crossover interval between two units. The UnitCheck function will be executed for all units inputted into the lifted function and the result will be matched with the function arguments the user entered. Based on the test results using specially generated data containing all cases of possible crossovers on unknown data, this method succeeded in processing unknown data that was not processed by the STP query tool created by Yogiandra (2019).
format Final Project
author Muhammad Suria Nagara, Raihan
spellingShingle Muhammad Suria Nagara, Raihan
SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
author_facet Muhammad Suria Nagara, Raihan
author_sort Muhammad Suria Nagara, Raihan
title SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
title_short SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
title_full SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
title_fullStr SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
title_full_unstemmed SPATIO-TEMPORAL PATTERN QUERIES PROCESSING ON MOVING OBJECT DATABASE WITH UNKNOWN DATA HANDLING
title_sort spatio-temporal pattern queries processing on moving object database with unknown data handling
url https://digilib.itb.ac.id/gdl/view/56905
_version_ 1822930317643612160