Spatial and temporal multi-level overlapping summaries for pattern detection, with application in agriculture

• Grant number: 12/25169-5
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: June 01, 2013
• End date: May 31, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Claudia Maria Bauzer Medeiros
• Grantee: Jordi Creus Tomàs
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The advent of a steadily increasing number of data sources that measure the variation of natural phenomena (for instance, streams from RFID networks, embedded sensors) has opened up many new challenges to the database research community, such as continuous multi-query processing and optimization, datastream management and warehousing, information and pattern mining. We consider in this project proposal the problem of pattern-based query and detection of spatial and temporal patterns in such kinds of data, applied to the context of agricultural analysis. The approach proposed lies in the use of a structure of event summaries, aggregating data at different spatio-temporal levels of granularity. The research will be validated against meteorological data, and also time series extracted from satellite images. The methods to be developed extend the state of the art, in the sense that they will explore combinations of patterns in multiple scales. The patterns are applied to structures that summarize the data, to be proposed as part of the project. The project will also analyze and develop an event pattern evaluation model that fits these constraints. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

TOMAS, JORDI CREUS; FARIA, FABIO AUGUSTO; DALLA MORA ESQUERDO, JULIO CESAR; COUTINHO, ALEXANDRE CAMARGO; MEDEIROS, CLAUDIA BAUZER. SiRCub, A Novel Approach to Recognize Agricultural Crops Using Supervised Classification. INTERNATIONAL JOURNAL OF AGRICULTURAL AND ENVIRONMENTAL INFORMATION SYSTEMS, v. 8, n. 4, p. 20-36, OCT-DEC 2017. (13/08293-7, 12/25169-5)