Sustainable Development Goals of Mapúa University

Sustainable Development Goals of Mapúa University

Sustainable Development Goals of Mapúa University

SDG-Related Research Outputs

2020

Title
CAHM: Companion Animal Health Monitoring System
Quantitative abundance and concentration of toxigenic and odor producing cyanobacteria in laguna lake: New discovery in the Philippines
ET-based Irrigation System with Automated Bird Deterrent System
Evapotranspiration (ET)-Based Irrigation System with Internet of Things (IoT) Integration for Capsicum Annuum Farming: A Methodology
Urban Diversity of Butterflies as a Biological Indicator of an Air Quality in Manila, Philippines
Butterflies behaviors and their Natural Enemies and Predators in Manila, Philippines

2019

Title
PetCare: A smart pet care IoT mobile application

2018

Title
Prediction at ungauged river flow as applied to canas river basin in cavite using morphometric analysis
Validation of LiDAR point clouds for classification of high-value crops using geometric-and reflectance-based extraction algorithm
Forest classification and deriving forestry resource parameters in infanta quezon using lidar data and validation with laser range finder
Hydrologic modeling and delineation of Calumpang river watershed using GIS and hydrologic model system

2017

Title
Forest mapping and classification of forest Type using LiDAR data and tree specie identification through image processing based on leaf extraction algorithms
Development and implementation of low cost salinity and temperature monitoring system for mangrove forest
Biodiversity sustainability using telemetry for the remote transmission of data from Lake Buhi, Camarines sur
Characterization using spectral signature of tropical plants through fast fourier transform
Mesozoic radiolarian faunas from the northwest Ilocos Region, Luzon, Philippines and their tectonic significance
Object-based land use and land cover mapping from LiDAR data and orthophoto: Application of decision tree-based data selection for SVM classification
Resource mapping of high value crops in cavite and development of the algorithm for detecting coconut, sugarcane, and rice using lidar data
A one-against-all extraction of Cocos nucifera at individual tree crown level via support vector machine classification using LiDAR data