By employing unsupervised and supervised machine learning techniques, we explore the feasibility of utilizing mobile call detail records (CDRs) as well as geographic information system (GIS) and remote sensing (RS) data to map poverty spatially
Homagama, a town in the Colombo District in Sri Lanka, is officially classified as a rural area. However, a visitor to Homagama is sure to find this designation confusing; it lies just 10 kilometers off Maharagama, one of the most densely populated cities in the country. Large parts of Homagama are also densely developed, with buildings packed together. Nevertheless, Homagama is classified as a rural area because it is administered by a Pradeshiya Sabha rather than a Municipal or an Urban Council. Officially, an area in Sri Lanka is considered urban if it is administered by a Municipal or an Urban Council.
A research brief which explores the key data sources, algorithmic techniques and roadblocks in applying remote sensing techniques for development.
Recently I presented a paper titled – Robustness of the mHealthSurvey Midlet for a Real-Time Biosurveillance program at the 2010 International Symposium on Medical Informatics and Communications Technology – in Taipei, Taiwan. The main focus was on mobile computing; especially surrounding Body Area Networks (BAN) that is in the working mills of the IEEE 802 standardization process under the auspices of Task Group 6. The present day challenges that countries like Taiwan and Japan face, also propagating in to other Asian countries, are increase in chronic illnesses, aging population, and need for convenience. Within this frame, researchers are realizing the growing need for remote sensing and maintenance of health; such remote maintenance ICT based services would reduce patient admissions (or inward patients), which countries like India, Sri Lanka, Taiwan, etc, fully subsidize and can be drastically reduced. The mHealthSurvey has proven the capability to transport digitized data compressed to ~ 2KB over GPRS-10 and higher networks in rural India and Sri Lanka.
From 13-15 October, 2008, The United Nations Office for Outer Space Affairs (UNOOSA) and the German Aerospace Center (DLR) with support from the International Strategy for Disaster Reduction – Platform for the Promotion of Early Warning (UNISDR-PPEW) and the United Nations University – Institute for Environment and Human Security (UNU-EHS) organized the Second United Nations International UN-SPIDER Workshop on “Disaster Management and Space Technology – Bridging the Gap” in Bonn, Germany. LIRNEasia researcher, Natasha Udu-gama was one of 134 participants representing 49 countries. The 3-day UN-SPIDER workshop was notable in that it featured a number of German and international presentations on the themes of Session 1: “Space technology in support of risk and disaster management”, Session 2: “Vulnerability and Risk Assessment”, Session 3: “Contributions of space-based technologies to existing and proposed early warning systems”, and Session 4: “Disaster Medicine, Telemedicine and Integrated Vector Management (IVM)”. Natasha Udu-gama presented on “Last Mile Hazard Information Dissemination” during Session 3 highlighting the usage of WorldSpace Addressable Radios for Emergency Alerts (AREA) systems as appropriate for last-mile hazard information dissemination in the LIRNEasia pilot project “Evaluating Last-Mile Hazard Information Dissemination”. The presentation also presented sustainability models for WorldSpace in Bangladesh and Indonesia, while demonstrating […]