Correcting GPS coordinates in Apple iPhone

• Main Author: Dellytania Setiawan
• Other Authors: Annamalai Benjamin Premkumar
• Format: Final Year Project
• Language: English
• Published: 2012
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer applications::Computer-aided engineering
• Online Access: http://hdl.handle.net/10356/48451
• Institution: Nanyang Technological University

The use of smartphone is growing rapidly. It leads to high demand for useful application in people’s life. Positioning is the common feature that people use in smartphone. Many positioning applications have been developed, for example GPS assisted map navigation, location-aware social networking, etc. However, GPS coordinates obtained from the GPS receiver in the smartphone is prone to errors. The most common reason is due to obstruction of tall building that results in weak signal strength at GPS receiver. This might affect the accuracy of GPS coordinates. GPS coordinates system is estimated to have up accuracy between 4 and 40 meters in the clear view of the sky. This project suggests the use of Kalman filter to provide correction to GPS coordinates (latitude and longitude). In this report, theory of Kalman filter is provided and the details of implementation are explained. The results indicate that Kalman filter algorithm is able to produce GPS coordinates with up to 6.5 % error rate. Nowadays, people are more conscious about their health. As a result many people demand a reliable, convenient, and fast method to measure their physical health. Thus, tele-home healthcare is growing rapidly. Tele-home healthcare is a system that provides a service in healthcare without a user going to the medication institution. A heart rate monitor in real time by using smartphone is developed in this project. The algorithm used was proposed by Pelegris, Banitsas, Orbach, and Marias on 2010 [6]. The results indicate that this system is able to measure heart rate up to 5.5% error rate. Singapore is one of countries with most aging population. In 2010, the population of people above 65 years old comprises 8.9% of Singapore’s total population [14]. The rapidly aging population resulted in increasing number of people with sight-problem. Thus, visual impairment due to AREDs (age-related eye disease) is common in Singapore. Visual impairment has a big effect on the quality of health and social life. This project proposes a method to use smartphone’s camera to detect obstacles to help visually impaired population. The results indicate that this system relatively accurate and convenient.