Shih, interest. However, they failed to analyze

Shih, et al. (2008) focused on both event detection and tracking. They tackled the event boundary determination issue in critical scenarios such as fire or pollution by a hazardous gas. For this purpose, they proposed a dynamic role assignment to sensor nodes so that the event can be tracked. Nevertheless, their approach is evaluated from one perspective only, the accuracy of the edge of the event of interest. However, they failed to analyze some important performance metrics such as energy consumption or delay.
2.5.3. Environmental Applications WorldWide
IoT has been applied all over the world in different areas. The examples below show how IoT is being used in different areas of the world to promote a smart environment.
Fire Detection in South Korea – According to Son, et al. (2006) Forest-Fires Surveillance System (FFSS) was developed to prevent forest fires in the South Korean Mountains and to have an early fire-alarm in real time. The system senses environment state such as temperature, humidity, smoke and determines forest-fires risk-level. This allows for the provision of an early alarm in real time when the forest-fire occurs, alerting people to extinguish forest-fires before it grows.
Flood Detection in the USA – An alert system for flood detection and prevention was deployed in the US, rainfalls, water level and weather sensors were used in that system to detect, predict and hence prevent floods. The sensors would supply information to a centralized database system in a pre-defined way (Coulson, 2006).
City-Wide Wireless Weather Sensor Network in Taipei – Chang, et al. (2010) developed the project to analyze the effectiveness of a city-wide wireless weather sensor network and Taipei Weather Science Learning Network (TWIN), in facilitating elementary and junior high students’ study of weather science. TWIN provided a distributed wireless weather sensor network throughout Taipei and promoted weather science learning activities for students. The network, composed of sixty school-based weather sensor nodes and a centralized weather data Archive server, the sixty weather sensor nodes were connected by a centralized archive server. The weather data from the area around the weather sensor node were collected every five minutes and wirelessly transferred to the TWIN server. This provided students with current weather data at specific locations in the city.


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