TY - GEN
T1 - Developing a hybrid system for sand and dust storm detection using satellite imaging and WSNs
AU - Akhlaq, Muhammad
AU - Sheltami, Tarek R.
AU - Shakshuki, Elhadi M.
PY - 2012
Y1 - 2012
N2 - Sand and dust storms (SDSs) offer very serious hazards to the environment, economy and health. An early warning of the upcoming SDS would allow people to take precautionary measures. Traditionally, satellite imaging is used to detect large-scale and long-term SDSs. However, small-scale and short-term SDSs may go undetected due to the poor spatial and temporal resolution of satellites. We propose a hybrid design of sand and dust storm detection system (SDSDS) using wireless sensor network (WSN) and satellite imaging in order to detect SDSs of all types. A layered architecture of context-aware system is used. While the WSN provides real time data from the area of interest, near-real time METEOSAT MSG images are obtained from their website. An experimental prototype is developed for evaluation of the proposed system. Performance studies show that such a hybrid approach can effectively detect and predict SDSs of all types.
AB - Sand and dust storms (SDSs) offer very serious hazards to the environment, economy and health. An early warning of the upcoming SDS would allow people to take precautionary measures. Traditionally, satellite imaging is used to detect large-scale and long-term SDSs. However, small-scale and short-term SDSs may go undetected due to the poor spatial and temporal resolution of satellites. We propose a hybrid design of sand and dust storm detection system (SDSDS) using wireless sensor network (WSN) and satellite imaging in order to detect SDSs of all types. A layered architecture of context-aware system is used. While the WSN provides real time data from the area of interest, near-real time METEOSAT MSG images are obtained from their website. An experimental prototype is developed for evaluation of the proposed system. Performance studies show that such a hybrid approach can effectively detect and predict SDSs of all types.
KW - context-aware systems
KW - environmental monitoring
KW - remote sensing
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/84873365028
U2 - 10.1145/2428736.2428744
DO - 10.1145/2428736.2428744
M3 - Conference contribution
AN - SCOPUS:84873365028
SN - 9781450313063
T3 - ACM International Conference Proceeding Series
SP - 9
EP - 15
BT - 14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings
ER -