Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Flash floods and hurricanes are caused by the release of energy inside the oceans. Hurricanes are very sudden and may lead to heavy infrastructural damage with loss revenues associated human and animal’s fatalities. Diversified techniques have been utilized to properly investigate the flash flo...
| Main Authors: | , , , , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/79665/ http://irep.iium.edu.my/79665/1/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_complete.pdf http://irep.iium.edu.my/79665/2/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_scopus.pdf |
| _version_ | 1848788813212549120 |
|---|---|
| author | Khan, Talha Ahmed Shaikh, Faraz Ahmed Khan, Sheroz Abdul Kadir, Kushsairy Mohd Su'ud, Mazliham Shahid, Zeeshan Yahya, Muhammad |
| author_facet | Khan, Talha Ahmed Shaikh, Faraz Ahmed Khan, Sheroz Abdul Kadir, Kushsairy Mohd Su'ud, Mazliham Shahid, Zeeshan Yahya, Muhammad |
| author_sort | Khan, Talha Ahmed |
| building | IIUM Repository |
| collection | Online Access |
| description | Flash floods and hurricanes are caused by the
release of energy inside the oceans. Hurricanes are very
sudden and may lead to heavy infrastructural damage
with loss revenues associated human and animal’s
fatalities. Diversified techniques have been utilized to
properly investigate the flash floods and hurricanes before
the event. A hydro atmospheric and climatic change due to
the hurricanes leads towards the high death toll.
Approaches for the early prediction of flash floods and
hurricanes may be categorized as (a) Modeling of the
system (bathymetry), (b) Sensors and gauges-based
measurement, (c) Radar-based images, (d) Satellite images
and data, and (e) AI-based prediction. Comparative
analysis of direct real-time data from the sensors and
gauges, is more reliable compared to other techniques but
it may contain some errors and missing information which
leads towards the false alarms. Therefore, in this paper, a
novel predictive hybrid algorithm (ANN PSO) has been
applied to estimate the flash floods and hurricanes more
precisely. A suitable combination of the sensors will give
the benefit of better precision and improved accuracy
when compare to the use of a single sensor. The
combination of six process variables utilized in this paper
for the measurement and investigation of the flash flood
has been discussed. Real-time data of over forty eight (48)
hours has been collected from PIR, Ultrasonic sensor,
Temperature sensor, CO2 sensor, Rainfall module,
Pressure, and temperature sensor. ANN feed-forward
propagation is trained by using sample collected data from
the multi-modal sensing device and applied for the
classification of events while neurons are optimized by the
particle swarm optimization (PSO), taking less processing
time without requiring advanced complex computational
resources. Results have proved that proposed AI based
technique for the early identification of flash floods and
hurricanes have worked more accurate and performancewise better than the ongoing techniques. The results
include flood probabilities and prediction analysis using
proposed algorithm. |
| first_indexed | 2025-11-14T17:46:47Z |
| format | Proceeding Paper |
| id | iium-79665 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:46:47Z |
| publishDate | 2019 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-796652020-07-13T01:00:52Z http://irep.iium.edu.my/79665/ Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm Khan, Talha Ahmed Shaikh, Faraz Ahmed Khan, Sheroz Abdul Kadir, Kushsairy Mohd Su'ud, Mazliham Shahid, Zeeshan Yahya, Muhammad T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Flash floods and hurricanes are caused by the release of energy inside the oceans. Hurricanes are very sudden and may lead to heavy infrastructural damage with loss revenues associated human and animal’s fatalities. Diversified techniques have been utilized to properly investigate the flash floods and hurricanes before the event. A hydro atmospheric and climatic change due to the hurricanes leads towards the high death toll. Approaches for the early prediction of flash floods and hurricanes may be categorized as (a) Modeling of the system (bathymetry), (b) Sensors and gauges-based measurement, (c) Radar-based images, (d) Satellite images and data, and (e) AI-based prediction. Comparative analysis of direct real-time data from the sensors and gauges, is more reliable compared to other techniques but it may contain some errors and missing information which leads towards the false alarms. Therefore, in this paper, a novel predictive hybrid algorithm (ANN PSO) has been applied to estimate the flash floods and hurricanes more precisely. A suitable combination of the sensors will give the benefit of better precision and improved accuracy when compare to the use of a single sensor. The combination of six process variables utilized in this paper for the measurement and investigation of the flash flood has been discussed. Real-time data of over forty eight (48) hours has been collected from PIR, Ultrasonic sensor, Temperature sensor, CO2 sensor, Rainfall module, Pressure, and temperature sensor. ANN feed-forward propagation is trained by using sample collected data from the multi-modal sensing device and applied for the classification of events while neurons are optimized by the particle swarm optimization (PSO), taking less processing time without requiring advanced complex computational resources. Results have proved that proposed AI based technique for the early identification of flash floods and hurricanes have worked more accurate and performancewise better than the ongoing techniques. The results include flood probabilities and prediction analysis using proposed algorithm. IEEE 2019-05 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/79665/1/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_complete.pdf application/pdf en http://irep.iium.edu.my/79665/2/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_scopus.pdf Khan, Talha Ahmed and Shaikh, Faraz Ahmed and Khan, Sheroz and Abdul Kadir, Kushsairy and Mohd Su'ud, Mazliham and Shahid, Zeeshan and Yahya, Muhammad (2019) Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm. In: "2019 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2019", 20 - 23 May 2019, Auckland; New Zealand. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8826825 10.1109/I2MTC.2019.8826825 |
| spellingShingle | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Khan, Talha Ahmed Shaikh, Faraz Ahmed Khan, Sheroz Abdul Kadir, Kushsairy Mohd Su'ud, Mazliham Shahid, Zeeshan Yahya, Muhammad Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title | Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title_full | Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title_fullStr | Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title_full_unstemmed | Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title_short | Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm |
| title_sort | flash floods prediction using real time data: an implementation of ann-pso with less false alarm |
| topic | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://irep.iium.edu.my/79665/ http://irep.iium.edu.my/79665/ http://irep.iium.edu.my/79665/ http://irep.iium.edu.my/79665/1/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_complete.pdf http://irep.iium.edu.my/79665/2/79665_Flash%20Floods%20Prediction%20using%20Real%20Time_scopus.pdf |