TABLE I. Summary of Related Works for Disaster Prediction and Early Signals (Acronyms Used in the Table- : , : Network Optimization Indicator Report).

Category	Reference	Target issue	Technology used	Hardware/API used	Case studies
IoT and ML	[53], 2020	Floods prediction	Convolution neural network	Hadoop MapReduce	Surat, India
	[55], 2019	Rainfall prediction	ANN and Logistic regression	LoraWan	UEM Campus
	[56], 2016	Forecast flood risk	Artificial Neural Networks	ZigBee,WSN	None
UAV	[69], 2019	Prediction	Geofencing	UAVs Base station, Flight controller	Surat, India
	[70], 2017	Assessing areas	Adhoc network as aerial mesh network	Raspberry-pi with NOIR pi camera	UEM Campus
	[71], 2019	Disaster assessment	SWIFTERS	DJI UAV, ROS library, Map server	None
	[72], 2019	Disaster assessment	Star algorithm, Tabu search, Gradient descent	Multi-UAVs	Jiuzhai valley earthquakes
ML and UAV	[20], 2019	Detecting flood areas	SVM, K-means clustering and PCA	Drones	Aerial images
Geodesics based	[73], 2010	Better prediction	Centre surrounded filters with gaussian weighted mean centers	Air-borne LiDAR	2010 Haiti earthquake
	[74], 2013	Better prediction	GEOSS and CEOS approach	Spatio-temporal infrastructure	2008 earthquake in Sichuan, China and Namibia flood plot
Satellite	[68], 2002	Water and non- water features	Landsat 7 Thematic mapper and DEM data	None	Floods in Pitt County, North Carolina
Remote sensing	[75], 2011	Develop flood hazard maps	Supervised MCL classification	RADARSAT remote sensing data, GIS data and ground data	Maghna river basin
ML and Remote sensing	[76], 2012	Classification of land cover	Random forest classifier	Landsat-5 Thematic Mapper data	Province of Granada
Data mining	[77], 2005	Tropical cyclone intensity	Apriori-base	None	Atlantic basin
Android based	[78], 2017	Alert signals	Partition based trajectory distance	JSON file	Haiti
ML and Object sensing	[79], 2011	Prediction of floods	Random forest classifier	None	Momance River — Haiti and Wenchuan town — China
	[80], 2017	Classification of land cover	Random forest classifier and SVM	None	Scopus databases
ML	[27], 2018	Sandstorm detection	CART decision tree, Naïve Bayes and Logistic Regression	None	Riyadh, Dammam, and Jeddah
	[41], 2017	Flood and landslide detection	Convolutional Neural Network	None	Japan and Thailand
	[34], 2014	Storm intensity	Symbolic Aggregate Approximation (SAX) and Artificial Neural Network (ANN)	Satellite-image data	Typhoon and Tropical cyclones
	[81], 2016	Disaster recognition	BB-SVM	ERESS	Kansai University