Abstract:
A system and methods for detecting, forecasting, and alerting of flash flooding conditions. Multiple video cameras are deployed in open areas over a region, each of which monitors a visible marker affixed to a ground-level surface such as a street or road. Surface water over a marker alters the visible characteristics thereof, which are captured by the camera monitoring the marker. Camera output is processed by video analytics and machine vision techniques to analyze the changes in visibility, which are compared against pre-existing reference data related to flash flooding, to extract indicia of flash flooding. Results derived from multiple cameras over the region are correlated to detect patterns indicative of flash flooding, and appropriate reports, alerts, and warnings are issued.

Description:
BACKGROUND 
       [0001]    Flooding is an overflow of water that submerges normally-dry land, and is a common hazard in many areas in world. Floods range in geographical extent from local, impacting a neighborhood or community, to broadly regional, affecting entire river basins and multiple states. Reliable flooding forecasting can greatly assist in protecting life and property by providing advance warning. 
         [0002]    Some flooding builds slowly over a time of days to weeks, while certain floods, known as “flash floods”, can develop rapidly over a period of minutes to hours, sometimes without any visible signs of rain. Flash flooding is characterized by elevated water in open areas, non-limiting examples of which include streets and roads. Flash floods are particularly dangerous for life and property, notably transportation equipment and infrastructure. 
         [0003]    Most current weather sensing and warning systems are based on wind, humidity, rain and temperature measurements, cloud observation, Doppler radar, and satellite telemetry. Rain gauges measure only continuous precipitation at specific locations. Doppler radar works well only with large-scale weather features such as frontal systems; moreover, Doppler radar is limited to flat terrain, because radar coverage is restricted by beam blockage in mountainous areas. In addition, radar measurements can be inaccurate: in drizzle and freezing conditions, Doppler readings can seriously misrepresent the amount of precipitation. Satellite-based detection is representative only of cloud coverage, and not actual precipitation at ground level. All of these technologies require models to translate sensed data into reliable flooding forecasts. None of them give any real-time indication about the actual state of flowing water, and are thus generally ineffective for detecting and predicting flash floods. 
         [0004]    Technologies do exist for detecting flooding in real time by providing sensor information for automatic processing. However, these technologies are not based on visual camera sensing and automated analytic methods. Camera sensing coupled with analytics offers the advantage of not only automatically detecting flash flooding conditions visually for early warning, but can also be used simultaneously and subsequently to visually inspect the situation in real time. 
         [0005]    It would therefore be highly desirable and advantageous to have an effective camera-based system for accurately monitoring and predicting flash flooding conditions. This goal is met by the present invention. 
       SUMMARY 
       [0006]    Embodiments of the present invention provide monitoring, detection, and forecasting specifically of flash flooding conditions, and provide early alert of possible flash flooding in areas such as cities, critical facilities, transportation systems, and the like. 
         [0007]    According to some embodiments the present invention provides a system for monitoring and detection of flash flooding events, the system comprising:
       a plurality of visual markers for placement on open area ground surfaces;   a plurality of video cameras for obtaining captured visual images of at least one of the visual markers;   a plurality of video analytics units for analyzing the captured visual images of the visual markers, for detecting surface water covering of one or more of the visual markers; and   a logic unit, for correlating data from at least one of the video analytics units and at least one of the video cameras, for relating surface water distributions on at least one of the visual markers to at least one flash flooding condition, and for issuing at least one notification relating to the flash flooding condition.       
 
         [0012]    According to some embodiments the present invention provides a method for monitoring and detection of flash flooding events, comprising:
       placing a plurality of visual markers on open area ground surfaces;   providing a plurality of video cameras for obtaining captured visual images of at least one of the visual markers;   analyzing the captured visual images of the visual markers, for detection of surface water covering of one or more of the visual markers, by a plurality of video analytics units;   correlating data from at least one of the video analytics units and at least one of the video cameras, by a logic unit, for relating surface water distributions on the visual markers to at least one flash flooding condition; and   issuing at least one notification relating to the flash flooding condition.       
 
         [0018]    According to some embodiments the present invention provides a computer readable medium (CRM), for example in transitory or non-transitory form, that, when loaded into a memory of a computing device and executed by at least one processor of the computing device, configured to execute the steps of a computer implemented method for monitoring and detection of flash flooding events. 
         [0019]    The term “flash flooding condition” herein denotes any condition relating to a flash flood, including a condition that no flash flooding is likely, or that no flash flooding has been detected. 
         [0020]    To detect flash flooding conditions and provide early warning capabilities, embodiments of the invention use video cameras for monitoring visual markers (herein also denoted simply as “markers”) placed on open area ground surfaces which potentially may be covered with water during and/or leading up to a flash flooding event. The term “open area” herein denotes that the area is unenclosed to air and water and is exposed to outdoor weather and flooding conditions. The camera outputs are processed by video analytics and machine vision techniques to detect changes in marker visibility caused by surface water over the markers. The markers are suited for installation on open areas such as roads and streets, allowing broad geographical coverage for detection and assessment of flash flooding events. 
         [0021]    In addition, the same cameras which are used to detect and forecast potential flash flooding may also be used to visually inspect the area, to monitor and verify the severity of the flash flooding, and to visually verify if there are any people, vehicles, or other property present in the danger zone. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0022]    The subject matter disclosed may best be understood by reference to the following detailed description when read with the accompanying drawings in which: 
           [0023]      FIG. 1  conceptually illustrates an example of a marker on a road, as monitored by a video camera according to an embodiment of the present invention. 
           [0024]      FIG. 2A  illustrates a block diagram of a system according to an embodiment of the invention, for a camera monitoring a dry marker. 
           [0025]      FIG. 2B  illustrates the block diagram of the system of  FIG. 2A  according to another embodiment of the invention, for the camera monitoring the marker when covered to a certain degree by surface water. 
           [0026]      FIG. 2C  illustrates the block diagram of the system of  FIG. 2B  according to a further embodiment of the invention, for the camera monitoring the marker covered to a different degree by surface water. 
           [0027]    As illustrated in  FIG. 2B  and  FIG. 2C , in addition to distinguishing surface water covering a visual marker from a dry visual marker, an embodiment of the present invention provides a capability of distinguishing multiple different degrees, for a non-limiting example, at least one of length, depth, area, or volume measurement, of covering a marker by surface water. 
           [0028]      FIG. 3  conceptually illustrates a networked arrangement according to an embodiment of the present invention, whereby multiple cameras connect to a server for gathering data over a geographical region for analysis and presentation of reports and forecasts related to flash flooding conditions throughout the region. 
       
    
    
       [0029]    For simplicity and clarity of illustration, elements shown in the figures are not necessarily drawn to scale, and the dimensions of some elements may be exaggerated relative to other elements. In addition, reference numerals may be repeated among the figures to indicate corresponding or analogous elements. 
       DETAILED DESCRIPTION 
       [0030]      FIG. 1  conceptually illustrates a marker  101  on a road surface  103 , as monitored by a video camera  105  according to an embodiment of the present invention. In other embodiments, a marker can be placed on other surfaces in open areas. Streets and roads are often utilized because they are usually in open areas, and they generally provide good and extended locations for monitoring. According to additional embodiments of the present invention, the ground surfaces upon which markers are placed are in low-lying areas which may be prone to flash flooding. 
         [0031]    According to an embodiment of the present invention, marker  101  is a passive visual element, including, but not limited to: a painted or printed pattern, a plaque, and a sticker, which is suitable for application to a surface, such as a road or street. The term “passive” with reference to a visual marker herein denotes that the marker does not output any visual light on its own, but relies on reflection, scattering, and/or absorption of ambient light for its visual appearance According to another embodiment, marker  101  is an active visual device, incorporating light-emitting components including, but not limited to: an electrical light, and an electroluminescent panel, which may be powered by mains, and/or battery, and/or solar panel. 
         [0032]    In an embodiment of the invention, video camera  105  is a digital camera, and in another embodiment, video camera  105  is an analog camera. In a further embodiment, video camera  105  is capable of providing still pictures and images. In still another embodiment, the field of view of video camera  105  extends substantially beyond the extent of marker  101  and includes the scene surrounding marker  101 . 
         [0033]      FIG. 2A  illustrates a block diagram of a system according to an embodiment of the invention, for camera  105  monitoring marker  101  in a dry condition. A captured video image A  203 A is output from camera  105  into a video analytics unit  205 , which compares video image A  203 A against reference data  201  to analyze video image A  203 A regarding the relevance thereof to possible flash flooding. In particular, video analytics unit  205  determines that marker  101  is in a dry condition, and then issues a dry marker report A  209 A for subsequent data processing (as disclosed below). 
         [0034]      FIG. 2B  illustrates the system of  FIG. 2A , for camera  105  monitoring of marker  101  in a wet condition, when marker  101  is covered to a certain degree by surface water  207 B. A captured video image B  203 B is output from camera  105  into video analytics unit  205 , which compares video image B  203 B against reference data  201  to analyze video image B  203 B regarding the relevance thereof to possible flash flooding. In particular, video analytics unit  205  determines that marker  101  is covered to a certain degree by surface water  207 B, and then issues a wet marker report B  209 B for subsequent data processing (as disclosed below). 
         [0035]      FIG. 2C  illustrates the system of  FIG. 2A , for camera  105  monitoring of marker  101  in a wet condition, when marker  101  is covered to a different degree by surface water  207 C. A captured video image C  203 C is output from camera  105  into video analytics unit  205 , which compares video image C  203 C against reference data  201  to analyze video image C  203 C regarding the relevance thereof to possible flash flooding. In particular, video analytics unit  205  determines that marker  101  is covered to a different degree by surface water  207 C, and then issues a wet marker report C  209 C for subsequent data processing (as disclosed below). 
         [0036]    In another embodiment of the invention, video analytics unit  205  also makes captured video images, (e.g., video image A  203 A, video image B  203 B, and video image C  203 C) available for subsequent data processing. 
         [0037]    In summary, the video stream from camera  105  is processed by video analytics unit  205 , which applies machine vision and/or image processing techniques to detect when marker  101  is dry ( FIG. 2A ), or is covered to varying degrees by surface water (surface water  207 B in  FIG. 2B , surface water  207 C in  FIG. 2C ) during or leading up to an incident of flash flooding. 
         [0038]      FIG. 3  conceptually illustrates a networked arrangement according to an embodiment of the present invention, whereby multiple visual markers  101 A,  101 B, . . . ,  101 C are respectively monitored by multiple cameras  105 A,  105 B, . . . ,  105 C respectively having multiple video analytics units  205 A,  205 B, . . . ,  205 C which connect via a network  301  to a server  303  for gathering data over a geographical region for analysis and presentation of reports and forecasts related to flash flooding conditions throughout the region. 
         [0039]    In various embodiments of the invention, server  303  performs as a logic unit which correlates data from multiple video analytics units  205 A,  205 B, . . . ,  205 C and/or multiple cameras  105 A,  105 B, . . . ,  105 C respectively monitoring visual markers  101 A,  101 B, . . . ,  101 C, for relating surface water distributions thereon to flash flooding conditions, and for issuing notifications relating to the flash flooding conditions. A notification includes, but is not limited to: a report of a flash flooding condition, a report of an absence of a flash flooding condition, a forecast of a flash flooding condition, and an alert (or warning) of a flash flooding condition, as disclosed below. 
         [0040]    In an embodiment of the present invention, one or more weather stations, such as a weather station  305 A, a weather station  305 B, and a weather station  305 C, provide additional detection of weather conditions for correlation with video analytics, and contribute to reference data  201  ( FIGS. 2A, 2B, and 2C ). 
         [0041]    According to further embodiments of the invention, server  303  receives and correlates additional data to improve the quality of flash flooding event detection—such as by increasing the confidence level of positive flash flooding event detection by reducing or eliminating false positive and false negative flash flooding detection. In a related embodiment, each detection from a video analytics unit is correlated with additional detections, such as by the same video analytics unit at a different time, or from nearby video analytics units in different places, such as neighboring areas. In other related embodiments, a detection from a video analytics unit is correlated with information including, but not limited to: data from flooding conductivity sensors or rain gauge sensors of a weather station; calibration data to correlate visual analytic results with direct measurements of surface water on a marker; weather condition data; and historical data from previous flooding events. 
         [0042]    According to further embodiments of the invention, cross correlation between camera sensor visual marker detections are performed by a logic unit utilizing techniques including, but not limited to: rule engines; complex event processing (CEP); data fusion with neighboring camera sensors; and machine learning. 
         [0043]    In certain embodiments, video analytics units include dedicated hardware devices or components. In other embodiments, video analytics units are implemented in software, and software. In various related embodiments, video analytics units are deployed in or near the video cameras; in other related embodiments, video analytics units are embedded within server  303 , which directly receives the video stream from the cameras over network  301 . 
         [0044]    According to an embodiment of the invention, flash flooding-related notifications, include, but are not limited to: reporting, advisory bulletins, analyses, updates, and warnings. In a related embodiment, these are distributed to subscribers via user-edge equipment, such as a personal computer/workstation  311 , a tablet computer  313 , and a telephone  315 , such as by a web client or other facility. In another related embodiment, distribution is performed via messaging techniques including, but not limited to: API calls, SMS, MMS, e-mail, and other messaging services. 
         [0045]    In further embodiments of the present invention, visual media content is sent with a flooding detection alert. Visual media content includes, but is not limited to: live video and/or audio streaming from the detected event; short recorded video clips; still images; and audio clips. Visual media content can assist first responders or the general public in validating the event, assessing the situation, and deciding on appropriate responses.