Patent Publication Number: US-2023133873-A1

Title: Remote monitoring system, remote monitoring apparatus, and method

Description:
TECHNICAL FIELD 
     The present disclosure relates to a remote monitoring system, a remote monitoring apparatus, and a method. 
     BACKGROUND ART 
     A system that monitors a target through a camera image acquired from a vehicle is known. The camera image is taken by a camera disposed in the vehicle. As a related art, Patent Literature 1 discloses a monitoring system designed to monitor a target to be primarily monitored. The monitoring system described in Patent Literature 1 includes a central monitoring apparatus and a monitoring terminal apparatus. The central monitoring apparatus is installed at authorities such as a police station or a fire station. The monitoring terminal apparatus is disposed in a mobile object such as a passenger vehicle. The monitoring system is used by the authorities such as a police station or a fire station to centrally monitor a town for public safety. 
     The central monitoring apparatus transmits a primary monitor command to the monitoring terminal apparatus. The primary monitor command contains primary monitor target information for designating a target to be primarily monitored and a position to be primarily monitored. The monitoring terminal apparatus determines a time at which the passenger vehicle is to be present at the position to be primarily monitored, based on a current position of the passenger vehicle. At a time when the passenger vehicle is present at or in a vicinity of the position to be primarily monitored, the monitoring terminal apparatus acquires image information in which the target to be primarily monitored is enlarged and transmits the image information to the central monitoring apparatus. In Patent Literature 1, the central monitoring apparatus is able to acquire the image information, in which the target to be primarily monitored is enlarged, from the vehicle traveling at or in the vicinity of the position to be primarily monitored out of a plurality of passenger vehicles traveling randomly. Thus, an observer can monitor even details of the target to be primarily monitored without visiting a site of the target. 
     As another related art, Patent Literature 2 discloses a remote video output system designed to remotely control an autonomous vehicle. In Patent Literature 2, the autonomous vehicle transmits visual data taken by an in-vehicle camera to a remote-control center through a network. The autonomous vehicle is equipped with a camera filming a frontward area, a camera filming a rearward area, a camera filming a right-side area, and a camera filming a left-side area of the autonomous vehicle and transmits visual data taken by each of the cameras to the remote-control center. 
     The autonomous vehicle calculates a degree of danger using a danger prediction algorithm, and based on the calculated degree of danger, controls a resolution and a frame rate of the visual data to be transmitted to the remote-control center. When the degree of danger is less than or equal to a threshold value, the autonomous vehicle transmits visual data with a relatively low resolution or a low frame rate to the remote-control center. When the degree of danger is greater than a threshold value, the autonomous vehicle transmits visual data with a relatively high resolution or a high frame rate to the remote control-center. 
     An observer on a remote-control center side remotely monitors the autonomous vehicle by observing a relatively low-resolution image usually. In response to an increase in the degree of danger concerning the autonomous vehicle, the observer is able to remotely monitor the autonomous vehicle through a relatively high-resolution image. In Patent Literature 2, the observer can predict danger before the autonomous vehicle does and can request an image of high image quality from the autonomous vehicle. When the observer performs an action to request an image of high image quality, the autonomous vehicle transmits visual data of high image quality to the remote-control center. 
     As another related art, Patent Literature 3 discloses a vehicular communication apparatus used for communication between a vehicle and a control center. In Patent Literature 3, the control center controls the apparatus to assist the autonomous vehicle in traveling. The vehicle has cameras to photograph (or film) areas on front, rear, right, and left sides of the vehicle as well as an inside of the vehicle. The vehicular communication apparatus transmits visual data taken by the cameras on the front, rear, right, and left sides as well as the camera inside the vehicle to the control center. 
     The vehicular communication apparatus identifies a situation in which the vehicle is placed using information from the cameras. The vehicular communication apparatus, based on the identified situation, determines priorities given to the front-, rear-, right-, and left-side cameras as well as the in-vehicle camera. In accordance with the determined priorities, the vehicular communication apparatus controls the resolution and frame rate of visual data taken by each camera. If a high priority is given to the camera photographing (or filming) the area on the front side of the vehicle, for example, the vehicular communication apparatus transmits visual data taken by the camera, which photographs (or films) the frontward area of the vehicle, in high resolution and at a high frame rate to the control center. 
     CITATION LIST 
     Patent Literatures 
     
         
         Patent Literature 1: International Patent Publication No. WO2013/094405 
         Patent Literature 2: International Patent Publication No. WO2018/155159 
         Patent Literature 3: Japanese Unexamined Patent Application Publication No. 2020-3934 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     The monitoring system described in Patent Literature 1 acquires the image information, in which the target to be primarily monitored is enlarged, from the vehicle traveling at a place where the predesignated target to be primarily monitored is present. The observer, by observing the image information, is able to monitor the designated target to be primarily monitored, i.e., a structure such as a specific facility, a shop, or an event site and a subject such as a human, an animal, or an object being present at such a place. Unfortunately, the monitoring system described in Patent Literature 1, which is used to centrally monitor a town for public safety, is not intended to monitor a target such as a situation in which the vehicle is driven. The monitoring system described in Patent Literature 1 cannot be adapted to a purpose of grasping a traveling situation that changes while the vehicle is traveling. 
     The remote video output system described in Patent Literature 2 causes visual data of high image quality to be transmitted from the autonomous vehicle to the remote-control center in response to an increase in the degree of danger concerning the autonomous vehicle or when the observer requests such a video. Unfortunately, in Patent Literature 2, low image quality or high image quality is selected for the overall image. In Patent Literature 2, for the high degree of danger, the overall image is rendered in high image quality. This causes a problem in such a way that a network band used for transmission of the visual data gets congested. In Patent Literature 2, a human (the observer) on the remote-control center side predicts danger and thus visual data of high image quality is requested according to human judgment. As a result, the observer is not able to monitor the target through visual data of high image quality for danger that the observer cannot notice. 
     The vehicular communication apparatus described in Patent Literature 3 is able to transmit visual data taken by each camera to the control center, in which image quality of the visual data is adjusted in response to a situation in which the vehicle is placed. Unfortunately, in Patent Literature 3, the image quality is adjusted on the vehicle side, and the control center simply receives visual data whose image quality has been adjusted. Potential danger may be hidden in an image of low image quality that is not given precedence. In this case, it is possible, for example, that the control center is unable to accurately predict danger due to low image quality. 
     In view of the above-described circumstances, an object of the present disclosure is to provide a remote monitoring system, a remote monitoring apparatus, a remote monitoring method, and an image acquisition method that each enable remote acquisition of an image from a vehicle when prediction of an event such as prediction of danger is performed on a center side such that the event can be predicted through the image with increased accuracy. 
     Solution to Problem 
     In order to achieve the above-described object, the present disclosure provides a remote monitoring system including: a vehicle having an imaging device; and a remote monitoring apparatus connected to the vehicle through a network, in which the remote monitoring apparatus includes: an image reception means for receiving an image taken by the imaging device through the network; an event prediction means for predicting an event based on the image received by the image reception means; and an important area identification means for identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event, and the vehicle includes an image adjustment means for adjusting quality concerning the identified important area in the image. 
     The present disclosure provides a remote monitoring apparatus including: an image reception means for receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; an event prediction means for predicting an event based on the image received by the image reception means; and an important area identification means for identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event, in which the image reception means receives, from the vehicle, the image, whose quality concerning the identified important area in the image has been adjusted. 
     The present disclosure provides a remote monitoring method including: receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; predicting an event based on the received image; identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event; and adjusting quality concerning the identified important area in the image. 
     The present disclosure provides an image acquisition method including: receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; predicting an event based on the received image; identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event; and receiving the image from the vehicle, quality concerning the identified important area in the image having been adjusted. 
     Advantageous Effects of Invention 
     A remote monitoring system, a remote monitoring apparatus, a remote monitoring method, and an image acquisition method according to the present disclosure each enable acquisition of an image from a vehicle when prediction of an event such as prediction of danger is performed on a center side such that the event can be predicted through the image with increased accuracy. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a schematic block diagram showing a remote monitoring system according to the present disclosure. 
         FIG.  2    is a schematic flowchart showing an operation procedure performed by a remote monitoring system according to the present disclosure. 
         FIG.  3    is a block diagram showing a remote monitoring system according to a first example embodiment of the present disclosure. 
         FIG.  4    is a block diagram showing an example of a configuration of a vehicle. 
         FIG.  5    is a block diagram showing an example of a configuration of a remote monitoring apparatus. 
         FIG.  6    is a flowchart showing an operation procedure performed by a remote monitoring system. 
         FIG.  7    is a drawing showing an example of an image received by an image reception unit before quality adjustment. 
         FIG.  8    is a drawing showing an example of an image received by an image reception unit after quality adjustment. 
         FIG.  9    is a block diagram showing a remote monitoring system according to a second example embodiment of the present disclosure. 
         FIG.  10    is a block diagram showing an example of a configuration of a computer apparatus. 
         FIG.  11    is a block diagram showing a hardware configuration of a microprocessor unit. 
     
    
    
     EXAMPLE EMBODIMENT 
     Prior to describing an example embodiment according to the present disclosure, an outline of the present disclosure will be described.  FIG.  1    schematically shows a remote monitoring system according to the present disclosure.  FIG.  2    schematically shows an operation procedure performed by a remote system. A remote monitoring system  10  includes a remote monitoring apparatus  11  and a vehicle  15 . An imaging device is disposed in the vehicle. The remote monitoring apparatus  11  is connected to the vehicle  15  through a network  20 . The remote monitoring apparatus  11  includes an image reception means  12 , an event prediction means  13 , and an important area identification means  14 . The vehicle  15  includes an image adjustment means  16 . 
     For instance, in the remote monitoring system  10 , the vehicle  15  is constructed as a mobile object such as an automobile, a bus, or a train. The vehicle may be an autonomous vehicle configured so as to be able to perform automated driving, may be a remotely driven vehicle for which remote driving is controllable, or may be an ordinary vehicle driven by a driver. The remote monitoring apparatus  11  is configured, for example, as an apparatus to remotely monitor the vehicle  15 . The important area identification means  14  constitutes, for example, a distribution control apparatus to control distribution of an image from the vehicle. The distribution control apparatus may be disposed in the remote monitoring apparatus or may be disposed in the vehicle. 
     The vehicle  15  transmits an image taken by the imaging device to the image reception means  12  through the network. The image reception means  12  receives the image from the vehicle  15 . The event prediction means  13  predicts an event based on the image received by the image reception means  12 . 
     Based on an event result predicted by the event prediction means  13 , the important area identification means  14  identifies an area related to the predicted event as an important area in the image. The image adjustment means  16  adjusts quality of the image such that the important area identified by the important area identification means  14  is clearer than another area in the image. The image reception means  12  receives the image whose quality has been adjusted through the network. 
       FIG.  2    schematically shows an operation procedure performed by a remote system. The image reception means  12  receives an image taken by the imaging device from the vehicle  15  through the network  30  (Step A1). The event prediction means  13  predicts an event based on the received image (Step A2). Based on a result of the predicted event, the important area identification means  14  identifies an area related to the predicted event as an important area in the image (Step A3). The image adjustment means  16  adjusts quality concerning the identified important area in the image (Step A4). 
     In the present disclosure, the important area identification means  14  identifies an area related to the event, which is predicted by the event prediction means  13 , as an important area. The image adjustment means  16  adjusts, for example, quality of the image such that the important area is clearer than the other area. In this way, the image reception means  12  is able to receive the image whose quality has been adjusted to render the important area clear, and the event prediction means  13  is able to predict an event from such an image. Thus, in the present disclosure, when prediction of an event such as prediction of danger is performed at a place remote from a vehicle, the system enables acquisition of an image from the vehicle such that the event can be predicted through the image with increased accuracy. 
     With reference to the drawings, an example embodiment according to the present disclosure will be described hereinafter in detail.  FIG.  3    shows a remote monitoring system according to a first example embodiment of the present disclosure. A remote monitoring system  100  includes a remote monitoring apparatus  101  and a vehicle  200 . In the remote monitoring system  100 , the remote monitoring apparatus  101  and the vehicle  200  communicate with each other through a network  102 . The network  102  may be, for example, a network in conformity with communication line standards such as long term evolution (LTE) or may include a radio communication network such as Wi-Fi (Registered Trademark) or a fifth-generation mobile communication system. The remote monitoring system  100  corresponds to the remote monitoring system  10  shown in  FIG.  1   . The remote monitoring apparatus  101  corresponds to the remote monitoring apparatus  11  shown in  FIG.  1   . The vehicle  200  corresponds to the vehicle  15  shown in  FIG.  1   . The network  102  corresponds to the network  20  shown in  FIG.  1   . 
       FIG.  4    shows an example of a configuration of the vehicle  200 . The vehicle  200  includes a communication apparatus  201  and a plurality of cameras  300 . The communication apparatus  201  is configured as an apparatus that provides radio communication between the vehicle  200  and the network  102  (refer to  FIG.  3   ). The communication apparatus  201  includes a wireless communication antenna, a transmitter, and a receiver. The communication apparatus  201  includes a processor, memory, an input/output unit, and a bus for connecting these parts. The communication apparatus  201  includes a distribution image adjustment unit  211 , an image transmission unit  212 , and an important area reception unit  213  as logical components. Functions of the distribution image adjustment unit  211 , the image transmission unit  212 , and the important area reception unit  213  are implemented, for example, by having a microcomputer execute a control program stored in the memory. 
     Each of the cameras  300  outputs visual data (an image) to the communication apparatus  201 . Each camera  300  photographs (or films), for example, an area on a front, rear, right, or left side of the vehicle. The communication apparatus  201  transmits an image taken by the camera  300  to the remote monitoring apparatus  101  through the network  102 . In  FIG.  4   , the four cameras  300  are illustrated. However, the number of the cameras  300  is not limited to four. The vehicle  200  may include at least one camera  300 . In this example embodiment, a communications band of the network  102  is insufficient for transmission of all images taken by the cameras  300  in high quality from the vehicle  200  to the remote monitoring apparatus  101 . 
     The distribution image adjustment unit  211  adjusts the quality of images taken by the plurality of the cameras  300 . Adjusting the image quality described here involves, for example, adjusting at least part of a compression ratio, resolution, a frame rate, or other properties of the image taken by each camera  300  and thereby adjusting an amount of data of the image to be transmitted to the remote monitoring apparatus  101  through the network  102 . It is conceivable that the distribution image adjustment unit  211 , for example, improves the quality of an important area and reduces the quality of an area other than the important area for quality adjustment. Improving the quality is, for example, action such as increasing the resolution (clearness) of the image and increasing the number of frames. 
     The important area reception unit  213  receives information about the important area (hereinafter also referred to as important area information) from the remote monitoring apparatus  101  through the network  102 . Identification of the important area by the remote monitoring apparatus  101  will be described later. 
     When receiving the important area information, the important area reception unit  213  informs the distribution image adjustment unit  211  of a position of the important area. If the distribution image adjustment unit  211  is not informed about the important area position from the important area reception unit  213 , the distribution image adjustment unit  211  adjusts the overall image taken by each camera  300  to an image of low image quality. The distribution image adjustment unit  211  may estimate, for example, a communications band from a pattern of traffic in a radio communication network and determine the quality of each image according to a result of the estimated band. 
     When the distribution image adjustment unit  211  is informed about the important area position from the important area reception unit  213 , the distribution image adjustment unit  211  adjusts the quality of the image taken by each camera  300  such that the important area is clearer than another area in the image. In other words, the distribution image adjustment unit  211  adjusts the image such that the quality of the important area is higher than the quality of the other area. The image transmission unit  212  transmits the image taken by each camera  300 , quality of which has been adjusted by the distribution image adjustment unit  211 , to the remote monitoring apparatus  101  through the network  102 . The distribution image adjustment unit  211  corresponds to the image adjustment means  16  shown in  FIG.  1   . 
     In this example embodiment, the image transmitted from the vehicle  200  to the remote monitoring apparatus  101  is a two-dimensional camera image. However, the image is not particularly limited to the two-dimensional image, with proviso that the image enables grasping of a situation surrounding the vehicle. The image transmitted from the vehicle  200  to the remote monitoring apparatus  101 , for example, may include a point cloud image generated using Light Detection and Ranging (LiDAR) or other technology. 
       FIG.  5    shows an example of a configuration of the remote monitoring apparatus  101 . The remote monitoring apparatus  101  includes an image reception unit  111 , a danger prediction unit  112 , a monitoring screen display unit  114 , and a distribution controller  115 . The image reception unit  111  receives an image transmitted from the vehicle  200  through the network  102  (refer to  FIG.  3   ). The image reception unit  111  corresponds to the image reception means  12  shown in  FIG.  1   . 
     The danger prediction unit  112  predicts whether an event related to danger (hereinafter also refer to as a dangerous event) occurs through each image received by the image reception unit  111 . The danger prediction unit  112  includes an object detection unit (an object detection means)  113 . The object detection unit  113  detects an object contained in the image. The object detection unit  113  detects, from the image, a position and a type of an object or another target that is related to a dangerous event to be predicted by the danger prediction unit  112 . The object detection unit  113  is not necessarily included in the danger prediction unit  112 . The danger prediction unit  112  and the object detection unit  113  may be disposed separately from each other. 
     The danger prediction unit  112 , based on the position and the type of the detected object or the like, predicts the occurrence of a dangerous event. The dangerous event, for example, may include a pedestrian running out into a road, the approach of another vehicle, and a collision with a fallen object on a road. The danger prediction unit  112  predicts the occurrence of a dangerous event from the image, for example, using a known danger prediction algorithm. The danger prediction unit  112  outputs information such as content of the dangerous event and the position of an object to the monitoring screen display unit  114  and the distribution controller  115 . The danger prediction unit  112  corresponds to the event prediction means  13  shown in  FIG.  1   . 
     The distribution controller (distribution control apparatus)  115  controls a distribution of the image to be transmitted from the vehicle  200  to the remote monitoring apparatus  101 . The distribution controller  115  includes an important area identification unit  116  and an important area informing unit  117 . Based on a dangerous event result predicted by the danger prediction unit  112 , the important area identification unit  116  identifies an area related to the predicted event as an important area in the image transmitted from the vehicle. The important area identification unit  116  corresponds to the important area identification means  14  shown in  FIG.  1   . 
     The important area identification unit  116  may identify an important area based on the position of the object detected with the object detection unit  113 . The important area identification unit  116  identifies, for example, an area bearing a predetermined relation to the position of the detected object as an important area. Alternatively, the important area identification unit  116 , when the occurrence of a dangerous event is predicted by the danger prediction unit  112 , may estimate a direction in which the object is shifting and predict a destination to which the object is shifting. The destination, which the object is shifting to, can be estimated, for example, from a situation of a past dangerous event. The important area identification unit  116  estimates the destination, which the object is shifting to, on a time-series basis, for example. Alternatively, the important area identification unit  116  may estimate the destination, which the object is shifting to, by a statistical technique. The important area identification unit  116  may identify an area associated with the predicted destination as an important area. 
     The important area informing unit  117  informs the important area reception unit  213  (refer to  FIG.  4   ) in the vehicle  200  of information about the important area, which is identified by the important area identification unit  116 , through the network  102 . The important area identification unit  116  may identify the important area in a plurality of images. The important area identification unit  116  may identify a plurality of the important areas in one image. The important area information includes information for identifying an image (camera) and information about the number and positions of important areas in the image, for example. 
     The monitoring screen display unit (image display means)  114  displays the image received by the image reception unit  111 . The monitoring screen display unit  114  displays, for example, images of the areas on the front, rear, right, and left sides of the vehicle, which are taken by the cameras  300  (refer to  FIG.  4   ), on a display screen. An observer, by monitoring the display screen, monitors whether or not there is a hindrance to traveling of the vehicle  200 . 
     When the danger prediction unit  112  predicts the occurrence of a dangerous event, an important area is identified by the important area identification unit  116 , and the image reception unit  111  receives an image in which the important area is rendered clear from the vehicle  200 . In this case, by monitoring the image in which the important area related to the predicted dangerous event is rendered clear, the observer is able to monitor whether or not there is a hindrance to traveling of the vehicle. The monitoring screen display unit  114 , when the danger prediction unit  112  predicts the occurrence of a dangerous event, may help invite the observer&#39;s attention to the event. For instance, the monitoring screen display unit  114  may display the predicted dangerous event result superimposing on the image received from the vehicle to inform the observer about which part in the image the potential danger is predicted. 
     The remote monitoring apparatus  101  may remotely control traveling of the vehicle as well as remotely monitor the vehicle. The remote monitoring apparatus  101  includes, for example, a remote controller, and the remote controller may transmit a remote control command to the vehicle to cause the vehicle to start turning right or come to an emergency stop, for example. The vehicle, when receiving the remote control command, operates in accordance with the command. Alternatively, the remote monitoring apparatus  101  may have a facility such as a steering wheel, an accelerator pedal, and a brake pedal to remotely steer the vehicle. The remote controller may remotely drive the vehicle in response to control put to a remote driving vehicle. 
     Next, an operation procedure performed by the remote monitoring system  100  will be described.  FIG.  6    shows an operation procedure (a remote monitoring method) performed by the remote monitoring system  100 . Each vehicle  200  transmits images taken by the cameras  300  (refer to  FIG.  4   ) to the remote monitoring apparatus  101  through the network  102 . The image reception unit  111  of the remote monitoring apparatus  101  receives an image from the vehicle  200  (Step B1). The monitoring screen display unit  114  displays the received image on a monitoring screen (Step B2). 
     The danger prediction unit  112  predicts whether a dangerous event occurs through each of the received images (Step B3). For instance, in the step B3, the object detection unit  113  detects an object in each image. The danger prediction unit  112 , based on a result of object detection, predicts whether a dangerous event occurs. The important area identification unit  116  determines whether or not the occurrence of a dangerous event is predicted by the danger prediction unit  112  (Step B4). When in the step B4, the identification unit determines that the occurrence of a dangerous event is not predicted, the process returns to the step B1. 
     When the occurrence of a dangerous event is predicted in the step B4, the important area identification unit  116  identifies an important area (Step B5). In the step B5, the important area identification unit  116  identifies, for example, an area in which a predetermined object such as a human is detected, as an important area. Alternatively, the important area identification unit  116  may predict a destination to which the detected object is shifting and identify an area for the destination as an important area. The important area informing unit  117  transmits information about the identified important area to the vehicle  200  through the network  102  (Step B6). For instance, the important area informing unit  117  transmits information indicating a position of the important area to the vehicle  200  through the network  102 . 
     The important area reception unit  213  (refer to  FIG.  4   ) of the vehicle  200  receives information indicating the position of the important area from the remote monitoring apparatus  101 . The distribution image adjustment unit  211 , based on the information received by the important area reception unit  213 , adjusts the quality of each image acquired from each camera  300  such that the important area is clearer than the other area in the image (Step B7). The image transmission unit  212  transmits the image, quality of which has been adjusted, to the remote monitoring apparatus  101  through the network  102 . After that, the process returns to the step B  1 , and the image reception unit  111  receives the image whose quality has been adjusted from the vehicle  200 . 
     The remote monitoring method described above includes an image acquisition method and a distribution control method. The image acquisition method is equivalent to the steps B1, B3, B5, and B6. The distribution control method is equivalent to the steps B5 and B6. 
       FIG.  7    shows an example of an image received by the image reception unit  111  before quality adjustment. Before information indicating the position of the important area is received, the distribution image adjustment unit  211  of the vehicle  200  transmits each image as an image in low resolution and at a low frame rate to the remote monitoring apparatus  101 . The monitoring screen display unit  114  displays the image in low resolution and at a low frame rate, which is received by the image reception unit  111 , on the monitoring screen. The observer monitors the image displayed by the monitoring screen display unit  114 . 
     For instance, the danger prediction unit  112  predicts the occurrence of a dangerous event in an area indicated by an area R in  FIG.  7   . In this case, the important area identification unit  116  identifies the area R as an important area. The important area informing unit  117  transmits information about the position (coordinates) of the area R to the vehicle  200 . 
       FIG.  8    shows an example of an image received by the image reception unit  111  after quality adjustment. The distribution image adjustment unit  211 , as shown in  FIG.  8   , adjusts the quality of the image to render the area of the area R clear. The distribution image adjustment unit  211  renders the area of the area R clear, for example, by adjusting at least one of the compression ratio, the resolution, or the frame rate of the area of the area R to a level higher than that of another area. In the remote monitoring apparatus  101 , the image reception unit  111  receives the image in which the area of the area R is rendered clear. In this case, the danger prediction unit  112  is able to predict whether a dangerous event occurs through the image in which the area of the area R is rendered clear. The observer is able to monitor the vehicle  200  through the image in which the area of the area R is rendered clear. 
     In this example embodiment, the danger prediction unit  112  predicts, for example, whether a traffic violation occurs. The object detection unit  113  detects, for example, a traffic stop sign or a stop line. The important area identification unit  116  identifies an area for the stop line as an important area in the image. The important area informing unit  117  informs the vehicle  200  of a position of the stop line area. The distribution image adjustment unit  211  of the vehicle  200  transmits an image in which the stop line area is rendered clear to the remote monitoring apparatus  101 . In this case, the observer is able to check whether or not a traffic violation occurs through the image in which the stop line area is rendered clear. 
     The object detection unit  113  may detect a traffic sign indicating no passing or no straddling. In this case, the important area identification unit  116  identifies, for example, an area for a centerline as an important area. The important area informing unit  117  informs the vehicle  200  of a position of the centerline area. The distribution image adjustment unit  211  of the vehicle  200  transmits an image in which the centerline area is rendered clear to the remote monitoring apparatus  101 . In this case, the observer is able to check whether or not a traffic violation occurs through the image in which the centerline area is rendered clear. 
     The danger prediction unit  112  may predict, for example, occurrence of a traffic obstruction. The object detection unit  113  detects, for example, an obstacle such as a fallen object on a road, a construction site, or an accident site. The important area identification unit  116  identifies an area for the obstacle or the like as an important area in the image. The important area informing unit  117  informs the vehicle  200  of a position of the obstacle or the like area. The distribution image adjustment unit  211  of the vehicle  200  transmits an image in which the obstacle or the like area is rendered clear to the remote monitoring apparatus  101 . In this case, the observer is able to check whether or not a traffic obstruction occurs through the image in which the obstacle area is rendered clear. 
     In several examples described above, the remote monitoring apparatus  101  may determine the occurrence of an event such as a traffic obstruction using a determination unit (not shown). The determination unit determines whether or not a traffic obstruction has occurred by performing an examination such as an image analysis on an image that is transmitted from the vehicle  200  after the important area in the image is rendered clear. When the occurrence of the event such as a traffic obstruction is determined, the determination unit may inform the observer of the occurrence of the event such as traffic injury. 
     In this example embodiment, the important area identification unit  116  identifies an important area based on a dangerous event result predicted by the danger prediction unit  112 . The important area informing unit  117  informs the vehicle  200  of a position of the important area. In the vehicle  200 , the distribution image adjustment unit  211  adjusts the quality of an image to render the important area in the image clear, and the image transmission unit  212  transmits the image, quality of which has been adjusted, to the remote monitoring apparatus  101 . In this way, the remote monitoring apparatus  101  is able to acquire the image from the vehicle  200  such that the event can be predicted through the image with increased accuracy. To put it another way, when prediction of an event such as prediction of danger is performed at the remote monitoring apparatus  101 , the vehicle  200  is able to distribute the image to the remote monitoring apparatus  101  such that the event can be predicted through the image with increased accuracy. The remote monitoring apparatus  101  is able to predict danger based on such an image with increased accuracy. 
     Next, a second example embodiment of the present disclosure will be described.  FIG.  9    shows a remote monitoring system according to the second example embodiment of the present disclosure. A remote monitoring system  100   a  according to this example embodiment includes a remote monitoring apparatus  101   a  and a communication apparatus  201   a  that is disposed in a vehicle. The remote monitoring apparatus  101   a  has a configuration such that in the remote monitoring apparatus  101  shown in  FIG.  5   , the distribution controller  115  is replaced by a result informing unit  118 . The communication apparatus  201   a  has a configuration such that in the communication apparatus  201  shown in  FIG.  4   , the important area reception unit  213  is replaced by a distribution controller  214 . Other points may be similar to those in the first example embodiment. 
     In this example embodiment, the danger prediction unit  112  outputs a predicted result including content of a dangerous event and a position of an object to the result informing unit  118 . The result informing unit  118  transmits the predicted result to the communication apparatus  201   a  on a vehicle side through a network  102  (refer to  FIG.  3   ). In the communication apparatus  201   a , the distribution controller (distribution control apparatus)  214  receives the result predicted by the danger prediction unit  112 . The distribution controller  214  includes an important area identification unit  215  and an important area informing unit  216 . The important area identification unit  215 , based on the result predicted by the danger prediction unit  112 , identifies an important area in an image. Operation of the important area identification unit  215  may be similar to operation of the important area identification unit  116  described in the first example embodiment. 
     The important area informing unit  216  informs the distribution image adjustment unit  211  of a position of the identified important area. The distribution image adjustment unit  211  adjusts the quality of an image to render the important area clear in the image. The image transmission unit  212  transmits the image whose quality has been adjusted to the remote monitoring apparatus  101  through the network. 
     In this example embodiment, the distribution controller  214  disposed in the vehicle  200  identifies the important area. In this case as well, the communication apparatus  201   a  on the vehicle side is able to distribute the image to the remote monitoring apparatus  101  such that the event can be predicted by the remote monitoring apparatus  101   a  through the image with increased accuracy. The remote monitoring apparatus  101   a  is able to acquire the image from the communication apparatus  201   a  on the vehicle side such that the event can be predicted through the image with increased accuracy. Thus, in this example embodiment, in a similar way to the first example embodiment, the remote monitoring apparatus  101   a  is able to predict danger with increased accuracy. 
     In the present disclosure, the remote monitoring apparatus  101  can be configured as a computer apparatus (a server apparatus).  FIG.  10    shows an example of a configuration of a computer apparatus that can be used as the remote monitoring apparatus  101 . A computer apparatus  500  includes a control unit (CPU: central processing unit)  510 , a storage unit  520 , a read only memory (ROM)  530 , a random access memory (RAM)  540 , a communication interface (IF: interface)  550 , and a user interface  560 . 
     The communication interface  550  is an interface for connecting the computer apparatus  500  to a communication network through wired communication means, wireless communication means, or the like. The user interface  560  includes, for example, a display unit such as a display. Further, the user interface  560  includes an input unit such as a keyboard, a mouse, and a touch panel. 
     The storage unit  520  is an auxiliary storage device that can hold various types of data. The storage unit  520  does not necessarily have to be a part of the computer apparatus  500 , but may be an external storage device, or a cloud storage connected to the computer apparatus  500  through a network. 
     The ROM  530  is a non-volatile storage device. For example, a semiconductor storage device such as a flash memory having a relatively small capacity can be used for the ROM  530 . A program(s) that is executed by the CPU  510  may be stored in the storage unit  520  or the ROM  530 . The storage unit  520  or the ROM  530  stores, for example, various programs for implementing the function of each unit in the remote monitoring apparatus  101 . 
     The RAM  540  is a volatile storage device. As the RAM  540 , various types of semiconductor memory apparatuses such as a dynamic random access memory (DRAM) or a static random access memory (SRAM) can be used. The RAM  540  can be used as an internal buffer for temporarily storing data and the like. The CPU  510  deploys (i.e., loads) a program stored in the storage unit  520  or the ROM  530  in the RAM  540 , and executes the deployed (i.e., loaded) program. The function of each unit in the remote monitoring apparatus  101  can be implemented by having the CPU  510  execute a program. 
     In the present disclosure, the distribution controller  214  included in the communication apparatus  201   a  can be configured as an apparatus such as a microprocessor unit.  FIG.  11    shows a hardware configuration of a microprocessor unit that can be used as the distribution controller  214 . A microprocessor unit  600  includes a processor  610 , a ROM  620 , and a RAM  630 . In the microprocessor unit  600 , the processor  610 , the ROM  620 , and the RAM  630  are connected to one another through a bus. The microprocessor unit  600  may include another circuit such as a peripheral circuit, a communication circuit, and an interface circuit, although illustration thereof is omitted. 
     The ROM  620  is a non-volatile storage device. For example, a semiconductor storage device such as a flash memory having a relatively small capacity can be used for the ROM  620 . The ROM  620  stores a program executed by the processor  610 . 
     The RAM  630  is a volatile storage device. As the RAM  630 , various types of semiconductor memory apparatuses such as a dynamic random access memory (DRAM) or a static random access memory (SRAM) can be used. The RAM  630  can be used as an internal buffer for temporarily storing data and the like. The processor  610  deploys (i.e., loads) a program stored in the ROM  620  in the RAM  630 , and executes the deployed (i.e., loaded) program. The function of each unit in the distribution controller  214  can be implemented by having the processor  610  execute a program. 
     The aforementioned program can be stored and provided to the computer apparatus  500  and the microprocessor unit  600  by using any type of non-transitory computer readable media. Non-transitory computer readable media include any type of tangible storage media. Examples of non-transitory computer readable media include magnetic storage media such as floppy disks, magnetic tapes, and hard disk drives, optical magnetic storage media such as magneto-optical disks, optical disk media such as compact disc (CD) and digital versatile disk (DVD), and semiconductor memories such as mask ROM, programmable ROM (PROM), erasable PROM (EPROM), flash ROM, and RAM. Further, the program may be provided to a computer using any type of transitory computer readable media. Examples of transitory computer readable media include electric signals, optical signals, and electromagnetic waves. Transitory computer readable media can provide the program to a computer apparatus and the like via a wired communication line such as electric wires and optical fibers or a radio communication line. 
     Although example embodiments according to the present disclosure have been described above in detail, the present disclosure is not limited to the above-described example embodiments, and the present disclosure also includes those that are obtained by making changes or modifications to the above-described example embodiments without departing from the spirit of the present disclosure. 
     The whole or part of the example embodiments disclosed above can be described as, but not limited to, the following Supplementary notes. 
     [Supplementary Note 1] 
     A remote monitoring system including: 
     a vehicle having an imaging device; and 
     a remote monitoring apparatus connected to the vehicle through a network, in which 
     the remote monitoring apparatus includes: 
     an image reception means for receiving an image taken by the imaging device through the network; 
     an event prediction means for predicting an event based on the image received by the image reception means; and 
     an important area identification means for identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event, and 
     the vehicle includes an image adjustment means for adjusting quality concerning the identified important area in the image. 
     [Supplementary Note 2] 
     The remote monitoring system described in Supplementary note 1, in which the image adjustment means adjusts quality of the image such that quality of the important area is higher than quality of an area other than the important area in the image. 
     [Supplementary Note 3] 
     The remote monitoring system described in Supplementary note 1 or 2, further including an object detection means for detecting an object from the image, the object being related to the event predicted by the event prediction means, 
     in which the important area identification means identifies the important area based on a position of the detected object. 
     [Supplementary Note 4] 
     The remote monitoring system described in Supplementary note 3, in which the important area identification means estimates a direction in which the object is shifting and identifies an area for a destination to which the object is shifting as the important area. 
     [Supplementary Note 5] 
     The remote monitoring system described in any one of Supplementary notes 1 to 4, in which the important area identification means informs the image adjustment means of the important area through the network. 
     [Supplementary Note 6] 
     The remote monitoring system described in any one of Supplementary notes 1 to 5, in which the event prediction means predicts an event related to occurrence of danger based on the image. 
     [Supplementary Note 7] 
     The remote monitoring system described in any one of Supplementary notes 1 to 6, further including an image display means for displaying the image whose quality is adjusted by the image adjustment means. 
     [Supplementary Note 8] 
     The remote monitoring system described in Supplementary note 7, in which the image display means displays a result of the predicted event superimposing on the image. 
     [Supplementary Note 9] 
     A remote monitoring apparatus including: 
     an image reception means for receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; 
     an event prediction means for predicting an event based on the image received by the image reception means; and 
     an important area identification means for identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event, 
     in which the image reception means receives, from the vehicle, the image, whose quality concerning the identified important area in the image has been adjusted. 
     [Supplementary Note 10] 
     The remote monitoring apparatus described in Supplementary note 9, in which the image reception means receives the image whose quality has been adjusted such that quality of the important area is higher than quality of an area other than the important area in the image. 
     [Supplementary Note 11] 
     The remote monitoring apparatus described in Supplementary note 9 or 10, further including an object detection means for detecting an object from the image, the object being related to the event predicted by the event prediction means, 
     in which the important area identification means identifies the important area based on a position of the detected object. 
     [Supplementary Note 12] 
     The remote monitoring apparatus described in Supplementary note 11, in which the important area identification means estimates a direction in which the object is shifting and identifies an area for a destination to which the object is shifting as the important area. 
     [Supplementary Note 13] 
     The remote monitoring apparatus described in any one of Supplementary notes 9 to 12, in which the important area identification means informs the vehicle of the important area through the network. 
     [Supplementary Note 14] 
     The remote monitoring apparatus described in any one of Supplementary notes 9 to 13, in which the event prediction means predicts an event related to occurrence of danger based on the image. 
     [Supplementary Note 15] 
     The remote monitoring apparatus described in any one of Supplementary notes 9 to 14, further including an image display means for displaying the image in which quality concerning the identified important area has been adjusted. 
     [Supplementary Note 16] 
     The remote monitoring apparatus described in Supplementary note 15, in which the image display means displays a result of the predicted event superimposing on the image. 
     [Supplementary Note 17] 
     A remote monitoring method including: 
     receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; 
     predicting an event based on the received image; 
     identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event; and 
     adjusting quality concerning the identified important area in the image. 
     [Supplementary Note 18] 
     The remote monitoring method described in Supplementary note 17, in which the adjusting of the quality includes adjusting quality of the image such that quality of the important area is higher than quality of an area other than the important area in the image. 
     [Supplementary Note 19] 
     The remote monitoring method described in Supplementary note 17 or 18, further including detecting an object related to the predicted event from the image, 
     in which the identifying of the important area includes identifying the important area based on a position of the detected object. 
     [Supplementary Note 20] 
     The remote monitoring method described in Supplementary note 19, in which the identifying of the important area includes estimating a direction in which the object is shifting and identifying an area for a destination to which the object is shifting as the important area. 
     [Supplementary Note 21] 
     The remote monitoring method described in any one of Supplementary notes 17 to 20, in which the vehicle is informed of the important area through the network. 
     [Supplementary Note 22] 
     The remote monitoring method described in any one of Supplementary notes 17 to 21, in which the predicting of the event includes predicting an event related to occurrence of danger based on the image. 
     [Supplementary Note 23] 
     The remote monitoring method described in any one of Supplementary notes 17 to 22, further including displaying the image in which quality concerning the important area has been adjusted. 
     [Supplementary Note 24] 
     The remote monitoring method described in Supplementary note 23, in which the displaying of the image includes displaying a result of the predicted event superimposing on the image. 
     [Supplementary Note 25] 
     An image acquisition method including: 
     receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; 
     predicting an event based on the received image; 
     identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event; and 
     receiving the image from the vehicle, quality concerning the identified important area in the image having been adjusted. 
     [Supplementary Note 26] 
     A non-transitory computer readable medium storing a program for causing a computer to perform processes including: 
     receiving an image from a vehicle through a network, the vehicle having an imaging device, the image being taken by the imaging device; 
     predicting an event based on the received image; 
     identifying an area as an important area in the image based on a result of the predicted event, the area being related to the predicted event; 
     informing the vehicle of the identified important area, the vehicle being configured to adjust quality of the image such that the important area is clearer than another area in the image to be received from the vehicle through the network; and 
     receiving the image from the vehicle, quality of the image having been adjusted such that the identified important area is clearer than the other area in the image. 
     REFERENCE SIGNS LIST 
     
         
           10  REMOTE MONITORING SYSTEM 
           11  REMOTE MONITORING APPARATUS 
           12  IMAGE RECEPTION MEANS 
           13  EVENT PREDICTION MEANS 
           14  IMPORTANT AREA IDENTIFICATION MEANS 
           15  VEHICLE 
           16  IMAGE ADJUSTMENT MEANS 
           20  NETWORK 
           100  REMOTE MONITORING SYSTEM 
           101  REMOTE MONITORING APPARATUS 
           102  NETWORK 
           111  IMAGE RECEPTION UNIT 
           112  DANGER PREDICTION UNIT 
           113  OBJECT DETECTION UNIT 
           114  MONITORING SCREEN DISPLAY UNIT 
           115 ,  214  DISTRIBUTION CONTROLLER 
           116 ,  215  IMPORTANT AREA IDENTIFICATION UNIT 
           117 ,  216  IMPORTANT AREA INFORMING UNIT 
           118  RESULT INFORMING UNIT 
           200  VEHICLE 
           201  COMMUNICATION APPARATUS 
           211  DISTRIBUTION IMAGE ADJUSTMENT UNIT 
           212  IMAGE TRANSMISSION UNIT 
           213  IMPORTANT AREA RECEPTION UNIT 
           300  CAMERA