CN111667663A - Waste transport driver violation detection method based on artificial intelligence video analysis - Google Patents
Waste transport driver violation detection method based on artificial intelligence video analysis Download PDFInfo
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- CN111667663A CN111667663A CN202010447358.4A CN202010447358A CN111667663A CN 111667663 A CN111667663 A CN 111667663A CN 202010447358 A CN202010447358 A CN 202010447358A CN 111667663 A CN111667663 A CN 111667663A
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- Prior art keywords
- driver
- vehicle
- target driver
- intelligent host
- definition camera
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Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
Abstract
The invention discloses a waste transport driver violation detection method based on artificial intelligence video analysis, which is characterized by comprising the following steps of: s1: the high-definition camera and the vehicle-mounted intelligent host are installed in the automobile cockpit, the high-definition camera is arranged aiming at a monitoring target driver, the high-definition camera is connected with the vehicle-mounted intelligent host, the high-definition camera is started in the process of monitoring the target driver to drive the vehicle, video collection is carried out on the detection target driver, and the collected video data are transmitted to the vehicle-mounted intelligent host. When the contrast reaches the preset threshold value, dangerous video pictures and time information can be conveyed to the control end, so that the dangerous driving behaviors can be punished and managed, the effect of conveniently monitoring and managing the driving process of a transport driver in real time is achieved, the aim of improving the safety management efficiency is fulfilled, the safety is improved, and the efficiency of the whole transport management is improved by applying the method.
Description
Technical Field
The invention relates to the technical field of transportation safety management, in particular to a waste transport driver violation detection method based on artificial intelligence video analysis.
Background
Artificial Intelligence (AI), abbreviated as English, is a new technical science for researching and developing theories, methods, techniques and application systems for simulating, extending and expanding human intelligence, is a branch of computer science, attempts to understand the essence of intelligence and produces a new intelligent machine which can respond in a manner similar to human intelligence, and the research in the field comprises robots, language recognition, image recognition, natural language processing, expert systems and the like, and the artificial intelligence is born, the theories and the techniques are mature day by day, the application field is expanded continuously, and the artificial intelligence has good application prospects in various fields; in the transportation management of waste gas, the driving management of a transportation driver is an important link of safety management, and new management equipment or a new management method is required to be applied to improve the management efficiency.
At present, the management efficiency of a transport company and an environmental protection company on waste transportation and the management efficiency of a transport driver are low, and the traditional management method is difficult to monitor and detect the illegal and unsafe behaviors of the driver in the transportation and driving process, so that the whole transportation safety management efficiency is low.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a waste transport driver violation detection method based on artificial intelligence video analysis.
A waste transport driver violation detection method based on artificial intelligence video analysis comprises the following steps:
s1: installing a high-definition camera and a vehicle-mounted intelligent host in an automobile cockpit, enabling the high-definition camera to be arranged aiming at a monitored target driver, enabling the high-definition camera to be connected with the vehicle-mounted intelligent host, starting the high-definition camera in the process of monitoring the target driver to drive a vehicle, acquiring videos of the detected target driver, and transmitting the acquired video data to the vehicle-mounted intelligent host;
s2: the intelligent host identifies behaviors and actions of a monitored target driver in the video through an internal processor, and the processor compares the behaviors and actions of the monitored target driver with human behavior identification models and compares and detects the actions of the monitored target driver with behaviors of smoking, connecting and disconnecting a mobile phone, fastening a safety belt and the like;
s3: when the similarity between the action behavior of the monitored target driver and the behaviors of smoking, connecting and disconnecting a mobile phone, not fastening a safety belt and the like is detected to reach a preset threshold value through comparison of an internal processor, the intelligent host intercepts picture signals and time information of a video picture, generates alarm information of abnormal behaviors of the vehicle according to the serial number of a camera, and transmits the alarm information to a transfer company and an environmental protection department in real time;
s4: after a transfer company or an environmental protection department receives alarm information, namely video picture pictures and time information during alarm are received in real time through a terminal, so that rapid manual secondary audit can be performed, and transport personnel are punished according to relevant laws, regulations and unit regulations when the potential safety hazard really exists;
and S5, the intelligent host detects that the action behavior of the monitored target driver is highly coincident with the model of the special high-risk driving state through comparison of the internal processor, and when the action behavior reaches a preset threshold value, the intelligent host transmits an emergency alarm signal to terminal equipment of emergency contact personnel of a transfer company or an environmental protection department, so that the emergency contact personnel emergently call the monitored target driver at the first time and remind the driver of safe driving.
Preferably, if the similarity threshold is not reached in step S3, no signal is sent to the outside.
Preferably, after the manual secondary review in step S4, when the driver with the potential safety hazard is penalized, the penalty message should be notified when the penalized driver completes the driving task, so as to reduce the influence on the emotion of the driver.
The invention provides a waste transport driver violation detection method based on artificial intelligence video analysis, the high-definition camera is used for carrying out real-time video acquisition on a monitored target driver, the vehicle-mounted intelligent host is used for receiving video data, and compares the action behavior of the monitored target driver with the dangerous driving action and behavior through an internal processor, when the contrast reaches a preset threshold value, namely, the dangerous video pictures and time information can be transmitted to the control end, the state of the monitored target driver can be checked for the second time through the second check, therefore, punishment management can be carried out on existing unsafe driving behaviors, the effect of conveniently carrying out real-time monitoring management on the driving process of a transport driver is achieved, the aim of improving the safety management efficiency is achieved, the safety is improved, and the efficiency of the whole transport management is improved by applying the method.
Detailed Description
The present invention will be further illustrated with reference to the following specific examples.
The invention provides a waste transport driver violation detection method based on artificial intelligence video analysis, which comprises the following steps of:
s1: installing a high-definition camera and a vehicle-mounted intelligent host in an automobile cockpit, enabling the high-definition camera to be arranged aiming at a monitored target driver, enabling the high-definition camera to be connected with the vehicle-mounted intelligent host, starting the high-definition camera in the process of monitoring the target driver to drive a vehicle, acquiring videos of the detected target driver, and transmitting the acquired video data to the vehicle-mounted intelligent host;
s2: the intelligent host identifies behaviors and actions of a monitored target driver in the video through an internal processor, and the processor compares the behaviors and actions of the monitored target driver with human behavior identification models and compares and detects the actions of the monitored target driver with behaviors of smoking, connecting and disconnecting a mobile phone, fastening a safety belt and the like;
s3: when the similarity between the action behavior of the monitored target driver and the behaviors of smoking, connecting and disconnecting a mobile phone, not fastening a safety belt and the like is detected to reach a preset threshold value through comparison of an internal processor, the intelligent host intercepts picture signals and time information of a video picture, generates alarm information of abnormal behaviors of the vehicle according to the serial number of a camera, and transmits the alarm information to a transfer company and an environmental protection department in real time;
s4: after a transfer company or an environmental protection department receives alarm information, namely video picture pictures and time information during alarm are received in real time through a terminal, so that rapid manual secondary audit can be performed, and transport personnel are punished according to relevant laws, regulations and unit regulations when the potential safety hazard really exists;
and S5, the intelligent host detects that the action behavior of the monitored target driver is highly coincident with the model of the special high-risk driving state through comparison of the internal processor, and when the action behavior reaches a preset threshold value, the intelligent host transmits an emergency alarm signal to terminal equipment of emergency contact personnel of a transfer company or an environmental protection department, so that the emergency contact personnel emergently call the monitored target driver at the first time and remind the driver of safe driving.
If the similarity threshold is not reached in step S3, no signal is sent to the outside.
After the manual secondary audit in step S4, when the driver who really has the potential safety hazard is penalized, the penalty message should be notified when the penalized driver completes the driving task, so as to reduce the influence on the emotion of the driver.
The invention provides a waste transport driver violation detection method based on artificial intelligence video analysis, the high-definition camera is used for carrying out real-time video acquisition on a monitored target driver, the vehicle-mounted intelligent host is used for receiving video data, and compares the action behavior of the monitored target driver with the dangerous driving action and behavior through an internal processor, when the contrast reaches a preset threshold value, namely, the dangerous video pictures and time information can be transmitted to the control end, the state of the monitored target driver can be checked for the second time through the second check, therefore, punishment management can be carried out on existing unsafe driving behaviors, the effect of conveniently carrying out real-time monitoring management on the driving process of a transport driver is achieved, the aim of improving the safety management efficiency is achieved, the safety is improved, and the efficiency of the whole transport management is improved by applying the method.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (3)
1. A waste transport driver violation detection method based on artificial intelligence video analysis is characterized by comprising the following steps:
s1: installing a high-definition camera and a vehicle-mounted intelligent host in an automobile cockpit, enabling the high-definition camera to be arranged aiming at a monitored target driver, enabling the high-definition camera to be connected with the vehicle-mounted intelligent host, starting the high-definition camera in the process of monitoring the target driver to drive a vehicle, acquiring videos of the detected target driver, and transmitting the acquired video data to the vehicle-mounted intelligent host;
s2: the intelligent host identifies behaviors and actions of a monitored target driver in the video through an internal processor, and the processor compares the behaviors and actions of the monitored target driver with human behavior identification models and compares and detects the actions of the monitored target driver with behaviors of smoking, connecting and disconnecting a mobile phone, fastening a safety belt and the like;
s3: when the similarity between the action behavior of the monitored target driver and the behaviors of smoking, connecting and disconnecting a mobile phone, not fastening a safety belt and the like is detected to reach a preset threshold value through comparison of an internal processor, the intelligent host intercepts picture signals and time information of a video picture, generates alarm information of abnormal behaviors of the vehicle according to the serial number of a camera, and transmits the alarm information to a transfer company and an environmental protection department in real time;
s4: after a transfer company or an environmental protection department receives alarm information, namely video picture pictures and time information during alarm are received in real time through a terminal, so that rapid manual secondary audit can be performed, and transport personnel are punished according to relevant laws, regulations and unit regulations when the potential safety hazard really exists;
and S5, the intelligent host detects that the action behavior of the monitored target driver is highly coincident with the model of the special high-risk driving state through comparison of the internal processor, and when the action behavior reaches a preset threshold value, the intelligent host transmits an emergency alarm signal to terminal equipment of emergency contact personnel of a transfer company or an environmental protection department, so that the emergency contact personnel emergently call the monitored target driver at the first time and remind the driver of safe driving.
2. The method for detecting the violation of a driver in waste transport according to claim 1, wherein no signal is sent to the outside if the similarity threshold is not reached in step S3.
3. The method for detecting the violation of drivers in waste transportation according to claim 1, wherein after the manual secondary review in step S4, when a driver who really has a safety hazard is penalized, the penalty message is notified again when the penalized driver completes the driving task, so as to reduce the influence on the emotion of the driver.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010447358.4A CN111667663A (en) | 2020-05-25 | 2020-05-25 | Waste transport driver violation detection method based on artificial intelligence video analysis |
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| CN202010447358.4A CN111667663A (en) | 2020-05-25 | 2020-05-25 | Waste transport driver violation detection method based on artificial intelligence video analysis |
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| CN111667663A true CN111667663A (en) | 2020-09-15 |
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| CN202010447358.4A Pending CN111667663A (en) | 2020-05-25 | 2020-05-25 | Waste transport driver violation detection method based on artificial intelligence video analysis |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007219578A (en) * | 2006-02-14 | 2007-08-30 | Omron Corp | Abnormality detection device and method, recording medium and program |
| CN104751663A (en) * | 2015-02-28 | 2015-07-01 | 北京壹卡行科技有限公司 | Safe driving auxiliary system and safe driving auxiliary method for driver |
| CN105718864A (en) * | 2016-01-18 | 2016-06-29 | 安徽天盛智能科技有限公司 | A method for detecting whether drivers and passengers of motor vehicles fasten seat belts on the way |
| CN109919407A (en) * | 2018-12-28 | 2019-06-21 | 地上铁租车（深圳）有限公司 | A kind of driving behavior active security management system |
-
2020
- 2020-05-25 CN CN202010447358.4A patent/CN111667663A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007219578A (en) * | 2006-02-14 | 2007-08-30 | Omron Corp | Abnormality detection device and method, recording medium and program |
| CN104751663A (en) * | 2015-02-28 | 2015-07-01 | 北京壹卡行科技有限公司 | Safe driving auxiliary system and safe driving auxiliary method for driver |
| CN105718864A (en) * | 2016-01-18 | 2016-06-29 | 安徽天盛智能科技有限公司 | A method for detecting whether drivers and passengers of motor vehicles fasten seat belts on the way |
| CN109919407A (en) * | 2018-12-28 | 2019-06-21 | 地上铁租车（深圳）有限公司 | A kind of driving behavior active security management system |
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Application publication date: 20200915 |