TWI752644B - Internet of things vehicle control system and internet of things vehicle control method - Google Patents

Abstract

An internet of things vehicle control system and an internet of things vehicle control method are provided. The internet of things vehicle control system has a control component, a pulse sensing device,a latitude and longitude positioning device, and a cloud device. The control component has an image sensing module, a type of neural module, and a control module. The image sensing module can detect an environment of a vehicle to generate an image information. The type of neural module filters out a first input value, a second input value, and a third input value by analyzing the image information. The control module inputs the first input value, the second input value, and the third input value to control the vehicle. The pulse sensing device detects a driver of the vehicle to generate a real-time pulse information. The latitude and longitude positioning device can locate the position of the vehicle and has a plurality of rescue latitude and longitude positions. Accordingly, when the driver of the vehicle is unwell, the internet of things vehicle control system can sent the driver to the hospital immediately by the vehicle thereof.

Description

Internet of things vehicle control system and Internet of things vehicle control method

The invention relates to a control system and a control method, in particular to an Internet of Things vehicle control system and an Internet of Things vehicle control method.

At present, the driving mode of vehicles is mostly manual driving, and the driver may have a vehicle accident due to physical mental weakness or sudden illness during the driving process. Therefore, the existing IoT vehicle control system can solve the problems caused by manual driving in an automatic driving manner.

However, although the existing IoT vehicle control system can drive the vehicle in an automatic driving manner, when the driver is physically unwell in the vehicle, the existing IoT vehicle control system cannot detect the driver's condition, and continues to follow the The original planned route is automatically driven. For example, if the driver is on a route with a preset travel time of five hours, if the driver suddenly suffers from cardiac discomfort and cannot request assistance or control the vehicle, the existing IoT vehicle control system is still based on the preset. Driving on the road, the driver will be trapped in the car for five hours and miss the prime time for first aid.

That is to say, the existing Internet of Things vehicle control system still lacks monitoring and response to the driver's physiological condition. Therefore, this problem has become an important subject of the existing Internet of Things vehicle control system.

Therefore, the inventor believes that the above-mentioned defects can be improved. Nate has devoted himself to research and application of scientific principles, and finally proposes an invention with reasonable design and effective improvement of the above-mentioned defects.

The technical problem to be solved by the present invention is to provide an Internet of Things vehicle control system and an Internet of Things vehicle control method in view of the deficiencies of the prior art, which can automatically drive the vehicle accurately and respond to the driver's physiological condition.

An embodiment of the present invention discloses an Internet of Things vehicle control system, which is installed on a vehicle body. The Internet of Things vehicle control system includes: a control component, a drive unit electrically connected to the vehicle body, and the control component It can control the rotation direction and rotation speed of the wheel group of the driving unit that drives the vehicle body. The control assembly includes: an image sensing module, which is arranged on the vehicle, and the image sensing module Detecting the environment of the vehicle body to generate an image information; a type of neural module analyzes the image information and filters out a first input value, a second input value and a third input value, the first input value In order to determine the parameter for decelerating the vehicle, the second input value is a parameter for determining the acceleration of the vehicle, and the third input value is obtained by using the second input value to optimize the acceleration of the vehicle and a control module electrically connected to the neural-like module, the control module includes: a proportional control unit that receives the first input value, and the proportional control unit utilizes the first input value The input value generates a deceleration command, and the deceleration command is used to control the drive unit to drive the wheel set to decelerate; an integral control unit receives the second input value, and the integral control unit uses the second input value generating an acceleration command, the acceleration command is used to control the driving unit to drive the wheel set to accelerate; and a differential control unit, receiving the third input value, the differential control unit generates the third input value by using the differential control unit an optimization command, the optimization command is used to optimize the acceleration change of the drive unit driving the wheel set after receiving the acceleration command; a pulse sensing device, electrically connected to the control component , the pulse sensing device is used to detect the The pulse of the driver in the vehicle body generates a real-time pulse information; and a latitude and longitude positioning device is electrically connected to the control assembly, the longitude and latitude positioning device can locate the position of the vehicle body and has a plurality of ambulance latitude and longitude positions, and a plurality of all the latitude and longitude positions. The rescue latitude and longitude position can be used for the control component to confirm the emergency rescue position; wherein, when the pulse sensing device detects that the real-time pulse information is lower than a normal value, the neural model of the control component The group utilizes a plurality of the rescue longitude and latitude positions of the longitude and latitude positioning device to screen the nearest emergency rescue longitude and latitude position, so that the control module of the control assembly can control the vehicle to go; a cloud device capable of The network receives the image information and the real-time pulse information.

An embodiment of the present invention further discloses a method for controlling an Internet of Things vehicle, which is used to control a vehicle body. The method includes the following steps: implementing a state monitoring step: obtaining real-time pulse information of a driver of the vehicle body; implementing a Status judgment step: judging whether the pulse of the real-time pulse information is lower than the normal value; if so, then implement the next step; if not, implement the state monitoring step; implement a position confirmation step: obtain the current location of the vehicle body Longitude and latitude position; implementing a rescue location search step: confirming a current ambulance latitude and longitude position closest to the vehicle body; implementing a route planning step: planning a travel route of the vehicle body to the ambulance latitude and longitude position; implementing a perception environment Steps: obtaining an image information of the surrounding environment of the vehicle body; implementing an information screening step: filtering the image information to generate a first input value, a second input value and a third input value; wherein, the first input value An input value is a parameter for determining the deceleration of the vehicle body, the second input value is a parameter for determining the acceleration of the vehicle body, and the third input value is an optimization obtained by using the second input value parameters for the acceleration of the vehicle body; implement a parameter input step: input the first input value, the second input value, and the third input value to a FOPID controller (FOPID controller); wherein, the The first input value is used as a deceleration parameter of the proportional operation, the second input value is used as an acceleration parameter of the integral operation, and the third input value is used as an optimization parameter of the differential operation; and implement an integration determination step: using the first input value, the second input value and The third input value commands the vehicle body to move along the route of travel.

To sum up, the Internet of Things vehicle control system and the Internet of Things vehicle control method disclosed in the embodiments of the present invention can obtain the image information around the vehicle body through "the image sensing module, and use the The neural module filters each input value for the control module to control the vehicle body” and “When the pulse sensing device detects that the real-time pulse information is lower than the normal value, the neural module The technical solution of screening the nearest emergency ambulance latitude and longitude position for the control module to control the vehicle to go”, so that the driver who drives the vehicle body can be in a physiological condition that cannot drive. Seek immediate medical attention.

For a further understanding of the features and technical content of the present invention, please refer to the following detailed descriptions and drawings of the present invention. However, the drawings provided are only for reference and description, and are not intended to limit the present invention.

100: IoT Vehicle Control System

110: Control Components

111: Image sensing module

112: Neural-like modules

113: Control Module

1131: Proportional Control Unit

1132: Integral control unit

1133: Differential Control Unit

114: Radar Sensing Module

120: Pulse Sensing Device

121: Pulse detection module

122: Communication module

130: latitude and longitude positioning device

140: Transmission device

150: Warning component

160: Eye Sensing Device

170: Brainwave Wearable Device

180: Cloud Device

200: body

210: Drive unit

220: Wheels

P: driver

V1: first input value

V2: Second input value

V3: The third input value

VD: Video Information

DT: Distance information

D1: Deceleration command

D2: Speed up command

D3: Optimization command

RP: Real-time pulse information

RB: real-time brainwave information

RE: Real-time eyeball information

LA: ambulance latitude and longitude position

WR: Ambulance Alert

PTH: route of travel

S101~S119, S103A: Steps

FIG. 1 is a schematic block diagram of a circuit of an IoT vehicle control system in cooperation with a vehicle according to a first embodiment of the present invention.

FIG. 2 is a functional block diagram of the IoT vehicle control system matching the vehicle according to the first embodiment of the present invention.

FIG. 3 is a schematic diagram of the state when the IoT vehicle control system obtains image information according to the first embodiment of the present invention.

FIG. 4 is a schematic diagram of a state when a driver wears a pulse sensing device and drives a vehicle body according to the first embodiment of the present invention.

FIG. 5 is a schematic state diagram of the Internet of Things vehicle control system when planning a travel route according to the first embodiment of the present invention.

FIG. 6 is a second embodiment of the Internet of Things vehicle control system in coordination with the electrical power of the vehicle. Road block diagram.

FIG. 7 is a functional block diagram of an IoT vehicle control system in coordination with a vehicle according to a second embodiment of the present invention.

FIG. 8 is a schematic diagram of the state when the IoT vehicle control system according to the second embodiment of the present invention acquires image information and distance information.

9 is a schematic diagram of a state when a driver wears a pulse sensing device, an eyeball sensing device, and a wearable brainwave device according to a second embodiment of the present invention.

FIG. 10 is a schematic block diagram of a flow chart of a method for controlling an Internet of Things vehicle according to a third embodiment of the present invention.

The following are specific specific examples to illustrate the embodiments of the “Internet of Things vehicle control system and the Internet of Things vehicle control method” disclosed in the present invention. Those skilled in the art can understand the advantages and effects of this creation from the content disclosed in this specification. . This creation can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the concept of this creation. In addition, the drawings in this creation are only for simple schematic illustration, and are not drawn according to the actual size, and are stated in advance. In addition, if it is indicated below to refer to a specific figure or as shown in a specific figure, it is only used for emphasis in the subsequent description, and most of the relevant content mentioned appears in the specific figure, but not Reference in this ensuing description is limited to those specific drawings. The following embodiments will further describe the related technical contents of the present creation in detail, but the disclosed contents are not intended to limit the protection scope of the present creation. In addition, the term "or", as used herein, should include any one or a combination of more of the associated listed items, as the case may be.

[First Embodiment]

As shown in FIG. 1 to FIG. 5 , it is the first embodiment of the present invention. Referring to FIG. 1 and FIG. 2 , the present embodiment discloses an IoT vehicle control system 100 , the IoT vehicle control system 100 is used to be installed on a vehicle body 200 , and the vehicle body 200 in this embodiment is It is an electric vehicle and has a driving unit 210 and a wheel group 220 driven by the driving unit 210 .

The IoT vehicle control system 100 includes a control component 110 , a pulse sensing device 120 , a latitude and longitude positioning device 130 , a transmission device 140 , an alarm component 150 , and a cloud device 180 . Specifically, the IoT vehicle control system 100 can confirm the physiological condition of a driver P (as shown in FIG. 4 ) driving the vehicle body 200 according to the pulse sensing device 120 , and use the control component 110 cooperates with the longitude and latitude positioning device 130 to control the vehicle body 200 to automatically travel to an ambulance unit (eg, a hospital) for medical treatment. In other words, any IoT vehicle control system that does not have the ability to confirm the driver's physiological condition and automatically drive the vehicle to the ambulance unit for medical treatment is not the IoT vehicle control system 100 referred to in the present invention. The structure of each element of the Internet of Things vehicle control system 100 will be introduced separately below, and the connection relationship between the various elements of the Internet of Things vehicle control system 100 will be described in due course.

The control assembly 110 is electrically connected to the drive unit 210 of the vehicle body 200 , and the control assembly 110 can control the rotation direction and rotation of the wheel set 220 of the vehicle body 200 driven by the drive unit 210 . speed. That is, the control assembly 110 is the main component that controls the movement of the vehicle body 200 . The control component 110 includes an image sensing module 111 , a type of neural module 112 and a control module 113 .

As shown in FIGS. 1 to 3 , the image sensing module 111 is disposed on the vehicle body 200 , and the image sensing module 111 detects the environment of the vehicle body 200 to generate an image information VD. Specifically, the image sensing module 111 is composed of a plurality of image recognizers in this embodiment and is disposed around the vehicle body 200 , and each of the image recognizers can capture the vehicle body 200 to generate an image frame, and a plurality of the image frames together form the image information VD.

The neural-like module 112 analyzes the image information VD and filters out a first input value V1, a second input value V2 and a third input value V3, and the first input value V1 is used to determine the vehicle body 200 is a parameter for deceleration, the second input value V2 is a parameter for determining the acceleration of the vehicle body 200, and the third input value V3 is obtained by using the second input value V2 to optimize the vehicle body 200 parameters for acceleration.

Specifically, the neural-like module 112 is an artificial neural network (Artificial Neural Network) in this embodiment, and the neural-like module 112 is optimized by a learning method based on mathematical statistics. It should be emphasized that the decision problem of artificial perception can be done through the application of mathematical statistics, that is, through statistical methods, the neural module 112 can have simple decision-making ability and simple judgment ability like a human being. .

For example, the image information VD detected and generated by the image sensing module 111 is the image content of a person walking in the center of the road where the vehicle body 200 is traveling. After image recognition, when it is determined that the distance between the person and the vehicle body 200 is less than 100 meters, the neural-like module 112 screens the image parameters (such as shadow length and change) in the image information VD as the The first input value V1 is used as a parameter for determining the deceleration of the vehicle body 200 . It should be noted that, the second input value V2 as the parameter for determining the acceleration of the vehicle body 200 and the third input value V3 as the parameter for optimizing the acceleration of the vehicle body 200 are also in a similar manner as described above. Screening judgment is carried out, so no examples are given.

The control module 113 is electrically connected to the neural-like module 112 . The control module 113 is a FOPID controller in this embodiment and includes a proportional control unit 1131 , an integral control unit 1132 and A differential control unit 1133 .

The proportional control unit 1131 receives the first input value V1, the proportional control unit 1131 uses the first input value V1 to generate a deceleration command D1, and the deceleration command D1 is used to control the driving unit 210 to drive the The wheel set 220 is decelerated. For example, the first input value V1 input into the proportional control unit 1131, the proportional control unit 1131 can generate the deceleration command D1 for decelerating to a speed of 30 kilometers per hour, the proportional control unit 1131 will issue the deceleration command D1 to the drive unit 210 , so that the driving unit 210 drives the wheel set 220 to decelerate, so that the vehicle speed of the vehicle body 200 is reduced to 30 kilometers per hour, and when the speed of the vehicle body 200 is 30 kilometers per hour, the proportional control The unit 1131 then stops issuing the deceleration command D1.

The integral control unit 1132 receives the second input value V2, the integral control unit 1132 uses the second input value V2 to generate an acceleration command D2, and the acceleration command D2 is used to control the driving unit 210 to drive the The wheel set 220 is accelerated. For example, the second input value V2 is input to the integral control unit 1132, and the integral control unit 1132 can generate the acceleration command D2 for accelerating to a speed of fifty kilometers per hour, and the integral control unit 1132 will The drive unit 210 issues the deceleration command D1, so that the drive unit 210 drives the wheel set 220 to accelerate, so that the vehicle speed of the vehicle body 200 is accelerated by fifty kilometers per hour, and when the speed of the vehicle body 200 is fifty kilometers per hour When the time is in, the integral control unit 1132 stops issuing the acceleration command D2.

In addition, it should be noted that if the first input value V1 input by the proportional control unit 1131 is relatively large (that is, the ratio is relatively large), the proportional control unit 1131 will cause the proportional control unit 1131 to control the speed of the vehicle body 200 to decelerate. During the process, the vehicle speed produces a certain range of vibration of the speed change (for example, the range of vibration is between 25 and 31 kilometers per hour), but cannot be accurately maintained to the speed desired by the deceleration command D1 (for example: 30 per hour). km), therefore, in cooperation with the integral control unit 1132, it can reduce and stabilize the oscillation range of the proportional control unit 1131 when the vehicle speed changes (for example: when the vehicle speed is lower than 30 kilometers per hour, the integral control unit 1132 increases the vehicle speed) , so that the vehicle speed of the vehicle body 200 is closer to the desired vehicle speed, for example.

The derivative control unit 1133 receives the third input value V3, and the derivative control unit 1133 uses the third input value V3 to generate an optimization command D3, and the optimization command D3 is used to optimize the The driving unit 210 drives the acceleration of the wheel set 220 after receiving the acceleration command Variety. Specifically, regardless of whether the drive unit 210 receives the deceleration command D1 from the proportional control unit 1131 or the acceleration command D2 from the integral control unit 1132, the vehicle speed change of the vehicle body 200 is irrelevant. An ideal linear change, and the optimization command D3 can make the vehicle speed change of the vehicle body 200 closer to the ideal linear change.

The pulse sensing device 120 is electrically connected to the control component 110 , and the pulse sensing device 120 is used for detecting the pulse of the driver in the vehicle body 200 to generate a real-time pulse information RP. Specifically, the pulse detection device 120 is a smart wearable bracelet in this embodiment and has a pulse detection module 121 and a communication module 122. In practice, the pulse detection module 121 can be Modular components used by methods such as photoplethysmography, electrocardiography, pressure oscillation, and image signal analysis. The communication module 122 is a Bluetooth communicator in this embodiment, and the communication module 122 can be wirelessly connected to the control component 110 .

The latitude and longitude positioning device 130 is electrically connected to the control assembly 110 , the latitude and longitude positioning device 130 can locate the position of the vehicle body 200 and has a plurality of rescue latitude and longitude positions LA, and the plurality of the rescue latitude and longitude positions LA can be used for The control assembly 110 confirms the location of the ambulance. The longitude and latitude positioning device 130 is a global positioning system (commonly known as: GPS positioning system) in this embodiment, and the longitude and latitude positioning device 130 is preset with a plurality of the rescue longitude and latitude positions LA such as hospitals, clinics, and ambulance stations, so as to Used by the control assembly 110 .

Specifically, as shown in FIG. 2 , FIG. 4 and FIG. 5 , when the pulse sensing device 120 detects that the real-time pulse information RP is lower than the normal value, the nerve-like module of the control component 110 112 Screen the nearest emergency rescue latitude and longitude position LA by using the multiple rescue latitude and longitude positions LA of the latitude and longitude positioning device 130 and plan a travel route PTH, so as to provide the control module of the control assembly 110 113 controls the vehicle body 200 to move forward.

The warning component 150 is electrically connected to the pulse sensing device 120. When the pulse sensing device 120 detects that the pulse of the real-time pulse information RP is lower than the normal value, the pulse sensing device 120 The setting 120 commands the alert component 150 to issue a rescue alert WR. In detail, the warning component 150 is a light flashing device with a buzzer function in this embodiment, and the warning component 150 is disposed at a conspicuous position of the vehicle body 200, such as the roof, and at the instant When the pulse of the pulse information RP is lower than the normal value, the warning component 150 can be the ambulance warning WR that emits a buzzer and a flashing light, so as to warn and inform the surrounding people and vehicles that the vehicle body 200 currently has emergency ambulances. need. Of course, the warning assembly 150 can also use the existing high and low beam lights, direction lights, horns, etc. of the vehicle body 200 to issue the ambulance warning WR.

The transmission device 140 is electrically connected to the control component 110 and the pulse sensing device 120 . The transmission device 140 is a wireless network communication device in this embodiment, and the transmission device is used to enable the control The image information VD of the component 110 and the real-time pulse information RP of the pulse sensing device 120 are sent to the cloud device 180 for recording. Further, the cloud device 180 that receives the image information VD and the pulse sensing device 120 is connected to a plurality of medical rescue units corresponding to the rescue latitude and longitude positions LA. When the pulse sensing device 120 detects that the pulse of the real-time pulse information RP is lower than the normal value, the transmission device 140 transmits the image information VD and the real-time pulse information RP to the cloud device 180 It can be used by the medical ambulance unit to instantly confirm the pulse condition of the driver P and the surrounding vehicle conditions of the vehicle body 200, so as to immediately take appropriate actions, such as: preparing ambulance equipment, or dispatching ambulance vehicles that can eliminate the vehicle condition ( helicopters, ambulances), etc.

[Second Embodiment]

As shown in FIG. 6 and FIG. 9 , which are the second embodiment of the present invention, this embodiment is similar to the above-mentioned first embodiment, and the similarities between the two embodiments will not be repeated. The difference between the above-mentioned first embodiment mainly lies in that: as shown in FIG. 6 , FIG. 7 and FIG. Eyeball sensing device 160 and a Brainwave wearable device 170 . The eyeball sensing device 160 and the brainwave wearing device 170 are integrated into a glasses structure for the driver P to wear in this embodiment. The eyeball sensing device 160 is the lens part, and the brainwave wearing device 170 is the frame part that contacts the head.

Further, the eyeball sensing device 160 can sense the eyeballs of the driver P in the vehicle body 200 to generate real-time eyeball information RE, and the brainwave wearable device 170 can sense the driver P The brainwaves generate a real-time brainwave information RB. In practice, when the human body is distracted and inattentive, the human body has many physiological characteristics, such as multiple eyelid blinks, pupil dilation, brain wave decline and other physiological characteristics. The group 112 can be determined from the real-time eyeball information RE generated by the eyeball sensing device 160 and the real-time brainwave information RB generated by the brainwave wearing device 170 . When the nerve-like module 112 determines from the real-time eyeball information RE that the number of eye blinks of the driver P of the vehicle body 200 is abnormal or the brainwave of the real-time brainwave information RB is abnormal, the control component 110 The control right of the vehicle body 200 is controlled, so as to prevent the driver P from causing an accident due to distraction and inattention.

Of course, the real-time eyeball information RE and the real-time brainwave information RB can also be transmitted to the cloud device 180 through the transmission device 140 for recording.

In addition, referring back to FIGS. 6 to 8 , the control assembly 110 further has a radar sensing module 114 disposed on the vehicle body 200 , and the radar sensing module 114 can detect the vehicle The environment of the body 200 generates a distance information DT; the neural module 112 can analyze the distance information DT and filter out the first input value V1, the second input value V2 and the third input value V3 , thereby improving the accuracy of the control assembly 110 when controlling the vehicle body 200 .

[Third Embodiment]

As shown in FIG. 10 , it is a third embodiment of the present invention. This embodiment is similar to the above-mentioned first embodiment, and the similarities between the two embodiments will not be repeated. Compared with the above-mentioned first embodiment, this embodiment The main difference between the embodiments is that this embodiment is an IoT vehicle using the first embodiment 1 to 5, the IoT vehicle control method includes: a state monitoring step S101, a state judging step S103, a position confirming step S105, a rescue position searching step S107, A rescue notification step S109 , a route planning step S111 , a sensing environment step S113 , an information screening step S115 , a parameter input step S117 and an integration determination step S119 .

The state monitoring step S101 : obtaining the real-time pulse information RP of the driver P of the vehicle body 200 . Specifically, the real-time pulse information RP is the number of beats per minute of the current pulse of the driver P.

The state judging step S103 : judging whether the pulse of the real-time pulse information RP is lower than a normal value. If yes, implement a warning sub-step S103A: emit the ambulance warning WR as sound and light, and then implement the position confirmation step S105. If not, the state monitoring step S101 is implemented. Further, the normal pulse of the human body must be at least more than 50 times per minute, that is to say, when the pulse of the real-time pulse information RP is lower than 50 times per minute, the pulse at this time is lower than the normal value, but The present invention is not limited to what is contained in this embodiment. For example, a sudden drop in the pulse rate is also a warning sign of an abnormal pulse.

The position confirmation step S105 : obtaining the current latitude and longitude position of the vehicle body 200 .

The ambulance location searching step S107 : confirming the ambulance latitude and longitude position LA that is currently closest to the vehicle body 200 , and then simultaneously executing the ambulance notification step S109 and the route planning step S111 . In other words, in the rescue position searching step S107, a rescue longitude and latitude position LA which is closest to the current position is found from among a plurality of the rescue longitude and latitude positions LA preset or recorded.

The ambulance notification step S109 : using the cloud device 180 to transmit the real-time pulse information RP and the current latitude and longitude position of the vehicle body 200 to the ambulance latitude and longitude position The emergency ambulance unit corresponding to LA. Specifically, the medical staff can know the pulse condition of the driver P and the position of the vehicle body 200 through the cloud device 180 , so as to make appropriate actions in real time.

The route planning step S111 : planning a travel route PTH of the vehicle body 200 to the ambulance latitude and longitude position LA. Of course, in planning the travel route PTH, it is necessary to consider the surrounding vehicle conditions of the ambulance latitude and longitude position LA to be traveled to, and the surrounding vehicle conditions of the vehicle body can be connected to an existing vehicle condition platform (for example, the highway bureau real-time vehicle condition system). ) to obtain the travel route PTH that can be reached in the shortest time.

The sensing environment step S113 : obtaining the image information VD of the surrounding environment of the vehicle body 200 .

The information screening step S115 : screening the image information VD to generate the first input value, the second input value and the third input value. The first input value V1 is a parameter for determining the deceleration of the vehicle body 200, the second input value V2 is a parameter for determining the acceleration of the vehicle body 200, and the third input value V3 is the The second input value V2 is obtained to optimize the parameters for the acceleration of the vehicle body 200 .

The parameter input step S117: Input the first input value V1, the second input value V2, and the third input value V3 to a FOPID controller (FOPID controller), which is the first embodiment. The control module 113 is described. The first input value V1 is used as a deceleration parameter of proportional operation, the second input value V2 is used as an acceleration parameter of integral operation, and the third input value V3 is used as an optimization parameter of differential operation.

The integration determination step S119 : using the first input value V1 , the second input value V2 and the third input value V3 to instruct the vehicle body 200 to move along the travel route.

[Technical effects of the embodiments of the present invention]

To sum up, the IoT vehicle control system 100 disclosed in the embodiments of the present invention and the The Internet of Things vehicle control method, which can obtain the image information VD around the vehicle body 200 through the image sensing module 111, and filter each input value by the neural module 112 for the control The module 113 controls the vehicle body 200" and "when the pulse sensing device 120 detects that the real-time pulse information RP is lower than the normal value, the nerve-like module 112 selects the nearest emergency ambulance. The latitude and longitude position LA is a technical solution for the control module 113 to control the vehicle body 200 to go”, so that the driver P driving the vehicle body 200 can immediately seek medical treatment when a physiological condition that cannot drive occurs.

The contents disclosed above are only preferred feasible embodiments of the present invention, and are not intended to limit the scope of the present invention. Therefore, any equivalent technical changes made by using the contents of the description and drawings of the present invention are included in the application of the present invention. within the scope of the patent.

100: IoT Vehicle Control System

110: Control Components

111: Image sensing module

112: Neural-like modules

113: Control Module

1131: Proportional Control Unit

1132: Integral control unit

1133: Differential Control Unit

120: Pulse Sensing Device

121: Pulse detection module

122: Communication module

130: latitude and longitude positioning device

140: Transmission device

150: Warning component

160: Eye Sensing Device

200: body

210: Drive unit

220: Wheels

Claims (9)

An Internet of Things vehicle control system is used to be installed on a vehicle body, the Internet of Things vehicle control system includes: a control component, which is electrically connected to a drive unit of the vehicle body, and the control component can control the drive unit The rotation direction and rotation speed of the wheel group of the unit that drives the vehicle body, and the control assembly includes: an image sensing module disposed on the vehicle body, and the image sensing module detects the The environment of the vehicle body generates an image information; a type of neural module analyzes the image information and filters out a first input value, a second input value and a third input value, and the first input value determines the A parameter for decelerating the vehicle body, the second input value is a parameter for determining the acceleration of the vehicle body, and the third input value is obtained by using the second input value to optimize the acceleration of the vehicle body. parameters; and a control module electrically connected to the neural-like module, the control module comprising: a proportional control unit receiving the first input value, the proportional control unit using the first input value to generate a deceleration command, the deceleration command is used to control the drive unit to drive the wheel set to decelerate; an integral control unit receives the second input value, and the integral control unit uses the second input value to generate an acceleration command, the acceleration command is used to control the driving unit to drive the wheel set to accelerate; and a differential control unit, which receives the third input value, and the differential control unit generates a an optimization command, the optimization command is used to optimize the acceleration change of the drive unit driving the wheel set after receiving the acceleration command; a pulse sensing device electrically connected to the control component, The pulse sensing device is used for detecting the pulse of the driver in the vehicle to generate a real-time pulse information. and a latitude and longitude positioning device electrically connected to the control assembly, the latitude and longitude positioning device can locate the position of the vehicle body and has a plurality of ambulance latitude and longitude positions, and the plurality of the ambulance latitude and longitude positions can be used for the control The component confirms the location of the emergency rescue; wherein, when the pulse sensing device detects that the real-time pulse information is lower than the normal value, the nerve-like module of the control component utilizes a plurality of all the positions of the longitude and latitude positioning device. The emergency ambulance latitude and longitude positions are screened to the nearest emergency ambulance latitude and longitude position, so that the control module of the control assembly controls the vehicle body to go; a cloud device can receive the image information and the Real-time pulse information. The Internet of Things vehicle control system according to claim 1, wherein the Internet of Things vehicle control system further includes a transmission device electrically connecting the control component and the pulse sensing device, and the transmission device can use The image information of the control component and the real-time pulse information of the pulse sensing device are transmitted to the cloud device for record. The Internet of Things vehicle control system according to claim 1, wherein the Internet of Things vehicle control system further comprises an eyeball sensing device electrically connected to the neural module of the control component, and the eyeball sensor The detection device can sense the driver's eyeball in the vehicle body to generate real-time eyeball information; when the neural module judges that the driver's eyeball blinks in the vehicle body is abnormal according to the real-time eyeball information, the The control assembly controls the vehicle body. The Internet of Things vehicle control system according to claim 1, wherein the Internet of Things The vehicle control system further includes a brainwave wearable device electrically connected to the neural module of the control component, the brainwave wearable device is used to be worn on the driver of the vehicle body and generate a real-time brain wave wave information; when the neural-like module determines from the real-time brain wave information that the driver's brain wave of the vehicle body is abnormal, the control component controls the vehicle body. The Internet of Things vehicle control system according to claim 1, wherein the Internet of Things vehicle control system further comprises a warning component disposed on the vehicle body; the pulse sensing device is electrically connected to the warning component, When the pulse sensing device detects that the pulse of the real-time pulse information is lower than the normal value, the pulse sensing device instructs the warning component to issue a rescue warning. The Internet of Things vehicle control system according to claim 1, wherein the control module is a FOPID controller (FOPID controller). The Internet of Things vehicle control system according to claim 1, wherein the control component further includes a radar sensing module disposed on the vehicle body, the radar sensing module can detect the vehicle The environment of the body generates a distance information; the neural module can analyze the distance information and filter out the first input value, the second input value and the third input value. An Internet of Things vehicle control method for controlling a vehicle body, the method comprising the following steps: implementing a state monitoring step: obtaining a real-time pulse information of a driver of the vehicle body; implementing a state judging step: judging the Whether the pulse of the real-time pulse information is lower than the normal value; if so, then go to the next step; if not, implement the state state monitoring step; implementing a position confirmation step: obtaining the current latitude and longitude position of the vehicle body; implementing an ambulance location searching step: confirming a current ambulance latitude and longitude position closest to the vehicle body; implementing an ambulance notification step: using the cloud The device transmits the real-time pulse information and the current latitude and longitude position of the vehicle body to the emergency ambulance unit corresponding to the ambulance latitude and longitude position; implementing a route planning step: planning a journey of the vehicle body to the ambulance latitude and longitude position route; implementing a step of perceiving the environment: obtaining an image information of the surrounding environment of the vehicle body; implementing an information screening step: filtering the image information to generate a first input value, a second input value and a third input value ; wherein, the first input value is a parameter for determining the deceleration of the vehicle body, the second input value is a parameter for determining the acceleration of the vehicle body, and the third input value is the use of the second input value. The parameters obtained to optimize the acceleration of the vehicle body; implement a parameter input step: input the first input value, the second input value, and the third input value to a FOPID controller (FOPID controller). controller); wherein, the first input value is used as a deceleration parameter of proportional operation, the second input value is used as an acceleration parameter of integral operation, and the third input value is used as an optimization parameter of differential operation; and An integrated determination step is implemented: using the first input value, the second input value and the third input value to command the vehicle body to move along the travel route. The Internet of Things vehicle control method according to claim 8, wherein, in the state determination step, when the pulse of the real-time pulse information is lower than a normal value, An ambulance alert is sounded and lighted.

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