CN105943273B - Cloud computing system - Google Patents
Cloud computing system Download PDFInfo
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- CN105943273B CN105943273B CN201610351290.3A CN201610351290A CN105943273B CN 105943273 B CN105943273 B CN 105943273B CN 201610351290 A CN201610351290 A CN 201610351290A CN 105943273 B CN105943273 B CN 105943273B
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G7/00—Beds specially adapted for nursing; Devices for lifting patients or disabled persons
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G7/00—Beds specially adapted for nursing; Devices for lifting patients or disabled persons
- A61G7/05—Parts, details or accessories of beds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/35—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/70—General characteristics of devices with special adaptations, e.g. for safety or comfort
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/70—General characteristics of devices with special adaptations, e.g. for safety or comfort
- A61G2203/72—General characteristics of devices with special adaptations, e.g. for safety or comfort for collision prevention
- A61G2203/723—Impact absorbing means, e.g. bumpers or airbags
Abstract
The present invention relates to a kind of cloud computing system, including using cloud base station as the platform supported, the platform includes ultrasonic listening equipment, CCD sensing equipments, target identification equipment, spring equipment and MSP430 single-chip microcomputers, MSP430 single-chip microcomputers respectively with ultrasonic listening equipment, CCD sensing equipments, target identification equipment connects with spring equipment, target identification equipment is connected with CCD sensing equipments, high definition side image for being shot based on CCD sensing equipments judges that ward bed side whether there is human body, MSP430 single-chip microcomputers are used to control spring equipment based on the testing result of target identification equipment and ultrasonic listening equipment.By means of the invention it is possible to provide more convenience.
Description
Technical field
The present invention relates to hospital equipment field, more particularly to a kind of cloud computing system.
Background technology
Generally, patient is safely can to rest or receive on one's sick bed treatment, is on the one hand because uninterrupted
Ground has medical personnel and carries out medical and nursing work, or has families of patients and look after for a long time, even in night, it is also possible to arranges special
The nursing staff of door retains one's original salary patient is nursed, and shortens the unmanned nurse time of patient, on the other hand also in that some
Patient still has certain ability to act, to oneself having carried out self specification, reduces the probability to fall from the bed.But medical care
Personnel, families of patients or even the nursing staff that retains one's original salary are manually to nurse after all, and oneself also has the time had a meal, rested, can not be right
Patient carries out the uninterrupted, nurse of 24 hours, and therefore, patient still has certain unmanned nurse time, meanwhile, also have
Patient is to completely lose ability to act, for these patients, it is likely to once unintentionally turns over the hair for resulting in falling from bed event
It is raw.
In order to avoid the generation of patient's falling from bed event, in the prior art, hospital management side also takes much positive arrange
Apply, for example, transforming sick bed bed body, increase the height of guardrail, and set some geofences to set in sick bed bed body
Standby and emergence call equipment, to reduce the possibility of patient's falling from bed, the trigger device of falling from bed alarm is provided for patient, these transformations
Sick bed equipment afterwards reduces the generation of patient's falling from bed event to a certain extent.Meanwhile hospital management side also takes
Measure, such as increase and the interaction and communication of families of patients, to reduce the time of the unmanned nurse of patient.
But to make mechanism excessively simple for these existing hospital bed structural reforms, because patient's falling from bed duration intervals are very of short duration, on
The detection and warning device accuracy of detection stated be not high, detection efficiency is low, the increase of guardrail height and nurses the increase of time only
The probability of patient's falling from bed can be reduced, without being avoided that the event of falling from bed occurs, most importantly, is lacked in the prior art to patient
The fast reaction measure of falling from bed event and fast reaction equipment, fast reaction can not be carried out to patient's falling from bed event, can not be timely
Patient body is quickly supported, leads to not the ill effect for avoiding patient's falling from bed.
Therefore, it is necessary to a kind of technical scheme of new sick bed structure design, the pendant of patient can accurately and efficiently be detected
Bed event, can quickly be alarmed, additionally it is possible to patient is given first aid to using some emergency reaction equipment.
The content of the invention
In order to solve the above problems, the invention provides a kind of cloud computing system, by transforming existing hospital bed bed
Body, weight detection equipment, image detecting apparatus and ray detector are introduced in existing hospital bed bed body to patient
Falling from bed event carries out accurate judgement, introduces some sources of early warning and is alarmed accordingly, in addition, also introducing targetedly
Urgent rescue equipment is effectively supported to the patient body to fall.
According to an aspect of the present invention, there is provided a kind of cloud computing system, the platform include ultrasonic listening equipment,
CCD sensing equipments, target identification equipment, spring equipment and MSP430 single-chip microcomputers, MSP430 single-chip microcomputers respectively with ultrasonic listening
Equipment, CCD sensing equipments, target identification equipment are connected with spring equipment, and target identification equipment is connected with CCD sensing equipments, are used
Judge that ward bed side whether there is human body in the high definition side image shot based on CCD sensing equipments, MSP430 single-chip microcomputers are used for
Spring equipment is controlled based on the testing result of target identification equipment and ultrasonic listening equipment.
More specifically, in the cloud computing system, including：Ultrasonic listening equipment, positioned at the side of sick bed bed board, use
In detecting whether that object passes through from the side of sick bed bed board, and when being detected with object and passing through from the side of sick bed bed board,
Send object and skim over signal；Wireless Telecom Equipment, it is connected with MSP430 single-chip microcomputers, including the sub- equipment of wireless receiving and wireless transmission
Sub- equipment, for receive fall trigger signal or fall pre-warning signal when will be fallen trigger signal by wireless communication link
Or the pre-warning signal that falls is sent to the cloud base station progress data processing of distal end；Display device, it is connected, is used for MSP430 single-chip microcomputers
Show and trigger signal or the corresponding text information of the pre-warning signal that falls of falling；Solar energy detection device, work as detecting in real time
Preceding solar energy intensity；Power supply unit, including solar powered device, battery, switching switch and electric pressure converter, switching are opened
Pass is connected with solar energy detection device, solar powered device and battery respectively, when the dump energy of battery is insufficient and works as
When preceding solar energy intensity is optionally greater than preset strength, solar powered device is switched to be powered by solar powered device,
Electric pressure converter and switching switch connection, so that the 5V voltage conversions of input will be switched by switching as 3.3V voltages, the wherein sun
The energy solar powered device of power supply device includes solar energy photovoltaic panel；Wireless charging device, respectively with solar energy detection device and
Battery connects, when the insufficient and current solar energy intensity of the dump energy of battery is less than preset strength, with neighbouring nothing
Micro USB electric terminals establish connection to start wireless charging operation, and wireless charging device is also connected with electric pressure converter to realize voltage
Conversion；CCD sensing equipments, positioned at the side of sick bed bed board, shot backwards to ward bed side with horizontal shooting direction to obtain high definition
Side image；Gray processing processing equipment, it is connected with CCD sensing equipments, for receiving high definition side image, and to high definition side view
As performing gray processing processing, to obtain gray level image；Contrast strengthens equipment, is connected with gray processing processing equipment, for connecing
Gray level image is received, and contrast enhancement processing is carried out to gray level image, to obtain the first enhancing image；Change of scale strengthens
Equipment, it is connected with contrast enhancing equipment, change of scale increasing is carried out for receiving the first enhancing image, and to the first enhancing image
Strength is managed, to obtain the second enhancing image；Edge strengthens equipment, is connected with change of scale enhancing equipment, increases for receiving second
Strong image, and edge enhancing processing is carried out to the second enhancing image, to obtain the 3rd enhancing image；Image compares equipment, respectively
Connect with edge enhancing equipment, Haar wavelet filterings equipment, Daubechies wavelet filterings equipment and adaptive recursive filtering equipment
Connect, when receiving the 3rd enhancing image from edge enhancing equipment, first start Haar wavelet filterings equipment to the 3rd enhancing image
Processing is filtered to obtain the first filtering image, determine mean square error between the first filtering image and the 3rd enhancing image with
As the first mean square error, when the first mean square error is less than or equal to default square mean error amount, using the first filtering image as mesh
Filtering image output is marked, when the first mean square error is more than default square mean error amount, starts Daubechies wavelet filtering equipment
Processing is filtered to obtain the second filtering image to the 3rd enhancing image, determine the second filtering image and the 3rd enhancing image it
Between mean square error using as the second mean square error, when the second mean square error is less than or equal to default square mean error amount, by second
Filtering image exports as target filtering image, when the second mean square error is more than default square mean error amount, continues to start adaptive
Answer recursive filtering equipment to be filtered processing to the 3rd enhancing image to obtain the 3rd filtering image, determine the 3rd filtering image and
Mean square error between 3rd enhancing image is using as the 3rd mean square error, when the 3rd mean square error is less than or equal to default mean square error
During difference, exported the 3rd filtering image as target filtering image, when the 3rd mean square error is more than default square mean error amount,
Determine the mean square error between the second filtering image and the 3rd enhancing image as the second mean square error, to select the first mean square error
Filtering image in difference, the second mean square error and the 3rd mean square error corresponding to the minimum mean square error of numerical value filters as target
Image exports, and is then turned off Haar wavelet filterings equipment, Daubechies wavelet filterings equipment and adaptive recursive filtering equipment；
Haar wavelet filtering equipment, for being handled using the wavelet filtering based on 2 rank Haar wavelet basis the 3rd enhancing image, to obtain
First filtering image；Daubechies wavelet filtering equipment is small based on 2 rank Daubechies for being used to the 3rd enhancing image
The wavelet filtering processing of ripple base, to obtain the second filtering image；Adaptive recursive filtering equipment, for being held to the 3rd enhancing image
Row adaptive-filtering processing, to obtain the 3rd filtering image；Binary conversion treatment equipment, equipment and static state are deposited compared with image respectively
Equipment connection is stored up, the gray value of each pixel of target filtering image and black and white threshold value are respectively compared, when the gray scale of pixel
When value is more than black and white threshold value, pixel is designated as white pixel, when the gray value of pixel is less than black and white threshold value, pixel is designated as black
Color pixel, so as to obtain binary image；Object detection apparatus, connect respectively with binary conversion treatment equipment and static storage device
Connect, for binary image, calculating the number of each column black picture element, the number of black picture element being more than or equal into threshold number of pixels
Row be designated as edge columns, be additionally operable to binary image, calculate the number of often row black picture element, the number of black picture element is more than
Row equal to threshold number of pixels is designated as edge lines, using the region of edge columns and edge lines intertexture as target domain of the existence, and from
Target domain of the existence is partitioned into binary image to be exported as target subgraph；Target identification equipment, deposited respectively with static state
Storage equipment connects with object detection apparatus, target subgraph is matched with each benchmark human body image, the match is successful then sends out
Go out to have human body signal, it fails to match then sends no human body signal；Spring equipment, it is connected with MSP430 single-chip microcomputers and is arranged on gas
On pad, for receive fall trigger signal when, air cushion is ejected into the side of sick bed from sick bed lower position level, and
Spring operation, which is sent, after the horizontal ejection of air cushion completes signal；Inflator pump, connect respectively with spring equipment, MSP430 single-chip microcomputers and air cushion
Connect, for receive fall trigger signal and receive spring operation complete signal when, according to preset inflation capacity to air cushion
It is inflated；Air cushion, before spring equipment does not receive trigger signal of falling, remain in below sick bed and in contraction-like
State, protected for the human body that fallen after inflation to sick bed；Weight rate detection device, on the downside of sick bed bed board
Face position, including weight detector and timer, weight detector are used to detect the load weight on sick bed bed board, weight in real time
The output of output and timer of the rate of change detection device based on weight detector determines the load weight change on sick bed bed board
Rate, when load weight rate of change is more than default rate of change, weight change pre-warning signal is sent, when load weight rate of change is less than
During equal to default rate of change, weight change normal signal is sent；MSP430 single-chip microcomputers, set respectively with CCD sensing equipments, spring
Standby, weight rate detection device, target identification equipment connect with ultrasonic detecting equipment, when reception weight change pre-warning signal
Afterwards, start CCD sensing equipments, then human body signal be present and when receiving object and skimming over signal receiving, send fall it is tactile
Signal, when receiving no human body signal and receiving object and skim over signal, send the pre-warning signal that falls, and do not receive
Object skims over signal and receives only and human body signal be present, sends the pre-warning signal that falls；Static storage device, for prestoring
Each benchmark human body image, each benchmark human body image are that the benchmark human body of the different bodily forms is shot in advance and obtained
Image, it is additionally operable to prestore default square mean error amount, black and white threshold value, threshold number of pixels and default rate of change.
More specifically, in the cloud computing system：Static storage device is also connected with power supply unit.
More specifically, in the cloud computing system：Static storage device is also connected with wireless charging device.
More specifically, in the cloud computing system：Static storage device is also connected with target identification equipment.
More specifically, in the cloud computing system：Static storage device is also connected with weight rate detection device.
More specifically, in the cloud computing system：MSP430 single-chip microcomputers are integrated in same with static storage device
On surface-mounted integrated circuit.
Brief description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the block diagram of the cloud computing system according to embodiment of the present invention.
Reference：1 ultrasonic listening equipment；2CCD sensing equipments；3 target identification equipments；4 spring equipments；5MSP430
Single-chip microcomputer
Embodiment
The embodiment of the cloud computing system of the present invention is described in detail below with reference to accompanying drawings.
Currently, hospital management side actively takes some measures and patient's falling from bed event is prevented and avoided, such as adds
Gu bed body, increase source of early warning, reduce unmanned nursing time, still, on the one hand these measures and equipment it is excessively simple, detection and
Early warning is inefficient, on the other hand, lacks the urgent rescue equipment that patient body is held up in patient's falling from bed, even if having detected disease
Consequence caused by people's falling from bed event also can not avoid patient's falling from bed, does not provide any help in practice for patient.
In order to overcome above-mentioned deficiency, the present invention has built a kind of cloud computing system, right using existing hospital bed bed body
It carries out structure of modification and upgrading, adds various detection devices and source of early warning and patient's falling from bed event is accurately identified,
It is particularly critical, it also add effective emergency reaction equipment and carry out urgent rescue in patient's falling from bed.
Fig. 1 is the block diagram of the cloud computing system according to embodiment of the present invention, and the platform includes ultrasound
Ripple detecting devices, CCD sensing equipments, target identification equipment, spring equipment and MSP430 single-chip microcomputers, MSP430 single-chip microcomputers respectively with
Ultrasonic listening equipment, CCD sensing equipments, target identification equipment are connected with spring equipment, and target identification equipment is set with CCD sensings
Standby connection, the high definition side image for being shot based on CCD sensing equipments judge that ward bed side whether there is human body, and MSP430 is mono-
Piece machine is used to control spring equipment based on the testing result of target identification equipment and ultrasonic listening equipment.
Then, continue that the concrete structure of the cloud computing system of the present invention is further detailed.
The platform includes：Ultrasonic listening equipment, positioned at the side of sick bed bed board, for having detected whether object from disease
The side of bed bed board is passed through, and when being detected with object and passing through from the side of sick bed bed board, sends object and skim over signal.
The platform includes：Wireless Telecom Equipment, it is connected with MSP430 single-chip microcomputers, including the sub- equipment of wireless receiving and wireless
Send sub- equipment, for receive fall trigger signal or fall pre-warning signal when will be fallen triggering by wireless communication link
The cloud base station that signal or the pre-warning signal that falls are sent to distal end carries out data processing.
The platform includes：Display device, it is connected with MSP430 single-chip microcomputers, trigger signal or is fallen for showing and falling
The corresponding text information of pre-warning signal.
The platform includes：Solar energy detection device, for detecting current solar energy intensity in real time；Power supply unit, bag
Include solar powered device, battery, switching switch and electric pressure converter, switching switch respectively with solar energy detection device, too
Positive energy power supply device connects with battery, when the insufficient and current solar energy intensity of the dump energy of battery is optionally greater than default
During intensity, solar powered device is switched to be powered by solar powered device, electric pressure converter and switching switch connection, with
To be 3.3V voltages by the 5V voltage conversions for switching switch input, wherein solar powered device solar energy electric supplier part includes
Solar energy photovoltaic panel.
The platform includes：Wireless charging device, it is connected respectively with solar energy detection device and battery, when battery
When dump energy is insufficient and current solar energy intensity is less than preset strength, establishes and connected to open with neighbouring wireless charging terminal
Dynamic wireless charging operation, wireless charging device are also connected with electric pressure converter to realize voltage conversion.
The platform includes：CCD sensing equipments, positioned at the side of sick bed bed board, backwards to ward bed side with horizontal shooting side
To shooting to obtain high definition side image；Gray processing processing equipment, it is connected with CCD sensing equipments, for receiving high definition side view
Picture, and gray processing processing is performed to high definition side image, to obtain gray level image.
The platform includes：Contrast strengthens equipment, is connected with gray processing processing equipment, for receiving gray level image,
And contrast enhancement processing is carried out to gray level image, to obtain the first enhancing image；Change of scale strengthens equipment, with contrast
Strengthen equipment connection, change of scale enhancing processing is carried out for receiving the first enhancing image, and to the first enhancing image, to obtain
Second enhancing image；Edge strengthens equipment, be connected with change of scale enhancing equipment, strengthens image for receiving second, and to the
Two enhancing images carry out edge enhancing processing, to obtain the 3rd enhancing image.
The platform includes：Image compares equipment, respectively with edge enhancing equipment, Haar wavelet filterings equipment,
Daubechies wavelet filterings equipment connects with adaptive recursive filtering equipment, strengthens when receiving the 3rd from edge enhancing equipment
During image, first start Haar wavelet filterings equipment and processing is filtered to obtain the first filtering image to the 3rd enhancing image, really
Mean square error between fixed first filtering image and the 3rd enhancing image is using as the first mean square error, when the first mean square error is small
When equal to default square mean error amount, exported the first filtering image as target filtering image, when the first mean square error is more than
During default square mean error amount, start Daubechies wavelet filterings equipment and processing is filtered to the 3rd enhancing image to obtain the
Two filtering images, mean square error between the second filtering image and the 3rd enhancing image is determined using as the second mean square error, when
When second mean square error is less than or equal to default square mean error amount, using the second filtering image as the output of target filtering image, when the
When two mean square errors are more than default square mean error amount, continue to start adaptive recursive filtering equipment and the 3rd enhancing image is filtered
Ripple processing determines mean square error between the 3rd filtering image and the 3rd enhancing image to be used as the to obtain the 3rd filtering image
Three mean square errors, when the 3rd mean square error is less than or equal to default square mean error amount, filtered the 3rd filtering image as target
Image exports, when the 3rd mean square error is more than default square mean error amount, determine the second filtering image and the 3rd enhancing image it
Between mean square error as the second mean square error, to select in the first mean square error, the second mean square error and the 3rd mean square error
Filtering image corresponding to the minimum mean square error of numerical value exports as target filtering image, is then turned off Haar wavelet filterings and sets
Standby, Daubechies wavelet filterings equipment and adaptive recursive filtering equipment.
The platform includes：Haar wavelet filtering equipment, 2 rank Haar wavelet basis are based on for being used to the 3rd enhancing image
Wavelet filtering processing, to obtain the first filtering image.
The platform includes：Daubechies wavelet filtering equipment, 2 ranks are based on for being used to the 3rd enhancing image
The wavelet filtering processing of Daubechies wavelet basis, to obtain the second filtering image.
The platform includes：Adaptive recursive filtering equipment, for performing adaptive-filtering processing to the 3rd enhancing image,
To obtain the 3rd filtering image；Binary conversion treatment equipment, equipment and static storage device connection compared with image respectively, by target
The gray value of each pixel of filtering image is respectively compared with black and white threshold value, when the gray value of pixel is more than black and white threshold value,
Pixel is designated as white pixel, when the gray value of pixel is less than black and white threshold value, pixel is designated as black picture element, so as to obtain two
Value image.
The platform includes：Object detection apparatus, it is connected, is used for binary conversion treatment equipment and static storage device respectively
To binary image, the number of each column black picture element is calculated, row of the number of black picture element more than or equal to threshold number of pixels are remembered
For edge columns, it is additionally operable to calculate binary image the number of often row black picture element, the number of black picture element is more than or equal to picture
The row of prime number threshold value is designated as edge lines, and the region that edge columns and edge lines are interweaved is as target domain of the existence, and from binaryzation
Target domain of the existence is partitioned into image to be exported as target subgraph.
The platform includes：Target identification equipment, it is connected respectively with static storage device and object detection apparatus, by target
Subgraph is matched with each benchmark human body image, and the match is successful then sends and human body signal be present, and it fails to match then sends nothing
Human body signal.
The platform includes：Spring equipment, it is connected and is arranged on air cushion with MSP430 single-chip microcomputers, for is receiving pendant
When falling trigger signal, air cushion is ejected into the side of sick bed from sick bed lower position level, and sent after the horizontal ejection of air cushion
Signal is completed in spring operation.
The platform includes：Inflator pump, it is connected respectively with spring equipment, MSP430 single-chip microcomputers and air cushion, for receiving
To fall trigger signal and receive spring operation complete signal when, air cushion is inflated according to preset inflation capacity；Air cushion,
Before spring equipment does not receive trigger signal of falling, remain in below sick bed and be in contraction state, for inflating
After the human body that fallen to sick bed protect.
The platform includes：Weight rate detection device, positioned at sick bed bed board downside position, including weight detector
And timer, weight detector are used to detect the load weight on sick bed bed board in real time, weight rate detection device is based on weight
The load weight rate of change in the output of detector and the output determination sick bed bed board of timer is measured, when load weight rate of change is big
When default rate of change, weight change pre-warning signal is sent, when load weight rate of change is less than or equal to default rate of change, is sent
Weight change normal signal.
The platform includes：MSP430 single-chip microcomputers, set respectively with CCD sensing equipments, spring equipment, weight rate detection
Standby, target identification equipment connects with ultrasonic detecting equipment, after weight change pre-warning signal is received, starts CCD sensing equipments,
Then human body signal be present and when receiving object and skimming over signal receiving, send trigger signal of falling, receiving nobody
Body signal and when receiving object and skimming over signal, sends the pre-warning signal that falls, and do not receive object and skim over signal and only connect
Receive and human body signal be present, send the pre-warning signal that falls.
The platform includes：Static storage device, for having prestored each benchmark human body image, each benchmark human body
Image is additionally operable to prestore default mean square error to be shot the image obtained in advance to the benchmark human body of the different bodily forms
Value, black and white threshold value, threshold number of pixels and default rate of change.
Alternatively, in the platform：Static storage device is also connected with power supply unit；Static storage device also with wirelessly
Charging equipment connects；Static storage device is also connected with target identification equipment；Static storage device also detects with weight rate
Equipment connects；And MSP430 single-chip microcomputers are integrated on same surface-mounted integrated circuit with static storage device.
In addition, wave filter, is the device filtered to ripple as its name suggests." ripple " is that a very extensive physics is general
Read, in electronic technology field, the value that " ripple " is narrowly confined to refer in particular to describe various physical quantitys is with time fluctuations
Process.The process is converted into the function of time of voltage or electric current, referred to as various physical quantitys by the effect of various kinds of sensors
Time waveform, or referred to as signal.Because the independent variable time is continuous value, referred to as continuous time signal,
Habitually it is referred to as analog signal again.
With the generation and rapid development of digital electronic computer technology, for the ease of computer to signal at
Reason, generate the complete theoretical and method that continuous time signal is transformed into discrete-time signal under sampling theorem guidance.
That is, primary signal only can be expressed without losing with sample value of the original analog signal on series of discrete time coordinate point
Lose any information since the expression of ripple, waveform, signal these concepts be various physical quantitys in objective world change, naturally
It is the carrier for the various information that modern society depends on for existence.Information needs to propagate, and what is leaned on is exactly the transmission of waveform signal.Signal exists
Its generation, conversion, each link of transmission may be distorted due to the presence of environment and interference, even quite a lot of
In the case of, this distortion is also very serious, causes signal and its entrained information to be embedded in dearly among noise.In order to
These noises are filtered out, recover the signal of script, it is necessary to be filtered processing using various wave filters.
Can not be that the patient to be fallen from sick bed is promptly rescued for prior art using the cloud computing system of the present invention
The technical problem of shield, testing result comprehensive analysis is carried out by adding high-precision multiple detection devices, effectively to judge patient
Whether fall, be additionally added necessary warning device and alarmed, at the same be also added into special emergency reaction equipment with
Urgent rescue is carried out when patient falls, avoids patient because falling from bed comes to harm.
It is understood that although the present invention is disclosed as above with preferred embodiment, but above-described embodiment and it is not used to
Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications are all made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (6)
1. a kind of cloud computing system, including using cloud base station as the platform supported, the platform includes ultrasonic listening equipment, CCD
Sensing equipment, target identification equipment, spring equipment and MSP430 single-chip microcomputers, MSP430 single-chip microcomputers are set with ultrasonic listening respectively
Standby, CCD sensing equipments, target identification equipment are connected with spring equipment, and target identification equipment is connected with CCD sensing equipments, is used for
High definition side image based on the shooting of CCD sensing equipments judges that ward bed side whether there is human body, and MSP430 single-chip microcomputers are used for base
Spring equipment is controlled in the testing result of target identification equipment and ultrasonic listening equipment；
Characterized in that, the platform also includes：
Ultrasonic listening equipment, positioned at the side of sick bed bed board, for detecting whether that object passes through from the side of sick bed bed board,
And when being detected with object and passing through from the side of sick bed bed board, send object and skim over signal；
Wireless Telecom Equipment, be connected with MSP430 single-chip microcomputers, including the sub- equipment of wireless receiving and transmit wirelessly sub- equipment, for
Receive fall trigger signal or fall pre-warning signal when believed by will fall trigger signal or early warning of falling of wireless communication link
The cloud base station for number being sent to distal end carries out data processing；
Display device, be connected with MSP430 single-chip microcomputers, for show with fall trigger signal or the pre-warning signal that falls it is corresponding literary
Word information；
Solar energy detection device, for detecting current solar energy intensity in real time；
Power supply unit, including solar powered device, battery, switching switch and electric pressure converter, switching switch respectively with too
Positive energy detection device, solar powered device connect with battery, when the solar energy that the dump energy of battery is insufficient and current
When intensity is optionally greater than preset strength, solar powered device is switched to be powered by solar powered device, electric pressure converter
Connected with switching switch, using the 5V voltage conversions by input is switched by switching as 3.3V voltages, wherein solar powered device
Solar powered device includes solar energy photovoltaic panel；
Wireless charging device, it is connected respectively with solar energy detection device and battery, when the dump energy of battery is insufficient and works as
When preceding solar energy intensity is less than preset strength, establishes and connected to start wireless charging operation with neighbouring wireless charging terminal,
Wireless charging device is also connected with electric pressure converter to realize voltage conversion；
CCD sensing equipments, positioned at the side of sick bed bed board, shot backwards to ward bed side with horizontal shooting direction to obtain high definition side
Face image；
Gray processing processing equipment, it is connected with CCD sensing equipments, is held for receiving high definition side image, and to high definition side image
Row gray processing processing, to obtain gray level image；
Contrast strengthens equipment, is connected with gray processing processing equipment, is carried out for receiving gray level image, and to gray level image
Contrast enhancement processing, to obtain the first enhancing image；
Change of scale strengthens equipment, is connected with contrast enhancing equipment, schemes for receiving the first enhancing image, and to the first enhancing
As carrying out change of scale enhancing processing, to obtain the second enhancing image；
Edge strengthens equipment, is connected with change of scale enhancing equipment, for receiving the second enhancing image, and to the second enhancing image
Edge enhancing processing is carried out, to obtain the 3rd enhancing image；
Image compares equipment, respectively with edge enhancing equipment, Haar wavelet filterings equipment, Daubechies wavelet filterings equipment and
Adaptive recursive filtering equipment connection, when receiving the 3rd enhancing image from edge enhancing equipment, first start the filter of Haar small echos
Wave device is filtered processing to obtain the first filtering image to the 3rd enhancing image, determines the first filtering image and the 3rd enhancing
Mean square error between image is using as the first mean square error, when the first mean square error is less than or equal to default square mean error amount,
Export the first filtering image as target filtering image, when the first mean square error is more than default square mean error amount, start
Daubechies wavelet filterings equipment is filtered processing to obtain the second filtering image to the 3rd enhancing image, determines the second filter
Mean square error between ripple image and the 3rd enhancing image using as the second mean square error, when the second mean square error be less than or equal to it is pre-
If during square mean error amount, exported the second filtering image as target filtering image, when the second mean square error is square more than default
During error amount, continue to start adaptive recursive filtering equipment and processing is filtered to obtain the 3rd filtering figure to the 3rd enhancing image
Picture, mean square error between the 3rd filtering image and the 3rd enhancing image is determined using as the 3rd mean square error, when the 3rd square
When error is less than or equal to default square mean error amount, exported the 3rd filtering image as target filtering image, when the 3rd mean square error
When difference is more than default square mean error amount, determine the mean square error between the second filtering image and the 3rd enhancing image to be used as second
Mean square error, select the mean square error institute that numerical value is minimum in the first mean square error, the second mean square error and the 3rd mean square error right
The filtering image answered exports as target filtering image, is then turned off Haar wavelet filterings equipment, Daubechies wavelet filterings
Equipment and adaptive recursive filtering equipment；
Haar wavelet filtering equipment, for being handled using the wavelet filtering based on 2 rank Haar wavelet basis the 3rd enhancing image, with
Obtain the first filtering image；
Daubechies wavelet filtering equipment, for using the 3rd enhancing image based on the small of 2 rank Daubechies wavelet basis
Ripple filtering process, to obtain the second filtering image；
Adaptive recursive filtering equipment, for performing adaptive-filtering processing to the 3rd enhancing image, schemed with obtaining the 3rd filtering
Picture；
Binary conversion treatment equipment, equipment and static storage device connection compared with image respectively, by each of target filtering image
The gray value of individual pixel is respectively compared with black and white threshold value, and when the gray value of pixel is more than black and white threshold value, pixel is designated as into white
Pixel, when the gray value of pixel is less than black and white threshold value, pixel is designated as black picture element, so as to obtain binary image；
Object detection apparatus, it is connected respectively with binary conversion treatment equipment and static storage device, for binary image, calculating
The number of each column black picture element, the row that the number of black picture element is more than or equal to threshold number of pixels are designated as edge columns, are additionally operable to pair
Binary image, the number of often row black picture element is calculated, the row that the number of black picture element is more than or equal to threshold number of pixels is designated as
Edge lines, the region that edge columns and edge lines are interweaved are partitioned into target as target domain of the existence from binary image
Domain of the existence as target subgraph to export；
Target identification equipment, it is connected respectively with static storage device and object detection apparatus, by target subgraph and each benchmark
Human body image is matched, and the match is successful then sends and human body signal be present, and it fails to match then sends no human body signal；
Spring equipment, be connected and be arranged on air cushion with MSP430 single-chip microcomputers, for receive fall trigger signal when, by gas
Pad is ejected into the side of sick bed from sick bed lower position level, and sends spring operation after the horizontal ejection of air cushion and complete signal；
Inflator pump, it is connected respectively with spring equipment, MSP430 single-chip microcomputers and air cushion, for trigger signal and connecing receiving to fall
When receiving spring operation completion signal, air cushion is inflated according to preset inflation capacity；
Air cushion, before spring equipment does not receive trigger signal of falling, remain in below sick bed and be in contraction state, use
Protected in the human body that fallen after inflation to sick bed；
Weight rate detection device, positioned at sick bed bed board downside position, including weight detector and timer, weight detecting
Instrument is used to detect the load weight on sick bed bed board, output and meter of the weight rate detection device based on weight detector in real time
When device output determine load weight rate of change on sick bed bed board, when load weight rate of change is more than default rate of change, hair
Go out weight change pre-warning signal, when load weight rate of change is less than or equal to default rate of change, send weight change normal signal；
MSP430 single-chip microcomputers, respectively with CCD sensing equipments, spring equipment, weight rate detection device, target identification equipment and
Ultrasonic detecting equipment connects, and after weight change pre-warning signal is received, starts CCD sensing equipments, is then receiving presence
Human body signal and when receiving object and skimming over signal, sends trigger signal of falling, is receiving no human body signal and receiving thing
When part skims over signal, the pre-warning signal that falls is sent, and does not receive object and skims over signal and receive only and human body signal be present,
Send the pre-warning signal that falls；
Static storage device, for having prestored each benchmark human body image, each benchmark human body image is to the different bodily forms
The benchmark human body image that is shot and obtained in advance, be additionally operable to prestore default square mean error amount, black and white threshold value, pixel
Number threshold value and default rate of change.
2. cloud computing system as claimed in claim 1, it is characterised in that：
Static storage device is also connected with power supply unit.
3. cloud computing system as claimed in claim 1, it is characterised in that：
Static storage device is also connected with wireless charging device.
4. cloud computing system as claimed in claim 1, it is characterised in that：
Static storage device is also connected with target identification equipment.
5. cloud computing system as claimed in claim 1, it is characterised in that：
Static storage device is also connected with weight rate detection device.
6. cloud computing system as claimed in claim 1, it is characterised in that：
MSP430 single-chip microcomputers are integrated on same surface-mounted integrated circuit with static storage device.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711318975.9A CN108030608A (en) | 2016-05-24 | 2016-05-24 | A kind of sick bed |
| CN201610351290.3A CN105943273B (en) | 2016-05-24 | 2016-05-24 | Cloud computing system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201610351290.3A CN105943273B (en) | 2016-05-24 | 2016-05-24 | Cloud computing system |
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| CN201711318975.9A Division CN108030608A (en) | 2016-05-24 | 2016-05-24 | A kind of sick bed |
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| CN105943273A CN105943273A (en) | 2016-09-21 |
| CN105943273B true CN105943273B (en) | 2018-01-09 |
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| CN201610351290.3A Active CN105943273B (en) | 2016-05-24 | 2016-05-24 | Cloud computing system |
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| Application Number | Title | Priority Date | Filing Date |
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| CN107257530A (en) * | 2017-06-06 | 2017-10-17 | 余姚德诚科技咨询有限公司 | Intelligent police car loudspeaker |
| CN107871383A (en) * | 2017-08-01 | 2018-04-03 | 刘太龙 | A kind of electronic security(ELSEC) support method based on communication |
| CN109686435B (en) * | 2019-01-08 | 2020-04-03 | 王海燕 | Self-adaptive medical treatment platform |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2000042052A (en) * | 1998-07-31 | 2000-02-15 | Denso Corp | Nursing care bed |
| SG121905A1 (en) * | 2004-10-26 | 2006-05-26 | Ngee Ann Polytechnic | Occupant monitoring and alert system |
| US7487562B2 (en) * | 2005-11-30 | 2009-02-10 | Hill-Rom Services, Inc. | Hospital bed having head angle alarm |
| JP4514717B2 (en) * | 2006-01-20 | 2010-07-28 | パラマウントベッド株式会社 | A bed apparatus equipped with a bed prediction and detection system |
| JP2007289251A (en) * | 2006-04-21 | 2007-11-08 | Ibaraki Pref Gov Kosei Nogyo Kyodo Kumiai Rengokai | Falling prevention bed |
| CN101313877A (en) * | 2008-05-07 | 2008-12-03 | 上海理工大学 | Intellectual nursing bed with anti-drop function |
| CN101697935B (en) * | 2009-06-07 | 2012-07-04 | 周秋来 | Intelligent and ecological healthy sleep system |
| US9060913B2 (en) * | 2013-03-15 | 2015-06-23 | H & M Innovations, Llc | Surgical table magnetic instrument holder |
| CN103973952A (en) * | 2014-05-15 | 2014-08-06 | 深圳市唯特视科技有限公司 | Four-dimensional human body recognition device |
| CN104732726B (en) * | 2015-04-16 | 2016-04-20 | 河南职业技术学院 | Visitor waterborne identifies monitor supervision platform |
| CN105488955A (en) * | 2015-12-11 | 2016-04-13 | 哈尔滨墨医生物技术有限公司 | A security alarm system for wards |
| CN205214795U (en) * | 2015-12-16 | 2016-05-11 | 四川华象林产工业有限公司 | Intelligent child bed |
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| CN105943273A (en) | 2016-09-21 |
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