CN113395661B - Indoor positioning system based on deep neural network - Google Patents
Indoor positioning system based on deep neural network Download PDFInfo
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- CN113395661B CN113395661B CN202110737987.5A CN202110737987A CN113395661B CN 113395661 B CN113395661 B CN 113395661B CN 202110737987 A CN202110737987 A CN 202110737987A CN 113395661 B CN113395661 B CN 113395661B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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Abstract
The invention discloses an indoor positioning system based on a deep neural network, wherein a positioning force arm is connected below a system box in a penetrating manner, a signal box is fixedly welded in the middle of the system box, and a rotating shaft is connected outside the signal box in a penetrating manner; and one side electric wire of the signal transmitter is connected with a signal data line, and the upper surface of the alloy bracket is provided with a rectangular sliding groove. The indoor positioning system based on the deep neural network; the vertical force arm and the ball screw are adopted, the ball screw is used for carrying out vertical ascending or descending treatment on the vertical force arm, and the height of the vertical force arm is adjusted according to the height of a building and the requirement of ground navigation.
Description
Technical Field
The invention relates to the technical field of indoor positioning, in particular to an indoor positioning system based on a deep neural network.
Background
In an outdoor environment, a global positioning system or a beidou satellite positioning system based on a global satellite navigation system can already meet certain outdoor positioning requirements, however, in an indoor environment, especially in a complex indoor environment such as an airport lobby, an exhibition hall, a mine and the like, the position information of a mobile terminal or a holder thereof, facilities and articles in the indoor environment is often required to be determined, but due to the problem that the existing positioning mode is limited by the conditions such as positioning time, positioning accuracy, the complex indoor environment and the like, the existing positioning mode is not perfect.
The indoor positioning system is generally a scattered signal emitter, and in the using process, only some important exits or departments can be guided and positioned, in the actual using process, the system is difficult to adjust the distance of the emitter of the positioning system according to the height of a building and the width of a corridor, so that in the using process of the positioning system, the accuracy of signal conduction and indoor positioning is not favorable for guiding and positioning in the large building, and the general navigation system can only provide signal transmission for the networking system, but the mobile system which cannot be networked cannot read some information, so that in the using process, the navigation function of the system is weaker.
In order to solve the problems, innovative design is urgently needed on the basis of the original indoor positioning structure.
Disclosure of Invention
The invention aims to provide an indoor positioning system based on a deep neural network, and aims to solve the problem that the system provided in the background technology is difficult to adjust the distance of a transmitter of the positioning system according to the height of a building and the width of a corridor, a general navigation system can only provide signal transmission for a networking system, but a mobile system which cannot be networked cannot read some information, and therefore the system navigation function is weak in the using process.
In order to achieve the purpose, the invention provides the following technical scheme: the invention discloses an indoor positioning system based on a deep neural network, wherein a positioning force arm is connected below a system box in a penetrating manner, a signal box is fixedly welded in the middle of the system box, and a rotating shaft is connected outside the signal box in a penetrating manner; the signal emitter is arranged in the alloy bracket, an electric wire at one side of the signal emitter is connected with a signal data wire, the upper surface of the alloy bracket is provided with a rectangular sliding chute, and a lifting panel is connected above the rectangular sliding chute in a nested manner; the positioning server is arranged in the system box body, a gauze panel is fixed right above the system box body through a bolt, and an electric wire at one side of the positioning server is connected with a communication module a; the outer side of the rotating shaft is installed on the conical gear, a ball screw is connected to the position right below the conical gear, a b communication module is fixed to one side of the alloy support through a bolt, and a guide sliding rod is connected to the outer side of the alloy support in a nested mode.
Preferably, the system box and the alloy support are in through connection, and the width of the alloy support is 3 times of the width of the lifting panel.
Preferably, the signal emitter and the lifting panel form a sliding structure through an alloy support and a rectangular sliding groove, the alloy supports are distributed at the bottom of the system box in a staggered mode, and the distance between the 2 combined gold supports ranges from 5 m to 10m.
Preferably, the positioning server is connected with the signal emitter through a communication module and a signal data line, and the signal emitter is mutually attached to the lifting panel.
Preferably, the rectangular sliding groove is connected with the lifting panel in a nested manner, the longitudinal section of the lifting panel is of an L-shaped structure, and a groove-shaped structure is arranged right above the lifting panel.
Preferably, the electronic tag and the lifting box body form a lifting structure through a vertical force arm, a ball screw and a guide slide rod, the longitudinal section of the vertical force arm is of a U-shaped structure, and the vertical force arm and the lifting box body are fixedly welded.
Compared with the prior art, the invention has the beneficial effects that: the indoor positioning system based on the deep neural network;
1. the vertical force arm and the ball screw are adopted, the ball screw is used for vertically ascending or descending the vertical force arm, the height of the vertical force arm is adjusted according to the height of a building and the requirement of ground navigation, the stability of the vertical force arm in the positioning and locking process is improved, the top of the lifting box body is hoisted through the ball screw, the situation that the lifting box body shakes in the signal transmission process is avoided, and the length of the lifting box body is changed and switched according to the length of a corridor;
2. adopt to lift panel and rectangle spout, utilize to lift the panel and lift the top of signal transmitter and shorten, according to the width of signal transmitter's width and the width in corridor, adjust the distance between the signal transmitter, utilize signal transmitter to conduct the signal of peripheral shop and access & exit, it is fixed to utilize the rectangle spout to lead to the bottom of lifting the panel, avoids between the signal transmitter apart from too big, influences the accuracy of signal in transmission process.
Drawings
FIG. 1 is a schematic front view of the present invention;
FIG. 2 is a schematic diagram of the internal structure of the system housing of the present invention;
FIG. 3 is a schematic top view of the system housing of the present invention;
FIG. 4 is a schematic bottom view of the lift chamber of the present invention;
FIG. 5 is a schematic diagram of the internal structure of the signal box of the present invention.
In the figure: 1. a system box body; 2. positioning a force arm; 3. a signal box body; 4. a rotating shaft; 5. lifting the box body; 6. a signal transmitter; 7. lifting the panel; 8. an alloy support; 9. a communication module; 10. a positioning server; 11. a signal data line; 12. a rectangular chute; 13. a screen panel; 14. an electronic tag; 15. an LED lamp; 16. a vertical force arm; 17. a bevel gear; 18. a ball screw; 19. b, a communication module; 20. and guiding the sliding rod.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution: the utility model provides an indoor positioning system based on degree of depth neural network, the system box 1 is running through under to be connected with the location arm of force 2, and the middle part welded fastening of system box 1 has signal box 3, and the outside running through of signal box 3 is connected with rotation axis 4, includes:
the LED lamp 15 is connected to the right lower portion of the lifting box body 5, the electronic tags 14 are arranged on the left side and the right side of the LED lamp 15, the vertical force arm 16 is fixedly welded to the right upper portion of the lifting box body 5, the guide sliding rod 20 is connected to the outer side of the vertical force arm 16 in a nested mode, and the ball screw 18 is connected to the outer side of the vertical force arm 16 in a threaded mode;
the signal emitter 6 is arranged inside the alloy support 8, a signal data line 11 is connected to an electric wire on one side of the signal emitter 6, a rectangular sliding groove 12 is formed in the upper surface of the alloy support 8, and the lifting panel 7 is connected to the position right above the rectangular sliding groove 12 in a nested mode;
the positioning server 10 is installed inside the system box body 1, a gauze panel 13 is fixed on the right upper part of the system box body 1 through bolts, and one side of the positioning server 10 is connected with the communication module a 9 through wires;
and a conical gear 17 which is installed on the outer side of the rotating shaft 4, a ball screw 18 is connected right below the conical gear 17, a b communication module 19 is fixed on one side of the alloy bracket 8 through a bolt, and a guide slide rod 20 is connected on the outer side of the alloy bracket 8 in a nested mode.
The system box body 1 and the alloy bracket 8 are in through connection, and the width of the alloy bracket 8 is 3 times of that of the lifting panel 7.
The signal emitter 6 and the lifting panel 7 form a sliding structure through an alloy bracket 8 and a rectangular sliding chute 12, the alloy brackets 8 are distributed at the bottom of the system box body 1 in a staggered mode, and the distance range between the 2 combined gold brackets 8 is 5-10m.
The positioning server 10 is connected with the signal emitter 6 through the a communication module 9 and the signal data line 11, and the signal emitter 6 is mutually attached to the lifting panel 7.
The rectangular sliding groove 12 is connected with the lifting panel 7 in a nested manner, the longitudinal section of the lifting panel 7 is of an L-shaped structure, and a groove-shaped structure is arranged right above the lifting panel 7.
The electronic tag 14 and the lifting box body 5 form a lifting structure through a vertical force arm 16, a ball screw 18 and a guide slide rod 20, the longitudinal section of the vertical force arm 16 is of a U-shaped structure, and the vertical force arm 16 and the lifting box body 5 are fixedly welded.
The working principle is as follows: when the indoor positioning system based on the deep neural network is used, according to the drawing 1, the device is firstly placed at a position needing to work, an operator firstly attaches the signal emitter 6 and the lifting panel 7 to each other according to the length of a building and the requirement of signal transmission, pulls the lifting panel 7 to enable the lifting panel 7 to slide on the outer side of the rectangular sliding groove 12, adjusts the position of the signal emitter 6, attaches the positioning force arm to the top of a wall, fixes and limits the system box body 1 and the positioning force arm 2 by using an expansion screw, installs the corresponding a communication module 9 and the positioning server 10 in the system box body 1, installs the signal data line 11 at the output end of the positioning server 10, connects the signal emitter 6 by using the signal data line 11 respectively, and conducts the received signals by using the signal data line 11;
the rotating shaft 4 is held, the rotating shaft 4 is utilized to drive the conical gear 17 to rotate, the conical gear 17 drives the ball screw 18 on one side to rotate, the ball screw 18 is utilized to drive the vertical force arm 16 on one side to vertically descend, the height of the lifting box body 5 is driven to be adjusted through the vertical force arm 16, different specific position information is led into the electronic tag 14, the electronic tag 14 is installed right below the lifting box body 5, and spatial coupling of radio frequency signals is achieved between the electronic tag 14 and a reader through a coupling element; in the coupling channel, according to the time sequence relation, the transmission of energy and data exchange are realized, and an operator can directly read the electronic tag 14 through a reader and know the corresponding position. The overall practicability is increased.
Those not described in detail in this specification are well within the skill of the art.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. The utility model provides an indoor positioning system based on degree of depth neural network, contains system box (1), and there is the location arm of force (2) through connection under system box (1), and the middle part welded fastening of system box (1) has signal box (3), the outside through connection of signal box (3) has rotation axis (4), its characterized in that: the method comprises the following steps:
the LED lamp lifting device comprises a lifting box body (5), wherein an LED lamp (15) is connected to the right lower portion of the lifting box body (5), electronic tags (14) are arranged on the left side and the right side of the LED lamp (15), a vertical force arm (16) is fixedly welded to the right upper portion of the lifting box body (5), a guide sliding rod (20) is connected to the outer side of the vertical force arm (16) in a nested mode, and a ball screw (18) is connected to the outer side of the vertical force arm (16) in a threaded mode;
the signal emitter (6) is installed inside the alloy support (8), an electric wire on one side of the signal emitter (6) is connected with a signal data wire (11), a rectangular sliding groove (12) is formed in the upper surface of the alloy support (8), and a lifting panel (7) is connected to the position right above the rectangular sliding groove (12) in a nested mode;
the positioning server (10) is installed inside the system box body (1), a gauze panel (13) is fixed on the right upper side of the system box body (1) through bolts, and an a communication module (9) is connected with one side of the positioning server (10) through an electric wire;
the conical gear (17) is installed on the outer side of the rotating shaft (4), a ball screw (18) is connected to the position right below the conical gear (17), a b communication module (19) is fixed to one side of the alloy support (8) through a bolt, and a guide sliding rod (20) is connected to the outer side of the alloy support (8) in a nested mode;
the signal emitter (6) and the lifting panel (7) form a sliding structure through an alloy support (8) and a rectangular sliding chute (12), the alloy supports (8) are distributed at the bottom of the system box body (1) in a staggered mode, and the distance between the 2 combinations Jin Zhijia (8) is 5-10m;
the electronic tag (14) and the lifting box body (5) form a lifting structure through a vertical force arm (16), a ball screw (18) and a guide slide rod (20), the longitudinal section of the vertical force arm (16) is of a U-shaped structure, and the vertical force arm (16) and the lifting box body (5) are fixedly welded.
2. The deep neural network-based indoor positioning system of claim 1, wherein: the system box body (1) is in through connection with the alloy support (8), and the width of the alloy support (8) is 3 times of that of the lifting panel (7).
3. The deep neural network-based indoor positioning system of claim 1, wherein: the positioning server (10) is connected with the signal emitter (6) through a communication module (9) and a signal data line (11), and the signal emitter (6) is mutually attached to the lifting panel (7).
4. The deep neural network-based indoor positioning system of claim 1, wherein: the rectangular sliding groove (12) is connected with the lifting panel (7) in a nested mode, the longitudinal section of the lifting panel (7) is of an L-shaped structure, and a groove-shaped structure is arranged right above the lifting panel (7).
5. The deep neural network-based indoor positioning system of claim 1, wherein: the working method of the system comprises the following steps: firstly, the indoor positioning system is placed at a position needing to work, an operator firstly attaches a signal transmitter (6) and a lifting panel (7) to each other according to the length of a building and the requirement of signal transmission, pulls the lifting panel (7) to enable the lifting panel (7) to slide on the outer side of a rectangular sliding groove (12), adjusts the position of the signal transmitter (6), attaches a positioning force arm to the top of a wall, fixes and limits a system box body (1) and a positioning force arm (2) by using an expansion screw, installs a corresponding communication module (a) and a corresponding positioning server (10) inside the system box body (1), installs the communication module at the output end of the positioning server (10) by using a signal data line (11), connects the signal transmitter (6) by using the signal data line (11) respectively, and conducts and processes received signals by using the signal data line (11);
the rotating shaft (4) is held, the rotating shaft (4) is utilized to drive the conical gear (17) to rotate, the conical gear (17) drives the ball screw (18) on one side to rotate, the ball screw (18) drives the vertical force arm (16) on one side to vertically descend, the vertical force arm (16) drives the lifting box body (5) to adjust the height, different specific position information is led into the electronic tag (14), the electronic tag (14) is installed under the lifting box body (5), and the electronic tag (14) and a reader are spatially coupled through a coupling element to realize radio-frequency signals; in the coupling channel, energy transfer and data exchange are realized according to a time sequence relation, and an operator can directly read the electronic tag (14) through a reader.
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| CN202110737987.5A CN113395661B (en) | 2021-06-30 | 2021-06-30 | Indoor positioning system based on deep neural network |
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| CN202110737987.5A CN113395661B (en) | 2021-06-30 | 2021-06-30 | Indoor positioning system based on deep neural network |
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