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Intelligent transport system with traffic management
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My patents are aimed to improve: quality of products, quality of services and safety of our environment.
The patent listed for sale, is my first one… You can view it details using a number of search engines, including Google:
Link
Please review attached copy of claims. There is an interesting link Link
which is listing other patents in this category…
More information in the next chapter...
Financial information
In respect to purchasing the patent, please note, that the process of re-assigning the patent to a buyer will take 3-4 weeks by the USPTO.
My patent portfolio is diversified. I am interested in selling this patent, or licensing its use. Open-minded, as I truly believe this patent can be important for a number of applications delivering superior quality of products and services.
For the right buyer – the patent could generate an astronomical ROI!
In general, the patent is about a system (apparatus) consisting of four major components: controller, sensors, track and object.
Controller includes 2 modes of operation:
1 – learning a process acceptance criteria, as function of the process and ambient environment
2 – maintaining the process within the acceptance criteria
Sensors include:
1 - ID readers (barcode, etc.)
2 - optical (photo-detectors, HD cameras, etc.)
3 - weight
Track includes:
1 - passive (ground, water, air) allowing active objects to advance along the track
2 – active (conveyor, etc.) advancing objects along the track
Object include:
1 – active (vehicle, airplane, boat, etc.), capable of advancing along a track
2 – passive (box, bottle, etc.), being advanced by a track
The acceptance criteria (predefined acceptance range) include:
1 – object identification (barcode, etc.)
2 – object physical shape (overall dimensions, specific dimension, etc.)
3 – object weight
4 – object motion parameters (direction, speed, etc.)
5 – traffic motion parameters (direction, speed, distance in-between objects, etc.)
EXAMPLE: Application #1 – automatic conveyor system of filling specified bottles to required level, transporting bottles at a maximum speed, and delivering the required quality bottles filled with liquid to specified destination on the conveyor
Controller – combination of a host computer and distributed networked embedded controllers, interfaced to: sensors along the track and to actuators controlling the conveyor
Sensors include - optical sensors positioned along the track to detect presence of a bottle, and level of liquid inside the bottle, motion parameters of the conveyor
Track - active conveyor with sections including: loading, liquid filling, inspection, rejection, unloading.
Object – passive bottle
Controller LEARNING mode of operation:
1) Bottles filled with liquid representing minimum and maximum acceptable levels are loaded onto conveyor
2) Conveyor is activated to advance the bottles at acceptable motion parameters, including minimum speed, distance between bottles
3) Controller will monitor sensors along he track and record process parameters, including dimensions of the bottle, level of liquid in the bottle, speed of moving bottle, distance between bottles
4) Conveyor is activated to advance the bottles at acceptable maximum speed
5) Controller will monitor sensors along he track and record process parameters as in (3)
6) Controller will analyze recorded data obtained (3,5) and generate process acceptance criteria
Controller SYSTEM mode of operation:
a) Empty bottles are placed on conveyor
b) Bottles outside acceptable physical shape are rejected
NOTE: Rejected bottles are either corrected to meet acceptable criteria or removed from the conveyor
c) Conveyor is advanced by controller at the speed within the acceptance range, while sustaining process acceptance criteria (6)
d) At the filling station each bottle will be filled with liquid to acceptance level
e) At the inspection station - bottles outside the acceptance range (size, weight, liquid level) will be diverted to a reject track for a corrective process
f) Filled bottles in compliance with the process acceptable criteria (6) are removed from the conveyor at the unloading station
EXAMPLE: Application #2 – transporting identified driverless vehicles along a track at maximum speed and within acceptable safety criteria
Controller – combination of a host computer and distributed networked embedded controllers, embedded into each vehicle
Sensors include – identification sensors; weight sensors; optical sensors positioned along the track to detect presence of a vehicle on the track, and respective motion parameters of each vehicle on the track (direction, speed, distance in-between, etc.)
Track – passive road
Object – driverless vehicle with on-board embedded controllers networked to the host controller
Controller LEARNING mode of operation:
1) Arrange identified vehicles along the track per desired motion parameters: orientation in direction of motion, distance in-between
2) Controller will monitor: identification sensors; sensors along the track and record process parameters, including: dimensions and weight of each vehicle; vehicle orientation
3) Begin advancing vehicles along the track at desired minimum speed while maintaining minimum desired distance in-between
4) Controller will monitor sensors along he track and record process parameters, including direction, speed and distance in-between vehicles
5) Repeat (3,4) at desired maximum speed
6) Repeat (3,4) at desired maximum distance in-between vehicles
7) Repeat (3,4) at desired maximum speed and maximum distance in-between vehicles
8) Controller will analyze recorded data obtained (3-7) and generate process acceptance criteria
Controller SYSTEM mode of operation:
a) Align vehicles at a starting point on the track
b) Controller will verify if vehicles are within the acceptable range in terms of: identity, size, weight, orientation, and reject the ones out of compliance
NOTE: Rejected vehicle is either corrected to meet acceptable criteria or removed from the track
c) Controller over network will instruct each vehicle embedded controller to begin advancing respective vehicle in specified direction and speed
d) Controller will in real-time monitor sensors and adjust controls of each vehicle to maintain the traffic of vehicles within process acceptance criteria (8)
The acceptance criteria (predefined acceptance range) include:
1 – vehicle identification
2 – vehicle physical shape (overall dimensions)
3 – vehicle weight
4 – vehicle motion parameters (direction, speed, etc.)
5 – traffic motion parameters (direction, speed, distance in-between vehicles, etc.)
In general terms, the apparatus (system) during the learning mode will be initially introduced to what is defined as accepted process quality. The system will then analyze the data obtained during the learning mode and calculate process acceptance criteria. The system will then in real-time execute controls to maintain the process within the acceptance criteria.
Best regards,
Zack
Patent publications:
US 7844416
Asking price:
50,000 USD
50,000 USD
Great invention
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