阅读说明：本技术 建筑施工现场监控系统及其监控方法 (Building construction site monitoring system and monitoring method thereof ) 是由 姚成龙 于 2021-09-08 设计创作，主要内容包括：本发明公开了建筑施工现场监控系统及其监控方法,涉及建筑施工安全监测技术领域,解决了现有方案中存在灵活性差、监测能力弱以及可视化程度低导致的警示不及时和救援不及时的技术问题；本发明设置了区域处理模块,区域处理模块通过采集所负责监测区域的监测数据,对监测数据进行分析获取预警标签,并根据预警标签进行及时预警；既能够保证预警的及时性,又能够提高数据处理的效率；本发明在进行数据处理之前,获取三维施工模型,并对三维施工模型进行划分获取监测区域,且根据重点设施将监测区域划分为重点区域和普通区域,将建筑施工现场分层次的监测,既保证了对重点区域的及时准确监测,又能够避免数据处理能力的浪费。(The invention discloses a building construction site monitoring system and a monitoring method thereof, relates to the technical field of building construction safety monitoring, and solves the technical problems of untimely warning and untimely rescue caused by poor flexibility, weak monitoring capability and low visualization degree in the existing scheme; the system is provided with a regional processing module, the regional processing module analyzes monitoring data to obtain an early warning label by acquiring the monitoring data of a monitored region, and early warning is carried out in time according to the early warning label; the timeliness of early warning can be guaranteed, and the data processing efficiency can be improved; before data processing is carried out, the three-dimensional construction model is obtained, the three-dimensional construction model is divided to obtain the monitoring area, the monitoring area is divided into a key area and a common area according to key facilities, and the construction site is monitored in a layered mode, so that timely and accurate monitoring of the key area is guaranteed, and waste of data processing capacity can be avoided.)

1. The building construction site monitoring system comprises a processor and a data storage module connected with the processor, and is characterized in that the processor is respectively in communication and/or electrical connection with a region processing module, a rescue processing module and a visual processing module, and the region processing module comprises an edge computing unit and a data acquisition unit connected with the edge computing unit;

carrying out three-dimensional modeling on a building construction site area through a processor to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module; the monitoring area comprises a key area and a common area;

the data acquisition unit acquires monitoring data of a monitoring area through the acquisition sensor and transmits the monitoring data to the corresponding edge calculation unit, the processor and the data storage module;

the edge calculation unit analyzes the monitoring data to obtain an early warning label and carries out early warning according to the early warning label; when the early warning label is larger than the label threshold value, the processor carries out real-time field monitoring on the corresponding monitoring area through an image recognition technology and sends a rescue signal according to a field monitoring result; wherein the tag threshold is an integer greater than 2;

after receiving the rescue signal, the rescue processing module acquires the real-time position of the worker in the monitoring area and completes dispatching of the rescue worker;

the visualization processing module is used for displaying the state of the monitoring area.

2. The building construction site monitoring system according to claim 1, wherein the acquisition of the monitoring area includes an automatic division manner and a manual division manner; the monitoring area division by the automatic division mode comprises the following steps:

analyzing the three-dimensional construction model to obtain key facilities; wherein the key facilities comprise a scaffold, a hoisting tower crane and an operation surface with the construction height of more than 2 meters;

taking key facilities as a center, and acquiring a key area according to a constant R; wherein, the key area is round or rectangular; when the key area is circular, the constant R is the radius of the key area, and when the key area is rectangular, the constant R is the radius of a circle circumscribed to the key area; the constant R is a real number greater than 5 and is measured in meters;

when the overlapping area of any two key areas is larger than the overlapping threshold value, combining the two key areas to form a new key area; wherein the overlapping threshold is a real number greater than 1, and the unit is square meter;

and marking the areas except the key areas in the monitoring area as normal areas.

3. The building construction site monitoring system according to claim 2, wherein one area processing module is provided for each of the key areas.

4. The construction site monitoring system according to claim 1, wherein the edge calculation unit acquiring the early warning tag includes:

extracting environmental data in the monitoring data; the environment data comprises environment temperature, environment humidity and vibration data, and is continuously monitored data within fixed time duration, and the fixed time duration is an integer greater than 5 seconds;

acquiring an early warning evaluation model through a data storage module;

and inputting the environmental data subjected to normalization processing into an early warning evaluation model to obtain an early warning label.

5. The building construction site monitoring system of claim 1, wherein when the early warning tag is greater than a tag threshold, real-time site monitoring is performed by a processor, including;

extracting a high-definition image in the monitoring data, and performing image preprocessing on the high-definition image to obtain a target image;

analyzing the target image through an image recognition technology to obtain an abnormal state of a corresponding monitoring area;

when the monitoring area has an abnormal state, generating and sending a rescue signal to a rescue processing module; wherein the abnormal conditions include a work surface collapse, a gathering of people, and a falling object.

6. The building construction site monitoring system according to claim 1, wherein the rescue processing module obtains real-time position and physical state of workers through an intelligent safety helmet; wherein, dispose GPS locater, high definition digtal camera, temperature sensor and heart rate sensor in the intelligent safety cap, the health status includes body temperature and rhythm of the heart.

7. The construction site monitoring system according to claim 4, wherein the obtaining of the early warning assessment model comprises:

acquiring standard training data through a data storage module; wherein the standard training data and the environmental data have the same content category;

marking an early warning label for the standard training data;

constructing an artificial intelligence model; the artificial intelligence model comprises a deep convolutional neural network and an RBF neural network;

training an artificial intelligence model through standard training data and corresponding early warning labels, marking the trained artificial intelligence model as an early warning evaluation model, and sending the trained early warning evaluation model to a data storage module for storage.

8. The monitoring method of the construction site monitoring system according to any one of claims 1 to 7, comprising:

carrying out three-dimensional modeling on a building construction site area to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module;

acquiring monitoring data of a monitoring area through an acquisition sensor; the acquisition sensor comprises a temperature sensor, a vibration sensor, a humidity sensor and a high-definition camera;

analyzing the monitoring data to obtain an early warning label, and early warning according to the early warning label;

when the early warning label is larger than the label threshold value, carrying out real-time field monitoring on the corresponding monitoring area through an image recognition technology, and sending a rescue signal according to a field monitoring result;

and after the rescue signal is generated, acquiring the real-time position of the worker in the monitoring area, and finishing dispatching the rescue worker.

Technical Field

The invention belongs to the technical field of building construction safety monitoring, and particularly relates to a building construction site monitoring system and a monitoring method thereof.

Background

The construction site is a place where a construction project is being developed and civil engineering is carried out, and the range of the construction site is closed by a coaming, a wire mesh or a fence so as to limit the entrance and exit of personnel, materials, machinery and vehicles. Various danger sources often exist in a building construction site, the danger sources mainly come from physical factors and behavior factors, the physical factors refer to defects of construction equipment and defects of protection equipment, and the behavior factors refer to abnormal working states of workers.

In the existing scheme, a monitoring device is fixedly arranged in a building construction site, the monitoring device monitors a dangerous source through a sensor or a camera, and a control center can control a warning device close to the dangerous source to send out warning confidence of a corresponding grade according to the position and the degree of danger of the dangerous source so as to warn workers; the existing scheme has serious lag in monitoring and warning of a dangerous source, and has the problems of poor flexibility, weaker monitoring capability and insufficient warning and rescue capability.

Therefore, a monitoring system capable of accurately monitoring a construction site in a full range and having a strong warning function and search and rescue capabilities is needed.

Disclosure of Invention

The invention provides a building construction site monitoring system and a monitoring method thereof, which are used for solving the technical problems of untimely warning and untimely rescue caused by poor flexibility, weak monitoring capability and low visualization degree in the existing scheme.

The purpose of the invention can be realized by the following technical scheme: the building construction site monitoring system comprises a processor and a data storage module connected with the processor;

the processor is respectively in communication and/or electrical connection with the area processing module, the rescue processing module and the visualization processing module, and the area processing module comprises an edge computing unit and a data acquisition unit connected with the edge computing unit;

carrying out three-dimensional modeling on a building construction site area through a processor to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module; the monitoring area comprises a key area and a common area;

the data acquisition unit acquires monitoring data of a monitoring area through the acquisition sensor and transmits the monitoring data to the corresponding edge calculation unit, the processor and the data storage module;

the edge calculation unit analyzes the monitoring data to obtain an early warning label and carries out early warning according to the early warning label; when the early warning label is larger than the label threshold value, the processor carries out real-time field monitoring on the corresponding monitoring area through an image recognition technology and sends a rescue signal according to a field monitoring result; wherein the tag threshold is an integer greater than 2;

after receiving the rescue signal, the rescue processing module acquires the real-time position of the worker in the monitoring area and completes dispatching of the rescue worker;

the visualization processing module is used for displaying the state of the monitoring area.

Preferably, the monitoring area is obtained by an automatic division method, including:

analyzing the three-dimensional construction model to obtain key facilities; wherein the key facilities comprise a scaffold, a hoisting tower crane and an operation surface with the construction height of more than 2 meters;

taking key facilities as a center, and acquiring a key area according to a constant R; wherein, the key area is round or rectangular; when the key area is circular, the constant R is the radius of the key area, and when the key area is rectangular, the constant R is the radius of a circle circumscribed to the key area; the constant R is a real number greater than 5 and is measured in meters;

when the overlapping area of any two key areas is larger than the overlapping threshold value, combining the two key areas to form a new key area; wherein the overlapping threshold is a real number greater than 1, and the unit is square meter;

and marking the areas except the key areas in the monitoring area as normal areas.

Preferably, the monitoring area is obtained by a manual division method, including:

and manually selecting a key area in the three-dimensional construction model, and marking the area except the key area in the monitoring area as a common area after the key area is manually selected.

Preferably, each of the key areas is provided with an area processing module.

Preferably, the acquiring of the warning label by the edge calculation unit includes:

extracting environmental data in the monitoring data; the environment data comprises environment temperature, environment humidity and vibration data, and is continuously monitored data within fixed time duration, and the fixed time duration is an integer greater than 5 seconds;

acquiring an early warning evaluation model through a data storage module; the early warning evaluation model is obtained by training an artificial intelligence model, and the artificial intelligence model comprises a deep convolution neural network and an RBF neural network;

inputting the environmental data subjected to normalization processing into an early warning evaluation model to obtain an early warning label; the early warning label is an integer which is greater than or equal to 0 and less than or equal to 10, and the larger the value of the early warning label is, the higher the danger degree is.

Preferably, the obtaining of the early warning evaluation model includes:

acquiring standard training data through a data storage module; wherein the standard training data and the environmental data have the same content category;

marking an early warning label for the standard training data;

constructing an artificial intelligence model; the artificial intelligence model comprises a deep convolutional neural network and an RBF neural network;

training an artificial intelligence model through standard training data and corresponding early warning labels, marking the trained artificial intelligence model as an early warning evaluation model, and sending the trained early warning evaluation model to a data storage module for storage.

Preferably, when the early warning tag is larger than the tag threshold value, real-time field monitoring is carried out through a processor, wherein the monitoring comprises the steps of;

extracting a high-definition image in the monitoring data, and performing image preprocessing on the high-definition image to obtain a target image;

analyzing the target image through an image recognition technology to obtain an abnormal state of a corresponding monitoring area;

when the monitoring area has an abnormal state, generating and sending a rescue signal to a rescue processing module; wherein the abnormal conditions include a work surface collapse, a gathering of people, and a falling object.

Preferably, the rescue processing module acquires the real-time position and the body state of a worker through an intelligent safety helmet; wherein, dispose GPS locater, high definition digtal camera, temperature sensor and heart rate sensor in the intelligent safety cap, the health status includes body temperature and rhythm of the heart.

Preferably, the acquisition sensor comprises a temperature sensor, a vibration sensor, a humidity sensor and a high-definition camera.

The building construction site monitoring method comprises the following steps:

carrying out three-dimensional modeling on a building construction site area to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module;

acquiring monitoring data of a monitoring area through an acquisition sensor; the acquisition sensor comprises a temperature sensor, a vibration sensor, a humidity sensor and a high-definition camera;

analyzing the monitoring data to obtain an early warning label, and early warning according to the early warning label;

when the early warning label is larger than the label threshold value, carrying out real-time field monitoring on the corresponding monitoring area through an image recognition technology, and sending a rescue signal according to a field monitoring result;

and after the rescue signal is generated, acquiring the real-time position of the worker in the monitoring area, and finishing dispatching the rescue worker.

Compared with the prior art, the invention has the beneficial effects that:

1. the invention is provided with an area processing module, wherein the area processing module comprises an edge calculating unit and a data acquisition unit; the region processing module analyzes the monitoring data to obtain an early warning label by acquiring the monitoring data of the region which is responsible for monitoring, and performs early warning in time according to the early warning label; the timeliness of early warning can be guaranteed, and the data processing efficiency can be improved.

2. Before data processing, the processor carries out three-dimensional modeling on the building construction site area to obtain a three-dimensional construction model, divides the three-dimensional construction model to obtain a monitoring area, divides the monitoring area into a key area and a common area according to key facilities, and carries out layered monitoring on the building construction site, so that timely and accurate monitoring on the key area is ensured, and waste of data processing capacity can be avoided.

3. When the early warning label is larger than the label threshold value, the processor carries out real-time field monitoring on the corresponding monitoring area through an image recognition technology, and sends a rescue signal according to a field monitoring result, and after the rescue processing module receives the rescue signal, the real-time position of a worker in the monitoring area is obtained, and dispatching of the rescue worker is completed; after early warning, the high-definition images of the monitored area are analyzed, specific abnormity of the monitored area is known, and workers are rescued in time by dispatching rescue workers, so that safety of the workers is further guaranteed.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a schematic diagram of the system of the present invention;

FIG. 2 is a schematic diagram of the working steps of the present invention.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.

The terminology used herein is for the purpose of describing embodiments and is not intended to be limiting and/or limiting of the present disclosure; it should be noted that the singular forms "a," "an," and "the" include the plural forms as well, unless the context clearly indicates otherwise; also, although the terms first, second, etc. may be used herein to describe various elements, the elements are not limited by these terms, which are only used to distinguish one element from another.

Referring to fig. 1-2, the present application provides a building construction site monitoring system, which includes a processor and a data storage module connected to the processor; the processor is respectively in communication and/or electrical connection with the area processing module, the rescue processing module and the visualization processing module, and the area processing module comprises an edge computing unit and a data acquisition unit connected with the edge computing unit.

In the application, the processor is mainly used for completing data interaction and processing tasks with large data volume; the area processing module is configured according to the monitoring area and is used for monitoring and early warning the monitoring area; the rescue processing module is used for positioning the position of the worker and dispatching rescue workers to complete rescue on the basis of analysis and judgment of the region processing module; the visual processing module carries out overall monitoring, displays high-definition images, data processing progress, worker rescue and the like of each monitored area in real time, and facilitates same scheduling.

One of the key points of the building construction site monitoring system provided by the application is that edge calculation is integrated into the building construction site monitoring system, so that the data processing efficiency is improved; the other key point is that the monitoring range and the monitoring precision are improved through the cross fusion of multiple technologies.

In the building construction site monitoring system provided by the application, a three-dimensional construction model is obtained by three-dimensionally modeling a building construction site area through a processor, the three-dimensional construction model is divided to obtain a monitoring area, and the monitoring area is arranged in an area processing module.

Firstly, modeling a building construction site area to be monitored to form a three-dimensional construction model; and then, dividing the three-dimensional construction model in an automatic division mode or a manual division mode to obtain a monitoring area, and then sending the division result of the monitoring area to the area processing module, the visualization processing module, the rescue processing module and the data storage module.

Wherein, divide the monitoring area through automatic partition mode and include:

analyzing the three-dimensional construction model to obtain key facilities; the key facilities are equipment or facilities which are easy to cause danger on a building construction site, such as scaffolds, hoisting tower cranes and operation surfaces with construction height of more than 2 meters;

taking key facilities as a center, and acquiring a key area according to a constant R; the key area can also be understood as an area which can be reached when key facilities are abnormal, and the key area in the application can be circular or rectangular and is selected and set according to specific conditions;

when the overlapping area of any two key areas is larger than the overlapping threshold value, combining the two key areas to form a new key area; and marking the areas except the key areas in the monitoring area as normal areas.

The monitoring area is divided in an automatic dividing mode, wherein the monitoring area is mainly formed by marking specific facilities and then forming a key area and a common area so as to finish the division of the monitoring area; when the construction site is very large and key facilities are more, the method can improve the efficiency and the accuracy of area division.

Wherein, divide the monitoring area through manual partition mode and include:

and manually selecting a key area in the three-dimensional construction model, and marking the area except the key area in the monitoring area as a common area after the key area is manually selected.

The monitoring areas are divided in an automatic dividing mode, corresponding key areas are distinguished in the three-dimensional construction model under the condition that the key areas are known, the mode is suitable for the condition that a building construction site is small, the key areas are known, and the efficiency of area division can be guaranteed.

The monitoring system for the building construction site further comprises a region processing module, a monitoring module and a monitoring module, wherein the region processing module is used for processing a monitoring region; in the application, each key area is at least provided with one area processing module, and when the common area is smaller, one area processing module can be shared by a plurality of common areas.

In the building construction site monitoring system provided by the application, the data acquisition unit acquires monitoring data of a monitoring area through the acquisition sensor and transmits the monitoring data to the corresponding edge calculation unit, the processor and the data storage module; the edge calculation unit analyzes the monitoring data to obtain an early warning label and carries out early warning according to the early warning label.

The edge calculation unit acquiring the early warning label includes:

extracting environmental data in the monitoring data; the environment data comprises data which can represent abnormal states of a monitoring area, such as environment temperature, environment humidity, vibration data and the like, and is continuously monitored within a fixed time length;

acquiring an early warning evaluation model through a data storage module; the early warning evaluation model is obtained by training an artificial intelligence model, and the artificial intelligence model comprises a deep convolution neural network and an RBF neural network;

and inputting the environmental data subjected to normalization processing into an early warning evaluation model to obtain an early warning label.

In the application, the early warning label is obtained by using the advantages of the artificial intelligence model, the data processing efficiency is improved, and the accuracy of abnormity judgment in the monitoring area is improved.

The early warning label is an integer which is greater than or equal to 0 and less than or equal to 10, the larger the value of the early warning label is, the higher the danger degree is, if the early warning label is 0, the corresponding monitoring area is free of abnormal conditions, and if the early warning label is 10, the corresponding monitoring area is casualties.

The acquisition of the early warning evaluation model comprises the following steps:

acquiring standard training data through a data storage module; wherein the standard training data and the environmental data have the same content category,

marking an early warning label for the standard training data;

constructing an artificial intelligence model; the artificial intelligence model comprises a deep convolutional neural network and an RBF neural network;

training an artificial intelligence model through standard training data and corresponding early warning labels, marking the trained artificial intelligence model as an early warning evaluation model, and sending the trained early warning evaluation model to a data storage module for storage.

The standard training data in the application are stored in the data storage module and are updated regularly, and the accuracy and the effectiveness of the data are guaranteed. The standard training data and the environmental data are consistent in content type, namely comprise environmental temperature, environmental humidity and vibration data, wherein the vibration data can be the average value of vibration in the monitored area and the maximum value of vibration in the monitored area.

It is worth noting that the artificial intelligence model needs to be trained through standard training data, so that the standard training data comprises environment data N seconds before the abnormal state of the monitoring area occurs and corresponding environment data when the monitoring area is normal; wherein N is a real number greater than 0.

The early warning evaluation model is obtained through regular training and is sent to the storage module to be stored so as to be called at any time.

In the building construction site monitoring system provided by the application, when the early warning tag is larger than the tag threshold value, the processor carries out real-time site monitoring on a corresponding monitoring area through an image recognition technology, and sends a rescue signal according to a site monitoring result, wherein the process comprises the steps of;

extracting a high-definition image in the monitoring data, and performing image preprocessing on the high-definition image to obtain a target image;

analyzing the target image through an image recognition technology to obtain an abnormal state of a corresponding monitoring area;

when the monitoring area has an abnormal state, generating and sending a rescue signal to a rescue processing module; wherein the abnormal conditions include a work surface collapse, a gathering of people, and a falling object.

And performing preliminary judgment according to the early warning label, judging that field image monitoring is required when the early warning label is larger than a label threshold value, and then identifying the abnormity of a monitoring area by combining a high-definition image and an image identification technology. The abnormity in the application comprises phenomena or behaviors which harm safety of workers and comprise falling objects, collapse of a working face and the like.

In the building construction site monitoring system provided by the application, after the rescue processing module receives the rescue signal, the real-time position of the worker in the monitoring area is obtained, and dispatch of the rescue worker is completed.

In the application, the rescue processing module acquires the real-time position and the physical state of the worker through the intelligent safety helmet and dispatches the rescue worker by combining the nearest principle, so that the worker in the dangerous situation is rescued.

In the building construction site monitoring system provided by the application, the visual processing module is used for displaying the state of a monitoring area, and comprises data acquisition, early warning label acquisition, real-time site monitoring, real-time position acquisition, rescue worker dispatching and other processes, and data interaction and result display.

The application provides a monitoring method of a building construction site monitoring system, which comprises the following steps:

carrying out three-dimensional modeling on a building construction site area to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module;

acquiring monitoring data of a monitoring area through an acquisition sensor; the acquisition sensor comprises a temperature sensor, a vibration sensor, a humidity sensor and a high-definition camera;

analyzing the monitoring data to obtain an early warning label, and early warning according to the early warning label;

when the early warning label is larger than the label threshold value, carrying out real-time field monitoring on the corresponding monitoring area through an image recognition technology, and sending a rescue signal according to a field monitoring result;

and after the rescue signal is generated, acquiring the real-time position of the worker in the monitoring area, and finishing dispatching the rescue worker.

Next, specific examples are:

the method comprises the steps of carrying out three-dimensional modeling on a building construction site area through a processor to obtain a three-dimensional construction model, and automatically dividing the three-dimensional modeling area by taking a scaffold in the three-dimensional construction model as a key facility to obtain a monitoring area.

The data acquisition unit acquires monitoring data of the key area and transmits the monitoring data to the corresponding edge calculation unit, the processor and the data storage module.

The edge calculation unit corresponding to the key area analyzes the monitoring data to obtain an early warning label, and when the early warning label is not 0, an alarm device (such as an alarm) or a smart phone is used for giving an alarm; when the early warning label is larger than 3, the processor analyzes the high-definition image of the monitored area through an image recognition technology, and when the scaffold collapses in the high-definition image, a rescue signal is generated and sent to the rescue processing module.

The rescue processing module obtains the real-time position and the body state of the worker through the intelligent safety helmet and dispatches rescue workers according to the real-time position of the worker to complete rescue.

The working principle of the invention is as follows:

carrying out three-dimensional modeling on a building construction site area to obtain a three-dimensional construction model, dividing the three-dimensional construction model to obtain a monitoring area, and setting the monitoring area in an area processing module; and acquiring monitoring data of the monitoring area through the acquisition sensor.

Analyzing the monitoring data to obtain an early warning label, and early warning according to the early warning label; and when the early warning label is larger than the label threshold value, carrying out real-time field monitoring on the corresponding monitoring area through an image recognition technology, and sending a rescue signal according to a field monitoring result.

And after the rescue signal is generated, acquiring the real-time position of the worker in the monitoring area, and finishing dispatching the rescue worker.

In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.