TOWARDS SCALABLE, ROBUST AND COST-EFFICIENT MECHANISM FOR MULTIPLE OBJECT LOCALIZATION IN SMART INDOOR ENVIRONMENT
20220300780 · 2022-09-22
Inventors
Cpc classification
H04W4/80
ELECTRICITY
G06K7/10366
PHYSICS
G01S13/75
PHYSICS
G06K7/10376
PHYSICS
G06K19/0723
PHYSICS
G06K7/10356
PHYSICS
International classification
Abstract
Systems and methods related to a RFID-based smart confined environment are provided. A system for localizing an object in a smart home includes a single RFID reader, a plurality of passive RFID tags, each of which is affixed to one of a plurality of objects to be located and contains information of a corresponding object, and a mobile platform including two antennas configured to transmit a carrier wave signal and receive a backscattering signal from a target object. The two antennas are parallelogram-shaped and abutted against each other along a radiation direction.
Claims
1. A radio frequency identification (RFID) based system for localizing an object, the system comprising: a RFID reader; a plurality of passive RFID tags, each of the plurality of passive RFID tags being placed on one of a plurality of objects to be located on, and containing data of, a corresponding object; and a mobile platform comprising two antennas configured to transmit a carrier wave signal and receive a backscattering signal from a target object associated with one of the plurality of passive RFID tags, the two antennas being abutted against each other along a radiation direction.
2. The system of claim 1, further comprising a localization server in wireless communication with the RFID reader, the localization server being configured to extract information of the target object in a data format comprising at least one of: a tag identification of the target object, an antenna identification identifying one of the two antennas, a received signal strength (RSS) value associated with a location of the mobile platform, and a time stamp value associated with the RSS value.
3. The system of claim 1, further comprising a localization server in wireless communication with the RFID reader, wherein the localization server directs the mobile platform to approach the target object using a hop-based mechanism.
4. The system of claim 1, wherein the two antennas each comprise a parallelogram shape having two opposite long sides and two opposite short sides, and wherein the two antennas are electrically connected on one of the two opposite short sides.
5. The system of claim 1, wherein the two antennas are arranged at an angle of about 45 degrees with respect to a direction perpendicular to the radiation direction.
6. The system of claim 1, wherein each of the two antennas has a beam pattern configured to provide a triangular coverage of a region.
7. The system of claim 1, wherein the mobile platform further comprises a digital camera configured to take an image of the target object when the mobile platform is within a predetermined range of the target object.
8. The system of claim 1, wherein the RFID reader is located in the mobile platform, and the system further comprises a rechargeable battery configured to supply power to the RFID reader.
9. The system of claim 1, further comprising an electric wire configured to provide a communicative connection between the RFID reader and the mobile platform.
10. The system of claim 1, wherein the RFID reader, the plurality of passive RFID tags, and the mobile platform are located in a confined environment.
11. A method for localizing a passive radio frequency identification (RFID) tag affixed to an object in a confined environment, the method being performed by a mobile platform equipped with two antennas, the method comprising: receiving a backscattering signal from the passive RFID tag by at least one of the two antennas at a first location; obtaining a first received signal strength (RSS) value based on the backscattering signal; when the first RSS value is not greater than a predetermined threshold value: moving the mobile platform to an intermediate location; and when the first RSS value is greater than the predetermined threshold value: stopping moving the mobile platform.
12. The method of claim 11, further comprising: obtaining a second RSS value by at least one of the two antennas at the intermediate location; when the second RSS value is greater than the predetermined threshold value: stopping moving the mobile platform; and when the second RSS value is not greater than the predetermined threshold value: repeating the receiving and obtaining steps to move the mobile platform toward the object.
13. The method of claim 11, further comprising: taking an image of the object by a digital camera mounted on the mobile platform when the first RSS value is greater than the predetermined threshold value.
14. The method of claim 11, wherein moving the mobile platform to the intermediate location comprises a discrete-time stochastic control mechanism operable to select the intermediate location based on: a set of locations; a set of actions; a probability that the first location at a first time value going to a second location at a second time value; and a reward as a result of an action for transitioning from the first location to the second location.
15. The method of claim 11, further comprising: sending the first RSS value to a localization server via an RFID reader.
16. The method of claim 11, wherein the mobile platform travels to the object with no more than 4 hops.
17. A mobile platform for localization of an object equipped with a passive radio frequency identification (RFID) tag, the mobile platform comprising: two antennas in communicative connection with an RFID reader and configured to receive a backscattering signal from the passive RFID tag at a first location, a memory configured to store computer instructions; and a processor coupled to the memory and configured to execute the computer instructions, wherein execution of the computer instructions cause the mobile platform to be configured to: obtain a first received signal strength (RSS) value based on the backscattering signal; move to an intermediate location when the first RSS value is not greater than a predetermined threshold value; and stop moving when the first RSS value is greater than the predetermined threshold value.
18. The mobile platform of claim 17, wherein the two antennas comprises two parallelogram-shaped antennas being arranged with an angle of about 45 degrees with respect to a direction perpendicular to a radiation direction.
19. The mobile platform of claim 17, wherein the RFID reader is located in the mobile platform, and the mobile platform further comprises a rechargeable battery configured to supply power to the RFID reader.
20. The mobile platform of claim 17, further comprising a digital camera configured to take an image of the object when the mobile platform is within a predetermined range of the object.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0026]
[0027]
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[0029]
[0030]
[0031]
[0032]
[0033]
[0034]
DETAILED DESCRIPTION
[0035] The present disclosure provides technical solutions to address the following challenges:
[0036] Existing RFID-based mechanisms leverage machine learning techniques to perform indoor localization. To achieve high localization accuracy, large amount of training data is usually required. Furthermore, training is required once the deployment environment is changed. Embodiments of this disclosure, hence, provide a dynamic process solution that does not require any sort of training, thereby greatly reducing the complexity of deployment, maintenance, and the localization process.
[0037] Existing methods are either intrusive (e.g., employs cameras) or expensive (e.g., employs active RFID) in nature. Embodiments of this disclosure provide a low-cost and non-intrusive process which can guarantee an individual's privacy and reduce the overall cost of the localization system.
[0038] Existing solutions primarily depend on the static RFID readers and antennas and require deploying of the same in each room of a smart home. This disclosure addresses the challenges of dynamic environments that on one hand does not require any additional installation and deployment when adding a new room to the localization area, and on the other hand, guarantees that new physical objects are incorporated in a plug-and-play manner.
[0039] The present inventors choose RFID tag ID identification for indoor localization within a smart home for the following reasons:
[0040] Existing solutions primarily employ machine learning techniques which require massive data sets and time to train on in order to learn and mature enough to be fulfilled for the indoor localization purposes.
[0041] Existing solutions are intrusive in nature, thereby not guaranteeing users' privacy within all contexts.
[0042] Scalability, cost, and robustness are yet other issues in the existing solutions, i.e., (a) they cannot support multi-object localization to an accurate extent, (b) are particularly expensive due to the deployment of RFID grids for localization purposes; and (c) are not capable of incorporating new physical objects in a plug-and-play manner.
[0043] Existing localization infrastructures involve mounting of static RFID antennas in a smart living space, and as such, the complexity surrounding a moving RFID antenna platform has not been deliberated.
[0044] An exemplary RFID-based localization scenario within an intelligent space (smart living space) according to embodiments of the present invention is provided. In this particular scenario, each stationary object (sofa, refrigerator, music system, door, key, thermostat, etc.) together with mobile objects (e.g., pets, humans) is affixed with a single passive RFID tag.
[0045] Passive RFID tags have no internal power source and are powered via the electromagnetic energy transmitted from one or more RFID readers. According to one embodiment, the RFID-based localization system may include a moving or mobile platform (e.g., robot) 15 having two RFID antennas Ant 0 and Ant 1 that are mounted on the mobile platform. The RFID antennas have been suitably angled to (a) maximize the coverage of a smart living space at any given time and location, (b) mitigate the overlapping coverage area of individual RFID antennas, and (c) allow the mobile platform (robot) to instantaneously traverse in the region of the antenna which has detected a requisite physical object in real-time without the need for complex training as well as excessive network management overhead. The RFID-based localization system may also include an RFID reader 17 and a localization server (e.g., a computer system) 19. In one embodiment, the RFID reader 17 may be coupled to the localization server 19 through a wired connection (e.g., Ethernet local area network) or a wireless air interface (e.g., Wi-Fi). In one embodiment, the RFID reader 17 may be coupled to the localization server 19 through a router. The localization server 19 is configured to control and/or program the RFID reader. The RFID antennas Ant 0, Ant 1 mounted on the mobile platform are connected with the RFID reader via an electric connection 16 which is configured to be a medium for the electromagnetic energy (data signals) to travel from the RFID reader to the antennas and back. The length and rating of the electrical connection 16 depends from the overall loss (e.g., cable attenuation, crosstalk, return loss, noise, etc.) and the size of the smart living space.
[0046] The RFID reader 17 is configured to communicate with the mobile platform 15 (including the antennas Ant 0, Ant 1) using time-division duplex (TDD), frequency-division duplex (FDD), half duplex, or full duplex techniques. The RFID reader provides a reader-to-tag transmission to the passive RFID tags in the smart living space through the antennas of the mobile platform. Each of the passive RFID tags scavenges power from a RF signal received via an air interface 14 and, in turn, responds with a corresponding tag-to-reader communication back to the RFID reader through the antennas of the mobile platform. The RFID reader then sends data and information received from the passive RFID tags to the localization server for storage and processing.
[0047] In one embodiment, the mobile platform (robot) may have a digital camera 103 installed thereon. In one embodiment, the digital camera is turned on when the robot (mobile platform) is within a predetermined range (e.g., within 1 meter) of a targeted object for identification purposes. In accordance to some embodiments of the present invention, the RFID-based localization system performs profiling and logical operations in order to store unique key features and characteristics of different objects (both mobile and stationary) in their respective RFID tags. In accordance to the present invention, any new object will have to pass through the profiling phase to allow the RFID-based localization system to distinguish one from the other.
[0048]
[0049] In one embodiment, the input block module 201 provides a plug-and-play operation for various types of physical objects. Physical objects may include mobile objects (e.g., pets, humans) and stationary objects (e.g., furniture, utensils, appliances, plants, etc.). The input block module 201 is scalable such that its capacity can be increased as needed without making any modification to the system. That is, appliances, furniture, pets, humans, etc. can be added to the smart living space without the need to modify or change the system. The input block module 201 communicates data and information of physical objects to the data access module 202 via a connection 212. The data access module 202 may be configured to collect, filter data and information received from the input block module 201. The data and information of the physical objects may include characteristics of the physical objects such as the physical features (whether the objects are moving or stationary), received signal strengths values of the antennas, the physical position of the movable platform (robot), etc.
[0050] The input block module 201 also communicates data and information of physical objects to the virtualization module 203 via a connection 213. The virtualization module 203 provides the mapping of the physical objects to corresponding virtual objects. The virtualization module 203 communicates each of the virtual objects with the data access module 202 through a connection 223 to collect and interpret the status of the corresponding physical object, i.e., query for the status and/or precise location of the physical object. The virtualization module 203 provides a platform that can operate as a storage for storing the collected information (e.g., status of a corresponding physical object) and generates events in response to the collected information to the event detection and aggregation module 204 through a connection 234.
[0051] The event and aggregation module 204 includes an event detection module or circuit 204a that may include a RFID reader configured to detect received signal strength indicator (RSSI) signals received from an object tagged with a RFID tag. The event detection module or circuit 204a may determine the object's geographical location based on an RSSI zone having the maximum signal strength. The event detection module or circuit 204a may also include one or more sensors for detecting state changes of the physical objects (whether a lamp, an appliance, a thermostat is on or off).
[0052] The event and aggregation module 204 may further include an event aggregation module or circuit 204b which analyzes and correlates events among the physical objects with a corresponding latency. In one embodiment, the context of the events may include an identity (e.g., identities for stationary objects, profiling database for multiple users), geographical location (spatiality) and timestamp (temporality).
[0053] The output block module 205 may include a rule composer module 205a which may be a web-based application with a user-friendly graphic user interface (GUI) for rule creation in a drag- and drop manner. The output block module 205 may also include a web-based user interface 205b to enable a user to manage physical objects of interest using a three-dimensional (3D) pointing program and device in a 3D smart living space. The output block module 205 may also include a short message service (SMS) notification circuit or device 205c for sending SMS notification messages to emergency authorities to alert and to respond to a particular event. The output block module 205 is in communicative interaction with the event detection and aggregation module 204 through a communication link 245. For example, the output block module 205 may transform events and supporting data into services. Services may be stored in a service repository in the form of representative state transfer (REST) compliant application programming interfaces (API). The communication links 212, 213, 223, 234, and 245 can be a wireless or a wired communication link.
[0054]
[0055] According to some embodiments of the present disclosure, an RFID-based indoor localization system may include a single RFID reader, two angled RFID antennas connected to the single RFID reader, and a single passive RFID tag attached to each stationary and mobile object in a smart living space. The RFID tag contains the profile information of a respective object which can be conveniently read via the RFID reader for both identification and localization purposes. After extracting the received signal strength (RSS) values from both antennas, the system pre-processes the RSS values by cleaning and pruning (filtering) noises. Subsequent to a data analytics stage, an engineered hop-based mechanism has been envisaged and implemented (primarily based on the Markov Decision Process) to reach an optimal decision for localizing the requisite physical object, and which in its essence, is primarily reliant on the direction of the antenna receiving the maximum signal strength from the targeted RFID object.
[0056]
[0057] Embodiments of the present disclosure provide the workflow of a smart indoor localization method in the scenario of a smart home. The process of setting up the antennas and then the process of locating a physical object (e.g., chair) are described below.
[0058]
[0059] In some embodiments, the RFID antennas share a common short side and are arranged in a V-shape (
[0060] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements are exaggerated relative to each other for clarity.
[0061] Although the mobile platform in the Figures is shown as a humanoid robot, the scope of the present disclosure is not limited thereto. In accordance with the present disclosure, the mobile platform can have other shapes, such as a shape of a circular drum, a circular or oval disc, a rectangular box, and any other physical forms. It is understood that the antennas can be disposed on the mobile platform in other form different from the one shown in the figures. In the example shown in
[0062] In some embodiments, the RFID reader can be mounted on a wall or ceiling of the smart living space and connected to the robot (mobile platform) through an electrical connection (e.g., cable), and the RFID reader receives the power supply from a power source through a power connector and provides a portion of the power to the mobile platform. In other embodiments, the RFID reader may be integrated within the mobile platform which also includes a rechargeable battery for supplying power to the integrated RFID reader. In accordance with the present disclosure, each of the physical objects in the smart living space is attached with an RFID tag that has its own inductive coil, through which a portion of the magnetic field energy transmitted by the RFID reader is transferred to electronic circuits of the tag. The RFID reader may be connected to a localization server through a wired or wireless connection. The workflow of a smart indoor localization method according to embodiments of the present may include the following processes:
[0063] A. General Workflow.—Once an RFID antenna detects the RFID tag of a targeted object to be localized (depending on the user's requirements), the robot accordingly traverses in the direction of the antenna detecting the object. In case where the requisite object is detected by both antennas, the robot will traverse in the direction of the antenna which has picked up the higher signal strength from the respective RFID tag.
[0064] B. Hop-based approach.—Since both RFID antennas are suitably angled to cover the entire coverage region of a smart living space, the robot will always traverse in a manner that it reaches the requisite target in minimum possible hops by narrowing down the probable target area in the shortest possible time. In doing the same, the robot may perform a number of maneuvers, including but not limited to, moving forward, right or left, and so on. Once a particular signal strength's threshold is reached (e.g., 10,000 units), the robot will turn on the digital camera for purpose of object identification. In some embodiments, the lag at each hop is approximately 0.5 second during which all the RSS extraction, data analytics, and computation pertinent to localization is performed followed by decision and triggering of the next hop. The hop-based approach further ensures that data (i.e., RSS values) collected at each hop is not only stable but also extremely reliable. It is pertinent to mention that the signal strength will not be collected by any of the RFID antennas during the process of hop transition as this is not only unnecessary but also results in inaccurate data points as RFID patterns are extremely sensitive to their ambience that changes during each point of a hop transition.
[0065] Hence, once a requisite hop has been made and the robot comes to an immediate stop, the accurate signal strength values will be recorded to allow the robot to make an accurate decision. In general, any object could be tracked within 3-4 hops executed in a time duration of τ seconds (where, r=2 to 3 s) within a standard-sized living room (e.g., 20 to 30 m.sup.2). It is also pertinent to highlight that the solution according to the present disclosure can localize pets and humans in other rooms provided that the inner walls of a smart home are neither filled up with concrete nor made up of several multi-layered bricks.
[0066] The proposed smart indoor localization system has its primary reliance on Markov Decision Process, which is a discrete-time stochastic control mechanism based on a 4-tuple principle (S, A, Pr.sub.a, Rw.sub.a), wherein:
S=finite set of states (referred to as hops in some embodiments of the present disclosure),
A=finite set of actions,
Pr.sub.a(s, s′)=probability that a particular action a in state s at time t leads to another states s′ at time t+1,
Rw.sub.a=immediate reward received as a result of the action a for transitioning from states s to state s′ (Rw.sub.a: S*A.fwdarw. being the reward function),
[0067] A state S.sub.t is considered Markov if and only if it has acquired relevant information from the history, i.e.,
P(S.sub.t+1|S.sub.t)=P(S.sub.t+1|S.sub.1, . . . ,S.sub.t)
where P((S.sub.t+1|S.sub.t) is a probability that depends on states S.sub.1, . . . , S.sub.t.
[0068] Therefore, the probability of traversing to the next state given the entire sequence of states a robot has already traversed through, is equal to the probability of moving to the next state given the present state, i.e., the future is independent of the past given the present state. The state transition probability is derived as:
Pr.sub.a(s,s′)=P(S.sub.t+1=s′|S.sub.t=s).
[0069] The core idea behind the Markov Decision Process is to find an optimal policy π for the robot's decision making, i.e., a function that would be specifying the action “a” that the robot will opt for in state “s”, i.e., a=π(s), so as to reach an optimal state “s′”, thereby maximizing the immediate rewards. The value function (i.e., expected sum of the discounted rewards) for the policy is:
V.sup.π(s)=E[R(s.sub.o)+γR(s.sub.o)+γ.sup.2R(s.sub.o)+ . . . |s.sub.o=s,π],
where γ is the discount factor. The optimal value function (i.e., best possible expected sum of discounted rewards) is: V.sup.π(s)=E [R(s.sub.o)+γR(s.sub.o)+γ.sup.2R(s.sub.o)+ . . . |s.sub.o=s, V*(s)=max.sub.πV.sup.π(s).
[0070]
[0071] In an exemplary embodiment, a targeted object (i.e., a chair) 606c has been read by antenna 1 at location 0. Subsequently, the robot traverses straight in the direction of antenna 1 by an appropriate hop length (generally recommended to be between 0.5 meter and 1.0 meter). On reaching location 1, the received signal strength (RSS) value has considerably increased (e.g., from 2184 units to 7778 units) which manifests that the robot is traversing in the right trajectory and hence an appropriate hop in the direction of antenna 1 was subsequently made. However, at location 2, the RSS value has significantly dropped (e.g., from 7778 units to 2358 units) which implied that the robot has started traversing away from the targeted object, and was then directed in a right maneuverer to location 3 where the RSS value increased beyond the threshold (e.g., 11559 units exceeding a predetermined threshold value of 10,000 units) and the robot turned on a digital camera configured to take images for object recognition purposes.
[0072] In one embodiment, the robot may send the received RSS values to a localization server using the following data format:
“Tag ID, Antenna ID, time at which a RSS value is received, and the corresponding RSS value”, Where Tag ID represents the identity of the passive RFID tag, antenna ID represents the identity of the antenna that is used to receive the backscattering signal of the passive RFIS tag, time represent a time stamp value associated with the location where the antenna receives the backscattering signal, and the RSS value represents the measured received signal strength value of the backscattering signal.
[0073] In one numerical example embodiment, the data format received by a localization server may be as follows:
0000 . . . 0000000001 (Tag ID), 1 (Antenna ID), 22:30:35.628 (time value in hours, minutes, seconds), 13162 (measured RS S value corresponding to the location of the antenna 1).
[0074] In the example shown, the tag ID can have any number of bits, e.g., from 10 bits to 128 bits, depending from the application. The antenna ID has 1 bit for identifying whether it is Antenna 0 or Antenna 1. The time value shows the current time in hours, minutes, second and fraction-decimal of a second corresponding to the location of the robotic platform. The measured RSS value is the received signal strength value acquired by the antenna at that location. In one embodiment, all these information are used by the localization server to determine the next motion direction of the robotic platform. As would be appreciated by those skilled in the art, the sequence of the data format can have a different sequential format, the number of bits may have a different bit length, and the resolution of the RSS value and the time stamp value may have a different format, which still fall within the scope of the present invention.
[0075]
[0076] According to different embodiments, features and techniques of the present disclosure may provide one or more of the following benefits and advantages:
[0077] Deployment of Angled RFID Antennas on a Mobile Robotic Platform
[0078] The present disclosure employs an engineered approach to install suitably angled RFID antennas on a moveable robotic platform. In one embodiment, the suitably angled RFID antennas include two antennas that have the same dimension (physical size) and are tilted at an angle of 45° in a direction perpendicular to the radiation direction in order to maximize the coverage of a smart living space, mitigate the overlapping coverage region of the antennas to avoid possible interferences, and to allow the robotic platform to instantaneously traverse in the direction of antennas detecting the target object. The properties and features of the RFID antennas have been described above with reference to
[0079] Hop-Based Localization Mechanism for Indoor Localization Purposes
[0080] The present disclosure employs a hop-based localization mechanism to ensure that the robotic platform localizes the requisite physical object by narrowing down to the probable target area in a shortest possible time without the need for any complex training or support of reference points.
[0081] Embodiments of the present disclosure provide many advantages and benefits in different aspects as follows:
[0082] a. Physical Objects Discovery Range. The read range of passive tags depends on many factors, such as the frequency of operation, the power of the RFID reader, interference from other radio frequency signals. By having the particular arrangement of two antennas having a parallelogram shape abutting at a short side and titled at an angle of about 45 degrees with respect to the horizontal plane, a correct location estimate of a target object with a resolution of about 100 cm (approximately 1 meter) can be achieved.
[0083] b. Scalability. Intelligent incorporation and orchestration of 1 to 256 physical objects (stationary and mobile objects) in a highly efficient manner.
[0084] c. Plug-and-play mode. The RFID-based localization system can detect the presence of new objects that are introduced into the smart living space without the need for deployment of any additional infrastructure. In other words, the localization server can be out-of-sign of a user and outside of the smart living space and remotely controls the robotic platform that a user may likely not be aware of the existence of the server. Only the profiling of a new RFID tag is required in order to capture the salient characteristics of a corresponding physical object.
[0085] d. Maximum Number of Hops Required to Localize the Physical Object. The RFID-based localization system requires only 3 or 4 hops to localize a target object depending on dimensions of the living space and the number of obstacles that may cause interference. The system achieves such a small number of hops by employing a Markov decision process that specifies the action “a” that the robotic platform will opt for in state “s” to reach an optimal state “s”, thereby maximizing the immediate rewards.
[0086] e. Maximum Time Required to Localize the Physical Object. The RFID-based localization system typically requires a few seconds to reach the target object (i.e., at each hop, the robotic platform takes 0.5 second to establish the next hop, however, the hop transition time is reliant on the robot's speed).
[0087] f. Accuracy—Generally Greater than 90% within all Contexts.
[0088] g. Cost Effectiveness. The RFID-based localization system employs passive RFID tags: One passive RFID tag (around 10 cents-50 cents) per object.
[0089] In accordance with the present disclosure, the RFID-based localization system may find applications in personal health-area services, personal safety-area services in a private residence, in health-care environments (nursing homes, hospitals) for tracking of medical doctors, nurses, and patients accurately. In some embodiments, referring to
[0090] Referring to
[0091] Referring to
[0092]
[0093]
[0094] The special-purpose computer system 90 also includes a communication interface device 95 that provides an interface to other devices such as a RFID reader, a router. The communication interface device 95 may include an Ethernet device, a modem (telephone, cable), a wireless network interface device, and the like. The special-purpose computer system 90 further includes a monitor 96 that allows a user to selects objects, text, commands, icons, and the like using a mouse or touch screen panel. The monitor may also display 3D graphic presentations of a smart living room and physical objects located therein. The special-purpose computer system 90 also includes a bus system 97 that couples all the devices 91 to 96 together. The bus system 97 may include a plurality of bus subsystems that provide mechanisms to connect various devices and components of the special-purpose computer system 90. The special-purpose computer system 90 may include hardware, firmware modules and software codes that execute the methodologies and functions described in
[0095] While the embodiments have been described with references to examples, those of skill in the art will be able to make modifications to the described embodiments without departing from the scope of the present invention. Those of skill in the art will recognize that variations are possible with the scope as defined in the following claims.