Patent Application
20050080586
The present invention is related generally to probing systems and methods and, more specifically, to systems and methods for measurement system performance optimization using mobile probes.
In traditional measurement systems, there are typically a finite number of fixed measurement devices, all known to and controlled by the measurement system. Generally such measurement devices are specifically configured and deployed for use by the measurement system at or as near as is practicable to a point at which measurement data is to be collected. When a set of measurements is to be made the system typically will download or otherwise configure each of these devices via whatever communication medium is provided, e.g., a measurement bus such as an IEEE-488 BUS, a local area network (LAN) connection, a serial link, or the like. The measurements are then made on command, periodically, or perhaps based on a time schedule. Depending on the sophistication of the devices, these measurements may be made by the device relatively independently from the rest of the measurement system. For example, a scheduled or periodic data collection, based on an internal device clock, perhaps synchronized to other clocks in the system may be made. Alternatively, devices may require an active command from the system for each measurement. The results typically are then delivered to the rest of the measurement system via the communication medium. Such measurement systems also typically include one or more processors or computers that execute control and analysis software for the measurement system to construct or modify a model of the measurements.
One of the key features of these existing systems is that the identity and location of each measurement device is known. Typically this information forms a basis for initiating control and for associating any resulting data with real world parameters being measured. Accordingly, the device identity, however represented, is often a pseudonym for the location of measurement and the resultant measure. Typically users of existing measurement systems know what instruments are available, what the instruments' locations are, how to access the instruments explicitly, and when data will be returned. Therefore, existing measurement systems are relatively closed.
Existing measurement systems employ spatial variables gleaned from dedicated instruments used to survey an environment variable. For example, a product known as WIZARD™, produced by AGILENT TECHNOLOGIES, made specifically for the wireless telephone industry, creates a model of the RF field strength around a cell tower or the like. Use of this product typically employs the use of dedicated instruments disposed in a vehicle, driven around to make spot measurements to verify and refine field strength data models. As another example, when the Environmental Protection Agency (EPA) is tracking a plume from a hazardous chemical spill, mobile air testing may be performed to derive a model of the plume.
Existing measurement systems typically employ a centralized location, away from the measurement devices, for data processing and model manipulation using the collected data. Therefore, a problem arises in that the collected data cannot be applied to the model at the point of measurement to improve the quality of the model or data collection, or to provide services related to model use. So software hosted by the measurement device, or the operator of the probe, cannot base their interaction or behavior on the subject measurement model. Typically the device does not have either any of the model or enough of it to make decisions. When trying to build models, the unavailability of model information at the measurement device can be a disadvantage.
The present invention is directed to systems and methods for improving the performance of distributed systems containing measurement probes in which some or all of the measurement probes are mobile, that is, not fixed at a given point in space. Embodiments of a performance optimized measurement system comprise at least one mobile measurement device hosting at least a portion of a measurement system model. The mobile measurement device is preferably enabled to evaluate a measurement taken by the mobile measurement device in light of the model for making a determination concerning the measurement, relative to the model. Embodiments of methods for measurement system performance optimization in accordance with the present invention include: augmenting the model using the measurements; directing a user of the mobile measurement device to a different location in response to the evaluation of the measurements; refining a location of the mobile measurement device using the model and the measurements; or determining one or more best modes of use of the mobile measurement device based on the measurements.
The above-incorporated U.S. patent application Ser. No. 10/306,940, entitled “SYSTEM AND METHOD FOR MEASUREMENT AND/OR CONTROL USING MOBILE PROBES” discloses systems and methods for utilizing a pool of mobile devices in probing operations comprising a probing host system including probe management and data management operative aspects, and a pool of mobile devices, one or more of which are operative under control of the probe management to provide probing data to the data management, wherein the one or more mobile devices comprise mobile devices for which location and movement is not under control of the probing host system. There are a variety of candidate platforms for probes of this nature. Presently there are many potential measurement devices that move around, by virtue of the public carrying devices that have communication capabilities and measurement capabilities. Herein these measurement devices have been termed, mobile measurement devices (MMDs).
The present systems and methods employ computational techniques based on measurements of physical variables by the measurement system, or accessible by the measurement system, via the measurement probes and on the spatial distribution of the underlying physical variables. Uses and computations for MMD data may include generation of a new model or improvement of existing models, spatial guidance to areas where a variable's value is more suitable for use by an application, and augmentation of a location service. It is also possible, based on a current model and its computed uncertainty and the statistics of the current data being collected, to compute which, if any, of these three uses are feasible, or to combine uses and/or models. Thus, in a region where the existing model is statistically very precise, such as may be determined from past history, either of the latter two modes of operation may be considered. On the other hand, if the model data for a region is of low quality, then the best use of the incoming data stream may be to refine the model.
The currently collected data and portion of the model resident on the MMD may be used to improve the model by measurement-based model generation or to guide some behavior, performance guidance based on a spatial model or the like. This may take the form of guiding MMD user actions to some goal or the like. Also, the model of some variable and a measurement of that variable may be used to refine a position. Various combinations of these three broad modes may be achieved in accordance with the present invention.
The foregoing has outlined rather broadly the features and technical advantages of the present invention in order that the detailed description of the invention that follows may be better understood. Additional features and advantages of the invention will be described hereinafter which form the subject of the claims of the invention. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present invention. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the invention as set forth in the appended claims. The novel features which are believed to be characteristic of the invention, both as to its organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present invention.
For a more complete understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the accompanying drawing, in which:
MMDs may be used to measure the value of a physical variable as a function of space and time either as their principal function or as a secondary function. The measurements are typically used for one of two purposes: to refine the understanding and to “compute” a model of the spatial temporal distribution of the measured physical variable; or to measure the value of the variable, particularly if the principal function of the device depends on the value of this variable as part of the operation of the device. Unlike existing models that reside at some central location and are inaccessible to an MMD except on a query basis, the present invention systems and methods (100), as depicted in
Wireless phones may be the most prevalent example of possible MMDs, a device that has communication capabilities, increasingly common computational resources available for measurement applications, and measurement capability. In the example of a wireless phone, the measurement capability may be built in for measuring properties of the phone itself or the communications infrastructure, or the measurement capability may be external, such as a sensor interfaced with a wireless phone via a serial connection or the like. It is expected that such capabilities may be found in various other user devices including PDAs, cameras and calculators. There are also similar but less ubiquitous devices or collections of devices that may be combined, for use as measurement probe, such as telemetry sensors found in automobiles and other vehicles such as aircraft, including drones, free floating buoys, etc. Some common features of these devices include an ability to communicate at least on an intermittent basis with devices outside of themselves; an availability of some computational resources within the device to manage the measurement process; access either internally or externally to a measurement device; and the location and availability of a particular device at any given point in time may be determined either from the infrastructure or from some external source. RF monitoring and environmental monitoring are used herein as canonical examples. However, as will be appreciated by one of ordinary skill in the art, other conditions, vectors or the like may be monitored, modeled and used for decision criteria in accordance with the present invention.
As long as these devices are moving around they may be employed as mobile probes, if they are equipped with the appropriate software and hardware to make measurements of interest. However, these devices may not be dedicated devices and their use as mobile probes is preferably a secondary function. By way of example, wireless phones have an RF field strength meter built in for their own operation. A wireless phone measures the RF power received from a given transmitter. In normal operation of the phone, this measured power is used to determine which of several possible base stations the phone communicates with. Since that meter may be used to measure the strength of an RF field and since owners of cell phones move around and use their phones, effective coverage of RF field strength for a wireless phone system or cell tower may be measured using wireless phones as MMDs. On a statistical basis, if one waits long enough at least one cell phone will move into an area of interest. These measurements combined with similar measurements from other phones can also be used to refine the system operator's understanding of the RF coverage in a region, that is the spatial distribution of RF power from an antenna. As discussed above, “drive-by” testing may be employed to make RF measurements over specific routes, in part through the use of a cell phone to provide inputs to RF planning tools such as the aforementioned WIZARD™ product from AGILENT TECHNOLOGIES. In the case of the WIZARD™ product these measurements are used to adjust the free space parameters of a heuristic model. However, when using MMDs in accordance with the present invention, software may be downloaded to cell phones to provide other measurement related functionality.
In principle, MMDs can be used to measure any variable for which an appropriate sensor can be devised within the context of the MMD. In addition to other parameters of the communication infrastructure, measurements of user behavior or related variables may also be made. Other possibilities may include chemical sensors for toxins, biological sensors, physical sensors for noise levels, radiation, etc.
In accordance with the present invention, additional types of computations and uses may be applied to the data collected by MMDs beyond that discussed above. These techniques will primarily be discussed below in the context of RF coverage measurements but are equally applicable to any measured variable.
Existing RF field strength modeling for a cell system is typically based on a mixture of heuristic RF models combined with known terrain and antenna locations. It is possible, in accordance with the present invention, to generate purely measurement-based models to either replace the current models or to provide greater detail within a region. This may be particularly valuable in complex regions where the current modeling technology has difficulty such as within dense urban areas, sparsely covered remote areas, etc.
As discussed above, existing measurement systems centrally collect all data and then analyze that data at a later time to form a model. The present invention, given a measurement and the model, operates in real time. The present invention provides a manner of refining a model as data is collected, in an intelligent fashion, locally, without significant communication cost, by employing a portion of the subject model, resident on the MMD. Existing systems have not given measurement probes a picture of the thing being measured and criteria for improving the resulting model and allowing the devices to refine the model.
For a model based on the n “most representative” locations out of N available, a newly acquired point from 202 may be evaluated at 203 to see whether it reinforces or detracts from the statistical quality of the model. If it reinforces the model this is noted at 204; if the point detracts then it is evaluated further at 205 to decide whether to discard it at 206 as likely faulty or to replace one of the n values at 207 with the newly acquired point, particularly if such replacement would give a better model. Preferably n should be selected to meet quality requirements for the model. As a third alternative, the newly acquired point may just be added to the model at 208, particularly if no information exists for that location of the measurement. The model may be represented in the MMD as a collection of already measured data points or as some sort of functional description. In other words as a function of X and Y, for example, given X and Y an expected RF field strength, or the like, is provided. So now when a new measurement is made for a given location at 202 the MMD may look at the model and make some determination of the worth of the measurement at 203. So, for example, if fifty points have already been measured at the present location a measurement at 202 may not be considered as adding anything to the present model at 203. So when the new measurement is compared with what was predicted for this location by the model at 203 and it is roughly within a tolerance level for the model, the new measurement can be ignored at 206 because it does not add any information to the model.
At 203 and/or 205 a determination may be made that the new measurement fits in one of several categories, 204, 206, 207 or 208. The new measurement may or may not add new information to the model. Statistically at this particular location, if insufficient or too little data has been collected to reach the accuracy desired the new data may be treated as additional information at 208. If at the model predicts the value which was measured, it may be ignored at 206 and it is not added into memory or stored because the model already has the data. Alternatively, it could be that the data seems to disagree with the existing model, in which case a determination may be made at 205 as to whether the data is clearly new information, for example, through taking another measurement at the same location. If the new measurement violates significantly what the model predicts, it should, depending on the modeling paradigm, be included at 208 or included while excluding some other data point in the model which may become unnecessary, at 207. Advantageously, if the existing model does not predict the new value, but if the new value is included in the model at 207, something else may become predictable because some other data in the model is no longer necessary and may be removed at 207, thereby keeping the model limited in data size. Thus, the present invention may be used to improve existing models in an intelligent fashion starting with the premise that a model is in place with some analysis, and that model analysis can be used from a mathematical point of view to help incorporate new data, either by saying the measurement is not adding any significant benefit to this model, the measurements disagree with the model, or the measurement is a new point.
In the context of RF drive test data collection, mode of operation 300 could lead to more efficient procedures for updating model parameters. For example, if while driving a pre-planned route it is observed at 303 that the current data being collected was repetitive and consistent with the current model. That is, an insignificant amount of new information was being learned. Then the MMD (drive-test vehicle) could be directed at 305 to a region where the model had less statistical reliability, such as an area of sparse data. This would allow more effective use of expensive drive test resources.
An MMD may be augmented to measure radiation levels or another hazardous condition or material. A desired behavior the device may demonstrate at 303, in accordance with the present invention, is that the model, possibly augmented by current measurements, may alert a user he or she is entering a dangerous area. This may be particularly useful in dealing with disaster response or military applications. If the MMD has a resident model of the dangerous conditions, versus space, then the model and/or related software may direct the user to a safer location or provide directions to lead the user out of the dangerous situation via the safest path, may be not the shortest path, but the safest path using trip planning.
Another application for embodiment 300 may be as a tracking function. This embodiment may be used to help track where a released substance is going. For example, where there has been a release of some pollutant or the like, someone may be sent to measure where the pollutant is and he or she may want to keep up with the pollutant so they can follow it to track it. So if an MMD operated by the user has a model, such as provided at 301, and the user is making measurements at 302, the user may be able to evaluate where he or she is located relative to a pollutant plume, or the like, at 303. The model may indicate the plume should be going in a particular direction, the user can test that determination and the model software may confirm the plume is moving in that direction or not, and in combination with previous measurements, augment the model, as discussed above in relation to embodiment 200.
The model, based on current reading or other goals, may influence, for example, where the user goes, how fast the measurements are taken, or other parameters based on the model. Embodiment 300 uses the model information, and computing from it, provides guidance at 304 or 305 on some task that is being carried out by a MMD user, either to make more measurements, to go to a specific place, or carry out a task. Embodiment 300 is made possible by a model present in the MMD. This embodiment may also use a current measurement as an alarm alerting the user of the MMD to a danger, direct the user to carry out a task, or trigger an inquiry based on the model present in the MMD.
Embodiment 400 provides a user an ability to locate and know where he or she is located relative to some variable that is being measured. For example, a person my be assigned to remain at some point on the aforementioned pollutant plume, such as someone who is to stay at the head of the plume. If this user momentarily loses track of where he or she is, they may make a measurement. A model of the plume may provide the most likely place that the user may be with respect to the distribution of this gaseous plume, based on that current measurement. As may be the case with this gaseous plume example, the model might not be a static model, it may be updated from some other source. Similarly, if a user is not in a mode of measuring for model enhancement, for example a user in a disaster response management mode or the like, updates to the model and use of current measurements may be used to tell the user where they are relative to the modeled event or situation.
Therefore, the present invention may guide various forms of using the model and/or MMD, depending on the combination of the measurements and what the model predicts at one point or another (502). Guidance may be provided from whichever embodiment is appropriate, which mode should be used, such as, should a shift into the acquisition mode (503) be made or a shift into a use and device mode (504). So more complicated scenarios can be built based on having a model available to the MMD.
Furthermore, with the computational capability that is provided by current cell phones, PDAs and the like, multiple models may be resident on a device with multiple measurements being made by the device. So combinations of resident models and/or ongoing measurements are possible in accordance with the present invention. For example, the results of a phone coverage measurement versus the concentration of dangerous substance models may be used to refine a user inquiry for a better phone connection. Thus, when an RF coverage inquiry above might result in advice to move into a region of great danger, a combination of the two models might result in directions to a location of safety with the best available coverage. As another example, when measuring hazardous conditions, the communications at one point might not be very good but an RF model might be used to locate a best position from which to forward findings. Similar combinations that do not necessarily involve danger but that are more favorable from multiple points of view are contemplated. For example, a model that provides the density of restaurants as a function of position, and another model which gave the density of traffic as a function of position within one phone, could act as a guide for finding a restaurant without being caught in a traffic jam. In each of the above examples, both models could be resident on the wireless phone and in some cases collecting data that augments the models.
Although the present invention and its advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims. Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the disclosure of the present invention, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized according to the present invention. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.
The present application is related to co-owned, co-pending U.S. patent application Ser. No. 10/306,940, filed on Nov. 27, 2002, entitled “SYSTEMS AND METHODS FOR MEASUREMENT AND/OR CONTROL USING MOBILE PROBES, the disclosure of which is incorporated herein by reference.
