WO2015054384A1

WO2015054384A1 - Method and apparatus for environment visualization in an electronic equipment facility

Info

Publication number: WO2015054384A1
Application number: PCT/US2014/059689
Authority: WO
Inventors: Clifford Federspiel; Sunil Doulatram AHUJA; Peter Christian VARADI
Original assignee: Vigilent Corporation
Priority date: 2013-10-08
Filing date: 2014-10-08
Publication date: 2015-04-16

Abstract

Method and apparatus for environment visualization in an electronic equipment facility are disclosed. The method comprises receiving input environmental data comprising sensor location and sensor data obtained from a plurality of sensors, derivative of sensor data, data obtained from an external database, or data input manually, wherein the input environmental data corresponds to locations within the facility that are not all located in the same plane, creating an environmental model of at least one of the facility or a three-dimensional model surface within the facility, based on the input environmental data, receiving a defined surface comprising a surface within the facility, or a subset of the three-dimensional model surface, computing the value of the environmental model at a plurality of locations along the defined surface to generate computed environmental data for the plurality of locations, and representing the computed environmental data as a graphic on a digital display.

Description

METHOD AND APPARATUS FOR ENVIRONMENT VISUALIZATION IN AN ELECTRONIC EQUIPMENT FACILITY

BACKGROUND

Field of the Invention

[0001] Embodiments of the present invention generally relate to environment management systems and, more particularly, to a method and apparatus for environment visualization in an electronic equipment facility.

Description of the Related Art

[0002] Datacenters, server rooms, or similar electronic equipment facilities generally include an arrangement of electronic equipment in racks or bays. The electronic equipment is sensitive to environmental factors such as temperature, humidity, and the like. Therefore, an environment suitable for operation of electronic equipment needs to be maintained in such facilities. Suitable sensors are used to measure the environmental data for monitoring and helping maintain such environmental factors desirably. Visualizing monitored environmental data within the facility is an important tool in managing the environmental conditions.

[0003] Some conventional solutions yield only planar (two dimensional) visualization data. Other solutions require deploying sensors in a planar fashion in facilities. However, in various facilities, such as data centers and telecom offices, racks and bays have a height that varies from one meter to four meters. Further, the height of the sensors varies based on the location of equipment installed in the racks and bays, and the type of equipment installed in the racks and bays. Accordingly, in such and several similar situations, it is impractical, and even infeasible to deploy sensors in a plane, that is, at a uniform height above the facility floor.

[0004] Therefore, there is a need in the art for a method and apparatus for environment visualization in an electronic equipment facility.

SUMMARY

[0005] Embodiments of the present invention include a method and apparatus for environment visualization in an electronic equipment facility, the method and apparatus substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.

[0006] These and other features and advantages of the present disclosure may be appreciated from a review of the following detailed description of the present disclosure, along with the accompanying figures in which like reference numerals refer to like parts throughout.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 is a schematic illustration of an electronic equipment facility incorporating an apparatus for environment visualization, according to one or more embodiments;

[0008] Figure 2 is a block diagram of the apparatus for environment visualization incorporated in the facility of Figure 1 , according to one or more embodiments;

[0009] Figure 3 is a schematic illustration of a virtual surface in the facility of Figure 1 , according to one or more embodiments;

[0010] Figure 4 is a schematic illustrating visualization of environmental data along virtual two-dimensional and three-dimensional surfaces in the facility on a computer screen, according to one or more embodiments; and

[0011] Figure 5 is a flowchart of a method for environment visualization in the facility, as performed by the apparatus of Figure 2, according to one or more embodiments.

[0012] While the method and apparatus is described herein by way of example for environment visualization in an electronic equipment facility, those skilled in the art will recognize that the method and apparatus for environment visualization in an electronic equipment facility is not limited to the embodiments or drawings described. It should be understood, that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed. Any headings used herein are for organizational purposes only and are not meant to limit the scope of the description or the claims. As used herein, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words "include", "including", and "includes" mean including, but not limited to.

DETAILED DESCRIPTION

[0013] Embodiments of the present invention generally relate to environment visualization in an electronic equipment facility. Multiple sensors for monitoring environmental parameters, for example, temperature, humidity, pressure, power consumption, and the like, are deployed throughout the facility, and generate measurements pertaining to one or more such environmental parameters. The sensors are installed as is convenient or feasible, for example, in an unordered fashion in the facility, and the sensors are not required to be located to conform to an ordered scheme, such as an array or a plane. Location of each sensor providing the measurement of environmental parameters is known or determined. The measurement data from the sensors and the location of the sensors, or input environmental data, includes one or more of data acquired from sensors in real-time, data acquired from a database that stores sensor data recorded at an earlier time, or data corresponding to one or more locations within the facility input by an operator of the apparatus.

[0014] According to various embodiments, the input environmental data is extrapolated and/or interpolated to create an environmental model of the facility. The environmental model of the facility is usable to compute environmental data at any location within the facility. The environmental model is used to generate computed environmental data along desired shapes or forms or a defined (real or virtual) surface within the facility. The surface may be two-dimensional or three-dimensional, and may be defined manually, for example, by a user of the apparatus, or the surface may be selected by the user from one or more pre-defined surfaces. For example, the surface may be defined as a cuboid corresponding to a real surface, for example, surface of a rack in the facility, or the surface may be defined as a virtual cylindrical shape enclosing electronic equipment. The surface is modeled as a grid having grid points corresponding to pixels needed to visualize the environment along the defined surface. Using the environmental model and the location of the grid points, environmental data is computed at the grid points. The computed environmental data for grid points corresponding to the defined surface is converted to displayable pixel data corresponding to the defined surface. The pixel data is used to generate a visualization of the environment along the defined two- dimensional or three-dimensional surface. Visualization of environmental data along various surfaces provides beneficial insight into the environmental dynamics within the facility, and enables better management of environmental parameters within the facility, for example, to improve performance, reduce cooling costs, enhances longevity of equipment, improved utilization of sensors, among others.

[0015] Various embodiments of a method and apparatus for environment visualization are described. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of claimed subject matter. However, it will be understood by those skilled in the art that claimed subject matter may be practiced without these specific details. In other instances, methods, apparatuses or systems that would be known by one of ordinary skill have not been described in detail so as not to obscure claimed subject matter.

[0016] Some portions of the detailed description that follow are presented in terms of algorithms or symbolic representations of operations on binary digital signals stored within a memory of a specific apparatus or special purpose computing device or platform. In the context of this particular specification, the term specific apparatus or the like includes a general-purpose computer once it is programmed to perform particular functions pursuant to instructions from program software. Algorithmic descriptions or symbolic representations are examples of techniques used by those of ordinary skill in the signal processing or related arts to convey the substance of their work to others skilled in the art. An algorithm is here, and is generally, considered to be a self-consistent sequence of operations or similar signal processing leading to a desired result. In this context, operations or processing involve physical manipulation of physical quantities. Typically, although not necessarily, such quantities may take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, data, values, elements, symbols, characters, terms, numbers, numerals or the like. It should be understood, however, that all of these or similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout this specification discussions utilizing terms such as "processing," "computing," "calculating," "determining" or the like refer to actions or processes of a specific apparatus, such as a special purpose computer or a similar special purpose electronic computing device. In the context of this specification, therefore, a special purpose computer or a similar special purpose electronic computing device is capable of manipulating or transforming signals, typically represented as physical electronic or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the special purpose computer or similar special purpose electronic computing device.

[0017] Figure 1 is a schematic illustration of an electronic equipment facility 100 incorporating an apparatus for environment visualization, according to one or more embodiments. Figure 1 depicts a perspective view 104, a top view 106 and a front view 108 of the facility 100. The facility 100 is enclosed by boundary 102 such as walls 102. The facility 100 comprises electronic equipment 1 10, one or more sensors 120, and a visualization server 130. In some embodiments, the visualization server 130 is external to the facility 100, however, the visualization server 130 is communicably coupled to one or more components within the facility, for example, the sensors 120, the electronic equipment 1 10 or environment conditioning equipment (not shown) associated with the facility 100. The conditioning equipment may be located internal or external to the facility 100, but is operational to condition the environment within the facility. The conditioning equipment includes, without limitation, air conditioners, dehumidifiers, fans or blowers, boilers, chillers, and the like.

[0018] Several factors, such as diverse equipment in the facility, variations in equipment installation configurations, e.g. in the height, horizontal alignment, variations in sensor installation locations, e.g. on racks or servers due to lack of space, different shapes or structures in the facility that are irregular, generally require the equipment 1 10 or the sensors 120 to be arranged in an unordered manner within the facility 100.

[0019] For example, the sensors 120 are positioned throughout the facility 100 at unordered locations that are suitable to install the sensors 120 for recording environmental data at such locations. For example, rack-top temperatures are not in a plane when racks in the facility are of an unequal height. Sensors 120 are installed on or within the racks or bays of the equipment 1 10, on the boundary 102, or in the region separating the equipment 1 10 and the boundary 102. Sensors include, without limitation, wired or wireless sensors located in the facility for measuring environmental data including, but not limited to, dry bulb temperature, relative humidity, pressure, power consumption and other operational parameters of the equipment 1 10, operational parameters of the facility's conditioning equipment, and the like. Sensors also include devices that provide parameters derived from the sensor data, such as, for example, vertical temperature gradient, dew point temperature, absolute humidity, open-loop cooling influence, closed-loop cooling influence, reserve, estimation error, model predictions, control gains, and the like generally known in the art. Estimation error is error associated with the known measurement noise levels associated with the sensors 120. Cooling influence is the value of a transfer function between cooling actions and temperatures evaluated at a steady state. In some embodiments, one or more sensors 120 are installed within the equipment 1 10.

[0020] Figure 2 is a block diagram of the apparatus 180 for environment visualization incorporated in the electronic equipment facility 100 of Figure 1 , according to one or more embodiments. The apparatus 180 comprises a visualization server 130, communicably coupled with the equipment 1 10, the sensors 120, conditioning equipment (not shown), and a display computer 154 having a display 160, via a network 170.

[0021] The network 170 comprises equipment and cabling for transporting digital data between devices connected to the network 170. By way of example, and in no way limiting the scope of the invention, in certain embodiments, the network 170 may comprise multiple routers and switches (not shown) that transport traffic between the visualization server 130, the sensors 120, the equipment 1 10, and the display computer 154. Network 170 is in one embodiment, a communication network and may run the Internet Protocol (IP) suite. According to some embodiments, the network 170 comprises of direct wired or wireless connections between the various devices associated with the network 170.

[0022] The visualization server 130 is a computing device (e.g., a laptop, a desktop, a Personal Digital Assistant (PDA), a tablet, a mobile phone and/or the like). The visualization server 130 includes a Central Processing Unit (CPU) 132, support circuits 134, and a memory 136. The CPU 132 may comprise one or more commercially available microprocessors or microcontrollers that facilitate data processing and storage. The various support circuits 134 facilitate the operation of the CPU 132 and include one or more clock circuits, power supplies, cache, input/output circuits, transceiver, displays and the like. The memory 136 comprises at least one of Read Only Memory (ROM), Random Access Memory (RAM), disk drive storage, optical storage, removable storage and/or the like. According to some embodiments, the visualization server 130 is connected to the display computer 154, for example, via the network 170. The memory 136 includes an operating system 138, input environmental data 140, monitoring module 142, modeling module 144, environmental model 146, computed environmental data 148, visualization data 150 and visualization module 152. The operating system 138 may include various commercially available operating systems.

[0023] The monitoring module 142 receives the input environmental data from the sensors 120, and stores the input environmental data 140. In some embodiments, the monitoring module 142 communicates directly with the sensors, for example, over a wireless connection, and determines the sensor locations based on additional information such as geolocation information transmitted by the sensors, wireless signal strength triangulation, and other location techniques known in the art. In some embodiments, the sensor location is provided to the monitoring module 142 at the time of installation of the sensors 120 or the visualization software 130. Location of the sensors is generally included in the input environmental data 140. In some embodiments, the monitoring module 142 receives input environmental data 140 manually, for example using one or more of an input device (not shown) coupled communicably to the visualization server 130. For example, an operator of the apparatus 180 may manually input or otherwise provide one or more environmental data as an input, corresponding to a particular location or region in the facility 100, or for the entire facility 100. In some embodiments, input environmental data 140 is extracted from a database (not shown) communicably coupled to the visualization server 130. Such a database includes sensor data (including sensor location), processed or derivative sensor data, and other data that is pertinent to the environmental parameters being visualized, and may include historical environmental data of the facility, or similar other facilities, as will occur readily to those skilled in the art.

[0024] The modeling module 144 computes the environmental model 146 of the facility 100 using the input environmental data 140. According to several embodiments, the modelling module 144 uses interpolation techniques, extrapolation techniques, or both, on the input environmental data 140 to create the environmental model 146 of the facility 100. Creating the environmental model 146, which is a set of one or more mathematical functions, includes solving for function parameters, weights or coefficients to create the mathematical function(s) capable of providing an estimated value of an environmental parameter, for a given location within the facility. The modelling module 144 employs various interpolation and/or extrapolation based modelling techniques known in the art, according to the available input environmental data, to solve for function parameters to generate the environmental model 146. Several known techniques for determining aforementioned function parameters include, but are not limited to, Gaussian elimination and least squares regression fitting, and the environmental model 146 includes a set of one or more mathematical functions including basis functions such as Gaussian functions and inverse distance functions, among several other suitable known functions that will occur readily to those skilled in the art.

[0025] The function parameters are selected such that the computing the environmental model 146 at sensor locations yields the value of environmental parameters to match with the values of the environmental parameters (or input environmental data) measured by sensors at the sensor locations. According to some embodiments, the functional parameters are selected such that the environmental model 146 yields the computed environmental values to accommodate errors or noise levels typically associated with the sensors used. According to some embodiments, the basis functions of the environmental model 146 are centered around a sensor location. The environmental model 146 comprises a weighted sum of the basis functions, the function parameters and weights are determined such that the weighted sum of the basis functions yields computed environmental values that are identical or nearly identical (e.g., within error ranges corresponding to known noise levels of the sensors) to the environmental values measured by the sensors for a given sensor location.

[0026] In one embodiment, the environmental model 146 is chosen as a linear combination of three-dimensional Gaussian functions, with the mean values of the Gaussian functions centered at the sensor locations, and the standard deviation of the Gaussian functions is proportional to the shortest distances from other sensors along each coordinate direction. Imposing the constraint that the environmental model 146 prediction for an environmental parameter at a location is equal to the measurement of the sensor at the location yields a set of equations that can be solved either using Gaussian elimination if the system is well-posed, or using least- squares if the system is over or under-determined. The solution to the set of equations yields the weights for each Gaussian function, and various such Gaussian functions are then combined to define the environmental model 146.

[0027] According to some embodiments, the basis functions are selected according to the defined surface for visualization of environmental data. The basis functions are representative of the defined surfaces, for example, for visualizing environmental data along isosurfaces, which are likely to be non-planar, basis functions that are representative for non-planar surfaces are used for providing optimal results. Similarly, for visualizing environmental data along an intersection of plane(s), basis functions that are representative of an intersection profile of planes, are used. Basis functions representative of a particular surface generally provide results with relatively lower errors for such a surface, and conversely, basis functions representative of a particular surface will provide results having relatively higher errors for surfaces other than such a surface.

[0028] In some embodiments, the modelling module 144 further excludes known volumes from the environmental model 146, for example, walls, pillars, and the like. Such exclusion requires solving boundary value problems to determine function parameters, weights or coefficients for the volume(s) excluded from consideration for creating the environmental model 146.

[0029] The environmental model 146 is created based on the input environmental data 140 relating to one or more environmental parameters, for example, temperature, pressure, humidity, among others, and the environmental model 146 includes one or more models to provide estimated values corresponding to one or more environmental parameters. The environmental model 146 can be used to compute an estimated (or modelled) value of an environmental parameter at any given location within the facility 100.

[0030] The modeling module 144 also generates the computed environmental data 148 corresponding to one or more locations in the facility 100 using the environmental model 146. According to some embodiments, the computed environmental data 148 is generated corresponding to points on a defined surface of interest, for example, a surface for which environment visualization is desired. The surface may be defined according to several different definition techniques, for example, as a grid, as a mathematical function, or other definition techniques generally known in the art. Grid points of a surface generally refer to a set of points sufficient to resolve the surface, and arranged as a grid along the surface the grid points represent. For surfaces defined as a grid, the modelling module 144 generates computed environmental data 148 using the location coordinates of grid points of the surface and the environmental model 146. If a higher resolution of visualization is required than feasible using the grid points, the modelling module 144 interprets pixels required to visualize environmental data at desired resolution as grid points, and generates computed environmental data 148 using the location coordinates of grid points corresponding to pixels required. For surfaces defined as mathematical functions, the modelling module 144 interprets pixels required to visualize environmental data on a computer screen as grid points, and generates computed environmental data 148 using the location coordinates of such grid points of the surface and the environmental model 146. The modelling module 144 is capable of defining pixels required, or the pixels required can be provided as an input by an operator of the visualization server 130. In general, the surface definitions are not limited to the definitions described above, and any known surface definition techniques may be used to generate computed environmental data 148 for the purpose of environment visualization along the surface.

[0031] The visualization module 150 converts the computed environmental data 148, for example, corresponding to a set of grid points of a defined surface within the facility 100, to visualization data 152 usable for visualizing the environment along the defined surface. According to some embodiments, the visualization data 152 comprises pixel information to display the visualization of the environment along the defined surface.

[0032] As used herein, the terms "grid points" and "pixels" correspond to the surface definitions and the visualization of such surface, respectively. Computed environmental data corresponding to grid point locations is converted to visualization data or pixel data for visualizing the environmental data. In several embodiments, a complete set of grid points corresponds to a complete set of pixels required to visualize the environmental data at a desired resolution, and therefore, a one-to-one correspondence exists between the grid points and the pixels. According to some embodiments, instead of generating the computed environmental data 148 for the complete set of grid point, a subset of the grid points is selected, and computed environmental data 148 is generated for the subset of grid points. For example, the subset includes one-tenth of the normal set grid points, and the subset of grid points may be distributed uniformly or non-uniformly along the surface. Using linear interpolation, the computed environmental data 148 values for the intermediate grid points (not included in the subset of grid points) is estimated. The visualization module 150 then converts the computed environmental data 148 (partially computed using the environmental model 146, and partially estimated by using linear interpolation) to visualization data 152 or the complete set of pixels required to visualize the environmental data at the desired resolution. Such estimation increases the computational efficiency of the apparatus 180. This and similar estimation techniques may be used for a desired balance between the computational efficiency, and accuracy of the resolution, as will occur readily to those skilled in the art without departing from the scope and spirit of the present invention.

[0033] In some embodiments, the visualization module 150 sends the visualization data 152 to a computer screen, for example, to the display 160 of the display computer 154, to display the visualization of the computed environmental data 148 overlay on an actual or representative image of the facility 100, for example, as illustrated further with respect to Figure 3. Examples of visualization module 150 include, without limitation, commercially available software packages such as MATLAB, MATPLOTLIB, GNUPLOT, and TECPLOT, among others. According to some embodiments, the visualization module 150 further includes functionality for providing preselected surfaces or volumes for visualization to an operator of the apparatus 180. The preselected surfaces or volumes include general purpose investigative visualization surfaces, or special purpose investigative visualization surfaces for identifying issues of particular types or associated with particular environmental parameters. A set of investigative visualization surfaces or volumes for high temperature may include isosurfaces for temperatures, or other parameters matching a predetermined criterion, for example, for temperatures exceeding a predefined threshold temperature value.

[0034] The display computer 154 is a computing device (e.g., a laptop, a desktop, a Personal Digital Assistant (PDA), a tablet, a mobile phone and/or the like) as are generally known in the art. The display computer 154 is associated with the display 160, and the display computer 154 is capable of displaying visualization data, for example, pixel information, on the display 160. The display 160 is a computer screen, and includes digital or analog displays generally known in the art and capable of displaying visualization data, such as pixel information. According to some embodiments, the display computer 154 receives instructions or inputs from an operator of the apparatus 180, and communicates them to the visualization server 130, for example, over the network 170. According to some embodiments, the operator of the apparatus 180 uses the display computer 154 for several operations including defining a surface or selecting one or more of pre-defined surfaces, selecting preferred visualizations, portions of visualizations therein, and the like, and communicate such operations to the visualization server.

[0035] Figure 3 is a schematic illustration of a planar surface 302 within the facility 100 of Figure 1 , according to one or more embodiments. The planar surface 302 is defined as a set of grid points 304 in the plane of the surface 302. The modeling module 144 generates computed environmental data 148 for grid points 304. The visualization module 150 converts the computed environmental data 148 to visualization data 152 for display, as a graphic on a computer screen, for example, as illustrated further with respect to Figure 4. According to some embodiments, the planar surface 302 is defined as a mathematical function. In such embodiments, the modelling module 144 determines density and arrangement of pixels required to generate visualization at a desired resolution, and generates computed environmental data 148 for grid points corresponding to the determined pixels. According to some embodiments, the computed environmental data 148 values at the grid points are converted to RGB (Red, Green, Blue) values based on a color map, as is generally known in the art. For example, the color map is a visual representation varying continuously from dark red representing a high temperature value, to dark blue representing a low temperature value, and green representing intermediate temperature values.

[0036] Figure 4 is a schematic illustrating visualization of environmental data along virtual two-dimensional or three-dimensional surfaces 410, 420, 430 in the facility 100 on a computer screen, for example, the display 160, according to one or more embodiments. The surface 410 is a planar surface (two-dimensional), for example, a subset of the surface 302 of Figure 3. The visualization module 150 converts the computed environmental data 148 corresponding to the grid points of the surface 410, to visualization data 152, which is displayed as the visualization graphic 412 of the environmental data corresponding to the surface 410. The environment visualization may include one or more environmental parameters, including, but not limited to temperature, pressure, humidity, power consumption, cooling influence, and redundancy, among others. Similar to the visualization graphic 412 corresponding to the planar surface 410, visualization graphic 422 corresponding to the cylindrical surface 420 and visualization graphic 432 corresponding to the partial hemispherical surface are generated by the apparatus 180 of Figure 2. For example, computed environmental data 148 is calculated for several points on the surfaces 410, 420 and 430 using the location coordinates of such points, and the environmental model 146. The computed environmental data 148 is converted to visualization 152 data or pixels, displayable on the display 160. The surfaces 410, 420 and 430 are virtual surfaces, that is, the surfaces 410, 420 and 430 do not correspond to an object within the facility 100, although the surfaces 410, 420 430 may intersect objects within the facility 100. However, visualizations for surfaces corresponding to a real surface of an object within the facility, for example, surface of a rack or other equipment, may be created in a similar manner using the techniques described above.

[0037] The surfaces 410, 420, 430 may represent a pre-defined surface, a surface defined by an operator of the apparatus 180, or an isosurface according to an environmental parameter of interest, and the like, useful in visualizing, analyzing or isolating issues pertaining to the environment within the facility. While specific surface shapes are illustrated by way of example in Figure 4, the visualization is not limited to these shapes, and visualization of any surface(s) that are defined can be generated using the techniques described above. Further, the techniques may readily be extended to visualizing volumes, such that multiple surfaces can be grouped to visualize a volume, or a surface could be used to visualize a cross section within a volume. According to some embodiments, the sensors 120 and the visualization server 130 are not displayed on the computer screen.

[0038] Using the techniques described above, several computer-generated color maps, contours, or other graphic representations of the environment are used to localize an environmental condition, and investigate the extent of the condition, for example, the location of excessive temperatures, and the extent (quantity) of the excessive temperatures.

[0039] According to some embodiments, the defined surface comprises selecting at least one pre-defined surface for visualizing an environmental parameter within a facility. According to some embodiments, one or more pre-defined surfaces or volumes are selected by an operator of the apparatus 180, to localize visually, the hottest area, space or volume within the facility 100. According to some embodiments, the visualization module 150 provides a general purpose sequence of pre-defined surfaces or volumes to the operator for systematically localizing an environmental condition and the extent of the condition. According to some embodiments, the visualization module 150 provides a specialized sequence of predefined surfaces or volumes to the operator in response to a condition or an issue articulated by the operator, for example, by way of a selection from a menu list of selectable issues. For example, if the location and extent of an excessively hot area is a suspected issue, in one embodiment, the visualization module 150 provides a visualization of temperature on a pre-defined sequence of planes, e.g. a first plane, and a second plane perpendicular to the first plane at a location within the hot area. According to some embodiments, the visualization module 150 determines and preselects one or more isosurfaces visualizing temperature, corresponding to parameters values that exceed a predetermined threshold for a given parameter.

[0040] According to some embodiments, the modelling module 144 creates the environmental model 146 for a real or virtual three-dimensional model surface (not shown), for example, pre-defined by an operator of the apparatus 180. In such embodiments, the input environmental data 140 is interpolated and/or extrapolated to create the environmental model 146 of the model surface, similar to the techniques described above. Creating the environmental model 146, which is a set of one or more mathematical functions or weighted mathematical functions, includes solving for function parameters, weights or coefficients to create the mathematical function(s) capable of providing an estimate value of an environmental parameter, for a given location on the pre-defined surface. The modelling module 144 employs various interpolation and/or extrapolation based modelling techniques known in the art, according to the available input environmental data, to solve for weights to generate the environmental model 146 for the model surface. Several known modelling techniques include, but are not limited to, Gaussian elimination, least squares regression fitting, basis functions such as Gaussian functions, inverse distance functions, among several other suitable known functions that will occur readily to those skilled in the art. In some embodiments, the modelling module 144 further excludes section of surfaces corresponding to known volumes from the environmental model 146, for example, walls, pillars, and the like. Such exclusion requires solving boundary value problems to determine weights, function parameters for the volume(s) excluded from consideration for creating the environmental model 146. The environmental model 146 of the pre-defined surface can be used to compute an estimated (or modelled) value of an environmental parameter at any point, or a subset of the model surface.

[0041] According to some embodiments (not shown), the environmental model 146 is created for a top surface of an electronic equipment, for example a server rack. In such an embodiment, environment visualization for the top surface of the rack or a subset thereof can be generated using techniques described above. The environmental model 146 of model surface is usable for generating environment visualization for any subset of such a surface using similar techniques to those described above.

[0042] Figure 5 is a flowchart of a method 500 for environment visualization in an electronic equipment facility, as performed by apparatus 180 of Figure 2, according to one or more embodiments. The method 500 starts at step 502, and proceeds to step 504 at which the method 500 receives or acquires input environmental data. The input environmental data is acquired, for example, from one or more of multiple sensors in real-time, for example the sensors 120 of Figure 1 , disposed in an electronic equipment facility, from a database that store sensor data and other relevant environmental data, or provided by manual input. The input environmental data, for example, the input environmental data 140 of Figure 2, corresponds to locations that are unordered, for example, located according to the convenient install position of various sensors. According to some embodiments, the locations for which input environmental data is provided do not all lie in the same plane. According to some embodiments, the input environmental data includes location data to which the environmental data corresponds. For example, if the environmental data corresponds to temperature recorded by the sensors, then such environmental data also includes the location of the sensors.

[0043] Location of the sensors may be obtained in several ways, for example, directly from sensors that are configured to provide the location, or from a database that is operable to provide the location to the method 500, or be input manually by an operator, or be determined using geo-location techniques, wireless signal strength triangulation, among other methods know in the art. The location could be transmitted with the environmental data, or be stored separately in a configuration file or database. The location of the sensors may be provided according to Cartesian coordinates, using a corner of the facility 100 of Figure 1 as a reference frame for the coordinate system, for example, to yield a sensor location using X, Y and Z coordinates. Alternate coordinate systems may be used equivalently for providing the location of the sensors in the facility.

[0044] The method 500 proceeds to step 506, at which the method 500 defines an environmental model, for example the environmental model 146 of Figure 2 or an environmental model 146 of a pre-defined surface (not shown), based on the input environmental data acquired at step 504. According to some embodiments, the method 500 defines the environmental model as a set of one or more mathematical functions comprising one or more of weights, coefficients and/or function parameters. The method 500 employs several known techniques such as Gaussian elimination, least squares regression, Gaussian functions, inverse distance function, and the like to yield the function parameters and weights or coefficients to define the environmental model for the facility, which is then stored for further use. In several embodiments, the method 500 employs boundary value problems to determine additional equation parameters to exclude known volumes from the environmental model. The environmental model can yield an estimated value of one or more environmental parameters for various locations within the facility. [0045] The method 500 proceeds to step 508, at which the method 500 uses the environmental model defined at step 506 to generate computed environmental data for grid points corresponding to a surface, for example, a surface defined by a user of the apparatus 180 of Figure 2. The method 500 computes the environmental data for grid points by supplying the location coordinates of the grid points to the environmental model. The method 500 computes the value of the environmental model for the given location coordinates, to yield an estimated value, or computed environmental data of the environmental parameter(s) for the given locations or grid points.

[0046] The method 500 proceeds to step 510, at which the method 510 converts the computed environmental data to visualization data. The visualization data comprises pixels that can be used to visualize the environmental data on a computer screen, in different colors, shades, patterns, combinations thereof, or in other visual distinguishing schemes. At step 512, the visualization data, which is a representation of the computed environmental data, is displayed on a computer screen, for example as illustrated by the display 160 of Figure 4. According to some embodiments, the visualization data is displayed as an overlay to an actual or representative image of the facility, for better comprehension of the visualization data. The visualization data or pixels are displayable as a graphic on a computer screen and includes, for example a color map, contour or other graphic display formats known in the art. The method 500 uses visualization techniques, including volumetric display using isosurfaces or clouds, and other techniques well known in the art for displaying the visualization data. The method 500 proceeds to step 515, where the method 500 ends.

[0047] According to some embodiments, the method 500 does not implement step 508, and instead implements a modified step (not shown). At the modified step, the method 500 generates, using the environmental model, computed environmental data for a subset of grid points corresponding to a surface defined by a user of the apparatus 180. The method 500 then estimates computed environmental data for all grid points for the defined surface by extrapolating and/or interpolating the computed environmental data for the subset of grid points. The modified step yields the computed environmental data corresponding to the entire defined surface, similar to the step 508. While the modified step approximates several data points in the computed environmental data, which may reduce visualization resolution or accuracy or both, however, the modified step makes the method 500 computationally faster.

[0048] Embodiments of the invention enable sensors installed at arbitrary locations in facilities, such as, data centers, telecommunications office, and the like. Sensors do not need to be oriented in planes, which is often necessary in data centers and telecom offices which have racks or bays that typically have different dimensions, such as unequal height. Embodiments of the invention enable visualization of data independent of the number, location, or orientation of the sensors, and the visualization may be performed over various conceivable surfaces or volumes. The sensors need not be located in the surface or volume being visualized, e.g. a cylindrical arrangement, to visualize the environmental data along a cylindrical surface. Further, according to several embodiments, one sensor provides data corresponding to multiple surfaces, e.g. planes, at the same time, enabling better utilization of the sensor, and may lead to reduction in the number of sensors required.

[0049] Various elements, devices, modules and circuits are described above in association with their respective functions. These elements, devices, modules and circuits are considered means for performing their respective functions as described herein. While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims

1 . A computer implemented method for environment visualization within a facility, comprising:

receiving input environmental data of the facility, the input environmental data comprising sensor location and at least one of sensor data obtained from a plurality of sensors, derivative of sensor data, data obtained from an external database, or data input manually;

creating an environmental model of at least one of the facility or a three- dimensional model surface within the facility, based on the input environmental data; receiving a defined surface comprising a surface within the facility, or a subset of the three-dimensional model surface;

computing the value of the environmental model at a plurality of locations along the defined surface to generate computed environmental data for the plurality of locations; and

representing the computed environmental data as a graphic on a digital display,

wherein at least one of the plurality of sensors is not located on the defined surface, or the plurality of sensors are not all located in a single plane, or both.

2. The method of claim 1 , wherein the input environmental data comprises at least one of temperature, pressure, humidity, power consumption, temperature gradient, cooling influence, reserve, sensor estimation error, or derivatives thereof.

3. The method of claim 2, wherein the graphic comprises visualization of at least one of temperature, pressure, humidity, power consumption, temperature gradient, cooling influence, reserve, sensor estimation error, or derivatives thereof.

4. The method of claim 1 , wherein the defined surface comprises at least one pre-defined surface for visualizing an environmental parameter within a facility.

5. The method of claim 1 , wherein the defined surface is at least one of a two- dimensional surface, a three-dimensional surface, part of a sphere surface, a cuboid surface, intersection of three or more planes, a surface corresponding to at least one part of equipment in the facility, or an isosurface corresponding to a parameter matching a predetermined criterion.

6. The method of claim 1 , wherein creating the environmental model comprises using a weighted sum of basis function to interpolate, extrapolate, or interpolate and extrapolate the input environmental data.

7. The method of claim 6, wherein the basis functions comprise a set of three- dimensional Gaussian functions, wherein

the mean value of the Gaussian functions are centered at the sensor locations,

the standard deviation of the Gaussian functions is proportional to the shortest distances from other sensors along each coordinate direction, and

weights of the Gaussian functions are computed such that the computed values of the environmental model yields substantially the same computed environmental data as the input environmental data for the sensor location.

8. The method of claim 6, wherein the basis functions are selected based on the defined surface.

9. The method of claim 1 , wherein the computing comprises generating computed environmental data for a subset of grid points corresponding to the defined surface, and estimating the computed environmental data for the grid points corresponding to the defined surface by at least one of extrapolating or interpolating the computed environmental data for the subset of grid points.

10. An apparatus comprising:

a monitoring module to receive input environmental data of a facility, the input environmental data comprising sensor location and at least one of sensor data obtained from a plurality of sensors, derivative of sensor data, data obtained from an external database, or data input manually, wherein the input environmental data corresponds to locations within the facility that are not all located in the same plane; a modelling module to create an environmental model of at least one of the facility or a three-dimensional model surface within the facility; and

a visualization module for

receiving a surface definition for a surface within the facility or a subset of the three-dimensional model surface,

computing the value of the environmental model at a plurality of locations along the defined surface to generate computed environmental data for the plurality of locations, and

representing the computed environmental data as a graphic on a computer screen.

1 1 . The apparatus of claim 10, wherein the input environmental data comprises at least one of temperature, pressure, humidity, power consumption, temperature gradient, cooling influence, reserve, sensor estimation error, or derivatives thereof.

12. The apparatus of claim 1 1 , wherein the graphic comprises visualization of at least one of temperature, pressure, humidity, power consumption, temperature gradient, cooling influence, reserve, sensor estimation error, or derivatives thereof.

13. The apparatus of claim 10, wherein the visualization module provides at least one pre-defined surface for visualizing an environmental parameter within a facility.

14. The apparatus of claim 10, wherein the modelling module creates the environmental model using a weighted sum of basis function to interpolate, extrapolate, or interpolate and extrapolate the input environmental data.

15. The apparatus of claim 14, wherein the basis functions comprise a set of three-dimensional Gaussian functions, wherein

the mean value of the Gaussian functions are centered at the sensor locations,

the standard deviation of the Gaussian functions is proportional to the shortest distances from other sensors along each coordinate direction, and weights of the Gaussian functions are computed such that the computed values of the environmental model yields substantially the same computed environmental data as the input environmental data for the sensor location.