Patent Publication Number: US-2022214324-A1

Title: System and method for predictively sensing harmful environmental conditions based on location and historical user data

Description:
FIELD OF THE DISCLOSURE 
     This disclosure generally relates to information handling systems, and more particularly relates to predictively sensing harmful environmental conditions based on geographic location and historical user data. 
     As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option is an information handling system. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes. Because technology and information handling needs and requirements may vary between different applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software resources that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems. 
     SUMMARY 
     An information handling system may include a sensor and a processor. The sensor may measure an environmental factor in an ambient environment immediately surrounding the information handling system. The processor may determine that the information handling system is in a first location, provide a first sampling frequency of the sensor based upon the first location, determine that the information handling system is in a second location, and provide a second sampling frequency of the sensor based upon the second location. The first sampling frequency may be different from the second sampling frequency 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       It will be appreciated that for simplicity and clarity of illustration, elements illustrated in the Figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements are exaggerated relative to other elements. Embodiments incorporating teachings of the present disclosure are shown and described with respect to the drawings presented herein, in which: 
         FIG. 1  is a block diagram illustrating an information handling system according to an embodiment of the current disclosure; 
         FIG. 2  is a flowchart illustrating a method for the dynamic adjustment of thresholds for sampling frequencies of sensors in an information handling system; 
         FIG. 3  is a flowchart illustrating a method of predicting environmental conditions to modify acquisition rates of the sensors of an information handling system; and 
         FIG. 4  is a block diagram illustrating a generalized information handling system according to another embodiment of the present disclosure. 
     
    
    
     The use of the same reference symbols in different drawings indicates similar or identical items. 
     DETAILED DESCRIPTION OF DRAWINGS 
     The following description in combination with the Figures is provided to assist in understanding the teachings disclosed herein. The following discussion will focus on specific implementations and embodiments of the teachings. This focus is provided to assist in describing the teachings, and should not be interpreted as a limitation on the scope or applicability of the teachings. However, other teachings can certainly be used in this application. The teachings can also be used in other applications, and with several different types of architectures, such as distributed computing architectures, client/server architectures, or middleware server architectures and associated resources. 
       FIG. 1  illustrates a green processing system  100 . Green processing system  100  represents an element of processing equipment that is designed and manufactured in accordance with various environmental sustainability goals, such as increased use of recycled and recyclable materials or materials that otherwise carry a lower carbon footprint in their manufacture, lower power consumption technologies, more healthy processing environments for the users of the processing equipment, and the like. In a particular embodiment, green processing system  100  is configured to monitor the processing environment in which the green processing system is utilized, or is projected to be utilized through the inclusion of various environmental sensors, and to dynamically adjust the data acquisition rates for environmental sensors to optimize the balance of keeping a user aware when in a higher potentially harmful environment and, when needed, to lower the rate of data acquisition by the environmental sensors, thereby reducing system resource load, lowering overall energy usage, and improving battery usage. 
     Green processing system  100  includes an information handling system  110  that includes environmental sensors  120  and an environmental control module  150 . Information handling system  110  represents a wide variety of types of computer systems, as needed or desired. As illustrated, information handling system  110  represents a laptop computer system, but the information handling system may be understood more broadly to represent other consumer oriented computer systems, such as tablet devices, cellular devices, smart phone, home desktop systems, other consumer oriented computer systems, as needed or desired. Moreover, information handling system  110  may be understood to represent a wide variety of types of commercial computer systems, such as slim client systems, workstations, office server systems, or other commercial computer systems, as needed or desired. Further, in its capacity to monitor and manage power consumption or processing resources, as described below, the teachings of the current disclosure may further be applied to datacenter equipment, such as server systems, blade- or sled-based processing systems, storage racks, I/O racks, switching racks, or other datacenter equipment, as needed or desired. 
     Environmental sensors  120  include various air quality sensors including a particulate matter sensor  122 , a CO 2  sensor  124 , a relative humidity/temperature sensor  126 , a barometric pressure sensor  128 , a volatile organic compound (VOC) sensor  130 , and a radon sensor  132 . Particulate matter sensor  122  represents a sensor that detects the presence of fine particulate matter in the ambient air around green processing system  100 . Fine particulate matter may include soot, dust, smoke, dirt, pollen, and the like. Fine particulate matter is typically measured in micrometers, and current environmental standards are concerned with fine particulate matter that is less than 2.5 micrometers in diameter. Hence a common particulate matter sensor may be designated as a PM2.5 sensor. CO 2  sensor  124  detects the amount of CO 2  in the ambient air around green processing system  100 . Various studies have shown that decision making and productivity issues may occur when CO 2  levels are greater than 1000 parts per million (ppm), and severe problems may occur at levels greater than 2500 ppm. It has been further understood that air recirculation in buildings may contribute to higher CO 2  levels. Relative humidity/temperature sensor  126  and barometric pressure sensor  128  represent sensors to detect atmospheric conditions, either as a function of the weather in the area of green processing system  100 , or as a result of the environmental conditioning in the vicinity of the green processing system. In either case, the atmospheric conditions surrounding green processing system  100  may have impacts on user health, productivity, sense of well-being, or the like. VOC sensor  128  represents a sensor that detects airborne chemicals or toxins that may have impacts on user health, productivity, sense of well-being, or the like. VOCs may include acetone, acetic acid, butanal, carbon disulfide, ethanol, alcohol, formaldehyde, methylene chloride, sulfur, or other compounds and may, in some cases, be considered as carcinogenic. VOCs may be present in the ambient air surrounding green processing system  100 , or may be outgassed from materials in the vicinity of the green processing system. Radon sensor  130  represents a sensor to detect radon in the ambient air surrounding green processing system  100 . Radon is a naturally occurring radioactive element that outgasses from the earth&#39;s surface, at rates which may vary due to the underlying geological strata at the particular location. However the concentration of radon in the ambient air surrounding green processing system  100  may be increased beyond the naturally occurring concentration due to poor ventilation or other environmental factors. 
     Other environmental sensors  120  include a light sensor  134 , a location sensor  136 , and a noise sensor  138 . Light sensor  134  represents a photodetector that operates to detect light in the ambient environment of green processing system  100 , and can include detectors for detecting the spectrum of the ambient light, including in the ultraviolet (UV) range, and can detect the brightness of the ambient light. Location sensor  136  represents various positional sensors of green processing system  100 , including a global positioning system (GPS), a wide area network (WAN) locator system, an accelerometer or other motion detector whereby the green processing system can determine relative location with respect to a fixed location determined by the GPS or WAN locator system, or other sensors configured to determine the location of the green processing system. Noise sensor  138  represents a microphone or other sound receiving sensor that can determine a frequency spectrum of the received sound in the ambient environment of green processing system  100 , the volume of the received sound, or the like. 
     It will be understood that each of sensors  120  may consume power within green processing system  100 , based upon the receipt and analysis of the various environmental factors measured by the various sensors. For example, while operating, particulate matter sensor  122  and CO 2  sensor  124  may consume on the order of 600 milliwatts (mW) of power. Other sensors  120  may similarly consume power within green processing system  100 . As such, operating all of sensors  120  simultaneously may result in an undue burden on the power resources of green processing system  100 , such as a battery or the like. Thus, it may be desirable to determine a sampling frequency for each of sensors  120 , based upon the type of ambient condition that is being measured, and the rate at which such conditions are likely to change. Moreover, each of sensors  120  may be understood to necessitate the consumption of system resources of information handling system  110 , such as processor cycles, memory resources, memory and I/O bandwidth, and the like. In particular, each one of sensors  120  may be associated with its own driver or other application programming interface (API) that utilizes processing resources to run. Thus, as with the power consumption described above, it may be desirable to minimize the amount of sampling done by each of sensors  120  in order to reduce the processing load on information handling system  110 . 
     Sensors  120  are each connected to environmental control module  150 . Here, environmental control module  150  may be understood to represent hardware needed to interface with one or more of sensors  120 , software, such as drivers and APIs needed to operate the sensors, or a combination thereof. In addition, environmental control module  150  operates to manage the sampling frequencies of sensors  120 , the power consumed by the sensors, the processing resources consumed by the sensors, and the like. As described further below, environmental control module  150  further operates to leverage historical data from sensors  120 , user location and location history data, external data resources, and the like, to modify the sampling frequencies, the power consumption, and the processing resource consumption of sensors  120  in order to intelligently optimize the performance of the sensors and of information handling system  110 , and to improve the health and wellbeing of the user of green processing system  100 . 
     The functions and features of green processing system  110 , and particularly of environmental control module  150  will be illustrated hereafter with reference to  FIGS. 2 and 3 , which provide flowcharts illustrating the functions and features of the green processing system. Note that the AQI indicators may be represented as a single number that aggregates the air quality as to a number of different environmental factors. For example, an AQI may be utilized that is an aggregation of particulate matter index, a CO2 index, a VOC index, or other separate indexes, as needed or desired. On the other hand, the AQI indicators may also be understood to represent each of the individual indexes. In this regard, as describe below, the actions taken can be based upon an aggregate AQI indication, upon separate AQI indications, or on a combination thereof. For example, where a user has a particular known susceptibility to particulate matter, the methods below can be understood in terms of a first flow for the aggregate AQI indication, and a second flow for the particulate matter index, and warnings and actions for the sensors related to the aggregate AQI indication can be taken separately, or in conjunction with the warnings and actions for the particulate matter sensor and the related particulate matter indication, as needed or desired. 
       FIG. 2  illustrates a method for the dynamic adjustment of thresholds for sampling frequencies of sensors in an information handling system utilizing indoor and outdoor air quality index (AQI) indicators based upon the context or location of the information handling system. The method starts at block  200 . Location information for the information handling system is gathered in block  202 . For example, one or more location sensor can determine the current location of an information handling system. A decision is made as to whether or not historical AQI information is available for the location in decision block  204 . If not, the “NO” branch of decision block  204  is taken and the method proceeds to block  206 , as described below. If historical AQI information is available, the “YES” branch of decision block  204  is taken, the historical the AQI information is utilized in block  236 , the user of the information handling system is notified of the key performance indicator (KPI) associated with the historical AQI information in block  238 , and the method proceeds to decision block  212 , as described below. Note here that, when the historical AQI information is used in block  236 , the historical AQI information is retrieved from a historical AQI database  234  that provides indexed AQI information for aggregated AQI indications and separate AQI indications, as needed or desired. Databases are known in the art, and the functions and features of the historical AQI database  234  will not be further described herein, except as needed to illustrate the current embodiments. 
     Returning to decision block  204 , when historical AQI information is not available, and the “NO” branch is taken, the location information from block  202  is passed to various AQI information providers in block  206 . Here, for example, a web interface of the information handling system may be invoked to gather the various AQI information from public or private sources of such information. Thus, where public AQI information is published in a location addressable form, the web interface can provide the location information to the public AQI information website to retrieve the AQI information for that location. On the other hand, where private AQI information is available, for example, on a subscription basis, the web interface can provide the location information to the private AQI information website, along with credential information to access the private AQI information, as needed or desired. 
     In either case, the AQI information providers return the associated AQI information for the location in block  208 . Here, in a first branch, the location information and the AQI information is stored in block  232  to historical AQI database  234  for future use. For example, at a future time, when the information handling system as returned to the particular location, the “YES” branch of decision block  204  can be taken and the AQI information can be retrieved from historical QAI database  234  for use in block  236 . In a second branch, the received AQI information is utilized to set one or more AQI threshold for the information handling system in block  210 . Here, for example, if a particular AQI indication is known to be particularly high or particularly low in a given location, a threshold for that AQI indication can be set at a level higher than the known level. In this way, any alerts generated are provided within the context of the known level for that AQI indication. 
     After the AQI thresholds are set in block  210 , or after the user of the information handling system is notified of the KPI associated with the historical AQI information in block  238 , a decision is made as to whether the AQI information has changed in decision block  212 . If not, the “NO” branch of decision block  212  is taken and the method returns to block  208  where the AQI information is retrieved for the location. If the AQI information has changed, the “YES” branch of decision block  212  is taken and the AQI thresholds are adjusted in block  214 , and a decision is made as to whether or not the AQI information has degraded in decision block  216 . If so, the “YES” branch of decision block  216  is taken, the measurement frequency for the associated sensors is increased in block  218 , and the AQI information for is measured by the information handling system in block  224 . If the AQI information has not degraded, the “NO” branch of decision block  216  is taken and a decision is made as to whether or not the AQI information has improved in decision block  220 . If so, the “YES” branch of decision block  220  is taken, the measurement frequency for the associated sensors is decreased in block  222 , and the AQI information for is measured by the information handling system in block  224 . If the AQI information has not improved, that is, when the AQI information as remained constant, the “NO” branch of decision block  220  is taken and AQI information for is measured by the information handling system in block  224 . 
     A decision is made as to whether or not the AQI as measured by the information handling system is greater than a threshold for that particular AQI in decision block  226 . If not, the “NO” branch of decision block  226  is taken and the method returns to block  224  where the AQI information for is measured by the information handling system. If the AQI as measured by the information handling system is greater than the threshold for the particular AQI, the “YES” branch of decision block  226  is taken, the AQI as measured by the information handling system is recorded to historical AQI database  234  in block  228 , the user is notified that the AQI as measured by the information handling system is greater than a threshold for that particular AQI in block  230 , and the method returns to block  208  where, the AQI information providers return the associated AQI information for the location of the information handling system. 
       FIG. 3  illustrates a method of predicting environmental conditions, such as the various AQI indications, in order to modify acquisition rates of the sensors of an information handling system based on historical AQI information. The method begins at block  300 . A future location of an information handling system is determined in block  302 . For example, a user may take a laptop computer system from a home location to a work location on a daily basis. Here, when the laptop computer system is presently at the home location, it can be determined that the future location will be the work location. Location information for the future location of the information handling system is gathered in block  304 . A decision is made as to whether or not historical AQI information for the future location is available in decision block  306 . If not, the “NO” branch of decision block  306  is taken and the method ends in block  326 . If historical AQI information for the future location is available, the “YES” branch of decision block  306  is taken, and the historical AQI information for the future location is read from a historical AQI database in block  308 . The future location information from block  302  is passed to various AQI information providers in block  310 , and the current AQI information from at the future location is received in block  312 . 
     A closest match between the historical AQI information for the future location and the current AQI information at the future location is compared to fine a closest match in block  314 , and a decision is made as to whether or not a correlation between the historical AQI information for the future location and the current AQI information at the future location is found in decision block  316 . If not, the “NO” branch of decision block  316  is taken and the method ends in block  326 . If a correlation between the historical AQI information for the future location and the current AQI information at the future location is found, the “YES” branch of decision block  316  is taken and the historical AQI information is divided into the associated component sensor data in block  318 . The relevant data from the historical AQI information is extracted in block  320 , and an expected AQI for the future location is predicted based upon the extracted information in block  322 . The user of the information handling system is notified of the predicted AQI for the future location in block  324 , and the method ends in block  326 . 
       FIG. 4  illustrates a generalized embodiment of an information handling system  400 . For purpose of this disclosure an information handling system can include any instrumentality or aggregate of instrumentalities operable to compute, classify, process, transmit, receive, retrieve, originate, switch, store, display, manifest, detect, record, reproduce, handle, or utilize any form of information, intelligence, or data for business, scientific, control, entertainment, or other purposes. For example, information handling system  400  can be a personal computer, a laptop computer, a smart phone, a tablet device or other consumer electronic device, a network server, a network storage device, a switch router or other network communication device, or any other suitable device and may vary in size, shape, performance, functionality, and price. Further, information handling system  400  can include processing resources for executing machine-executable code, such as a central processing unit (CPU), a programmable logic array (PLA), an embedded device such as a System-on-a-Chip (SoC), or other control logic hardware. Information handling system  400  can also include one or more computer-readable medium for storing machine-executable code, such as software or data. Additional components of information handling system  400  can include one or more storage devices that can store machine-executable code, one or more communications ports for communicating with external devices, and various input and output (I/O) devices, such as a keyboard, a mouse, and a video display. Information handling system  400  can also include one or more buses operable to transmit information between the various hardware components. 
     Information handling system  400  can include devices or modules that embody one or more of the devices or modules described below, and operates to perform one or more of the methods described below. Information handling system  400  includes a processors  402  and  404 , an input/output (I/O) interface  410 , memories  420  and  425 , a graphics interface  430 , a basic input and output system/universal extensible firmware interface (BIOS/UEFI) module  440 , a disk controller  450 , a hard disk drive (HDD)  454 , an optical disk drive (ODD)  456 , a disk emulator  460  connected to an external solid state drive (SSD)  462 , an I/O bridge  470 , one or more add-on resources  474 , a trusted platform module (TPM)  476 , a network interface  480 , a management device  490 , and a power supply  495 . Processors  402  and  404 , I/O interface  410 , memory  420 , graphics interface  430 , BIOS/UEFI module  440 , disk controller  450 , HDD  454 , ODD  456 , disk emulator  460 , SSD  462 , I/O bridge  470 , add-on resources  474 , TPM  476 , and network interface  480  operate together to provide a host environment of information handling system  400  that operates to provide the data processing functionality of the information handling system. The host environment operates to execute machine-executable code, including platform BIOS/UEFI code, device firmware, operating system code, applications, programs, and the like, to perform the data processing tasks associated with information handling system  400 . 
     In the host environment, processor  402  is connected to I/O interface  410  via processor interface  406 , and processor  404  is connected to the I/O interface via processor interface  408 . Memory  420  is connected to processor  402  via a memory interface  422 . Memory  425  is connected to processor  404  via a memory interface  427 . Graphics interface  430  is connected to I/O interface  410  via a graphics interface  432 , and provides a video display output  436  to a video display  434 . In a particular embodiment, information handling system  400  includes separate memories that are dedicated to each of processors  402  and  404  via separate memory interfaces. An example of memories  420  and  430  include random access memory (RAM) such as static RAM (SRAM), dynamic RAM (DRAM), non-volatile RAM (NV-RAM), or the like, read only memory (ROM), another type of memory, or a combination thereof. 
     BIOS/UEFI module  440 , disk controller  450 , and I/O bridge  470  are connected to I/O interface  410  via an I/O channel  412 . An example of I/O channel  412  includes a Peripheral Component Interconnect (PCI) interface, a PCI-Extended (PCI-X) interface, a high-speed PCI-Express (PCIe) interface, another industry standard or proprietary communication interface, or a combination thereof. I/O interface  410  can also include one or more other I/O interfaces, including an Industry Standard Architecture (ISA) interface, a Small Computer Serial Interface (SCSI) interface, an Inter-Integrated Circuit (I 2 C) interface, a System Packet Interface (SPI), a Universal Serial Bus (USB), another interface, or a combination thereof. BIOS/UEFI module  440  includes BIOS/UEFI code operable to detect resources within information handling system  400 , to provide drivers for the resources, initialize the resources, and access the resources. BIOS/UEFI module  440  includes code that operates to detect resources within information handling system  400 , to provide drivers for the resources, to initialize the resources, and to access the resources. 
     Disk controller  450  includes a disk interface  452  that connects the disk controller to HDD  454 , to ODD  456 , and to disk emulator  460 . An example of disk interface  452  includes an Integrated Drive Electronics (IDE) interface, an Advanced Technology Attachment (ATA) such as a parallel ATA (PATA) interface or a serial ATA (SATA) interface, a SCSI interface, a USB interface, a proprietary interface, or a combination thereof. Disk emulator  460  permits SSD  464  to be connected to information handling system  400  via an external interface  462 . An example of external interface  462  includes a USB interface, an IEEE 1394 (Firewire) interface, a proprietary interface, or a combination thereof. Alternatively, solid-state drive  464  can be disposed within information handling system  400 . 
     I/O bridge  470  includes a peripheral interface  472  that connects the I/O bridge to add-on resource  474 , to TPM  476 , and to network interface  480 . Peripheral interface  472  can be the same type of interface as I/O channel  412 , or can be a different type of interface. As such, I/O bridge  470  extends the capacity of I/O channel  412  when peripheral interface  472  and the I/O channel are of the same type, and the I/O bridge translates information from a format suitable to the I/O channel to a format suitable to the peripheral channel  472  when they are of a different type. Add-on resource  474  can include a data storage system, an additional graphics interface, a network interface card (NIC), a sound/video processing card, another add-on resource, or a combination thereof. Add-on resource  474  can be on a main circuit board, on separate circuit board or add-in card disposed within information handling system  400 , a device that is external to the information handling system, or a combination thereof. 
     Network interface  480  represents a NIC disposed within information handling system  400 , on a main circuit board of the information handling system, integrated onto another component such as I/O interface  410 , in another suitable location, or a combination thereof. Network interface device  480  includes network channels  482  and  484  that provide interfaces to devices that are external to information handling system  400 . In a particular embodiment, network channels  482  and  484  are of a different type than peripheral channel  472  and network interface  480  translates information from a format suitable to the peripheral channel to a format suitable to external devices. An example of network channels  482  and  484  includes InfiniBand channels, Fibre Channel channels, Gigabit Ethernet channels, proprietary channel architectures, or a combination thereof. Network channels  482  and  484  can be connected to external network resources (not illustrated). The network resource can include another information handling system, a data storage system, another network, a grid management system, another suitable resource, or a combination thereof. 
     Management device  490  represents one or more processing devices, such as a dedicated baseboard management controller (BMC) System-on-a-Chip (SoC) device, one or more associated memory devices, one or more network interface devices, a complex programmable logic device (CPLD), and the like, that operate together to provide the management environment for information handling system  400 . In particular, management device  490  is connected to various components of the host environment via various internal communication interfaces, such as a Low Pin Count (LPC) interface, an Inter-Integrated-Circuit (I2C) interface, a PCIe interface, or the like, to provide an out-of-band ( 00 B) mechanism to retrieve information related to the operation of the host environment, to provide BIOS/UEFI or system firmware updates, to manage non-processing components of information handling system  400 , such as system cooling fans and power supplies. Management device  490  can include a network connection to an external management system, and the management device can communicate with the management system to report status information for information handling system  400 , to receive BIOS/UEFI or system firmware updates, or to perform other task for managing and controlling the operation of information handling system  400 . Management device  490  can operate off of a separate power plane from the components of the host environment so that the management device receives power to manage information handling system  400  when the information handling system is otherwise shut down. An example of management device  490  include a commercially available BMC product or other device that operates in accordance with an Intelligent Platform Management Initiative (IPMI) specification, a Web Services Management (WSMan) interface, a Redfish Application Programming Interface (API), another Distributed Management Task Force (DMTF), or other management standard, and can include an Integrated Dell Remote Access Controller (iDRAC), an Embedded Controller (EC), or the like. Management device  490  may further include associated memory devices, logic devices, security devices, or the like, as needed or desired. 
     Although only a few exemplary embodiments have been described in detail herein, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of the embodiments of the present disclosure. Accordingly, all such modifications are intended to be included within the scope of the embodiments of the present disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. 
     The above-disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover any and all such modifications, enhancements, and other embodiments that fall within the scope of the present invention. Thus, to the maximum extent allowed by law, the scope of the present invention is to be determined by the broadest permissible interpretation of the following claims and their equivalents, and shall not be restricted or limited by the foregoing detailed description.