Information processing infrastructure, program, and system

Abstract

Provided is an information processing infrastructure comprising: an acquisition unit that acquires, via a plurality of wireless base stations disposed in a region corresponding to the information processing infrastructure, measurement data obtained by measuring, by radio waves, the health condition of a person located in the coverage area of the plurality of wireless base stations; and a condition determination unit that determines whether the health condition of the person is a dangerous condition on the basis of the measurement data acquired by the acquisition unit. The information processing infrastructure further comprises a RAN control unit that controls a RAN configured by the plurality of wireless base stations, and the acquisition unit may receive, from a measurement terminal located within the coverage area of the plurality of wireless base stations constituting the RAN, measurement data measured by the measurement terminal, via the wireless base stations. The information processing infrastructure may perform RAN control and AI processing (including RAN control AI processing, such as RAN Intelligent Controller (RIC), and non-RAN control AI processing).

Description

Information processing infrastructure, programs, and systems

[0001] The present invention relates to an information processing infrastructure, a program, and a system.

[0002] Patent Document 1 states that "attempts are being considered to place various sensors in living spaces to automatically adjust equipment such as air conditioners and lighting, and to provide resident monitoring services, health advice services, etc." [Prior art documents] [Patent documents] [Patent document 1] JP 2019-148963 A

[0003] Millimeter waves, with their high frequency, wide bandwidth, small size, light weight, low cost, and low interference, are expected to be used in home applications. Various application systems, such as non-contact sensing for home healthcare, monitoring in private spaces like bathrooms, and indoor security monitoring, are rapidly gaining attention. For example, spread-spectrum millimeter-wave radar technology and feature-point-based heart rate estimation algorithms have been reported to enable real-time measurement of heart rate intervals with an accuracy comparable to that of an electrocardiogram. High-sensitivity measurements have also been reported, enabling simultaneous monitoring of the movements of multiple people with a single radar. However, these technologies rely on analyzing data stored in storage, making it difficult to quickly detect and respond to threats to human health.

[0004] In the information processing infrastructure according to this embodiment, for example, an information processing infrastructure installed in a region collects measurement data obtained by measuring the health status of humans using millimeter-wave sensors or the like installed in the region via a wireless base station communicatively connected thereto, and determines whether the health status of humans is in a dangerous state by analyzing the data using AI (Artificial Intelligence) or the like. In the information processing infrastructure according to this embodiment, for example, in addition to determining the health status of humans, control of a radio access network (RAN) may also be performed. By running the RAN control function on a high-performance GPU (Graphics Processing Unit) server rather than a general-purpose server, the surplus computing resources can be utilized for AI processing. Types of AI processing include AI processing related to RAN control (sometimes referred to as RAN-controlled AI processing) and AI processing not related to RAN control (sometimes referred to as non-RAN-controlled AI processing).

[0005] An example of RAN control AI processing is RIC (RAN Intelligent Controller). RIC is a technology that uses AI to optimize RAN radio resources and automate RAN operations. RIC includes Non-RT RIC (Non-Real Time RIC) and Near-RT RIC (Near-Real Time RIC). Non-RT RIC is sometimes called Centralized RIC. Non-RT RIC is located inside SMO (Service Management and Orchestration), which manages and orchestrates the RAN. Non-RT RIC generates and notifies policies related to RAN control and sends information to Near-RT RIC. For example, the Non-RT RIC performs machine learning using data collected from the RAN to generate a trained model for RAN control and transmits it to the Near-RT RIC. The Near-RT RIC is sometimes called a Distributed RIC. Compared to the Non-RT RIC, the Near-RT RIC is located closer to the RAN nodes (RU (Radio Unit), DU (Distributed Unit), CU (Central Unit)) and controls the RAN nodes, resources, etc. The Near-RT RIC performs processing with higher real-time performance than the Non-RT RIC. The Near-RT RIC performs inference processing related to RAN control using, for example, a trained model acquired from the Non-RT RIC. RAN control AI processing is not limited to the RIC.

[0006] According to one embodiment of the present invention, there is provided an information processing infrastructure. The information processing infrastructure may include an acquisition unit that acquires, via a plurality of wireless base stations located in a region corresponding to the information processing infrastructure, measurement data that measures the health status of a person located within the coverage area of ​​the plurality of wireless base stations using radio waves. The information processing infrastructure may also include a condition determination unit that determines whether the health status of the person is in a critical state based on the measurement data acquired by the acquisition unit.

[0007] The information processing infrastructure may further include a RAN control unit that controls a RAN configured by the plurality of radio base stations, and the acquisition unit may receive the measurement data measured by a measurement terminal located within a coverage area of ​​the plurality of radio base stations that configure the RAN from the measurement terminal via the radio base station. The acquisition unit may further acquire risk information that indicates a risk that the health condition of the person in the area will become dangerous, and the information processing infrastructure may further include a measurement adjustment unit that, in response to the acquisition unit's acquisition of the risk information, transmits to the measurement terminal an increase instruction to increase the frequency of measurement and the frequency of transmission of the measurement data to the information processing infrastructure.

[0008] In any of the information processing platforms, the acquisition unit may further acquire risk information indicating the risk of the health condition of the person within the area becoming dangerous, and the information processing platform may further include a measurement adjustment unit that controls an increase in the number of measurement terminals that transmit the measurement data to the information processing platform within the coverage area in response to the acquisition unit acquiring the risk information.

[0009] In any of the information processing platforms, the measurement terminal may measure the health status of a person located within the space in which the measurement terminal is installed using radio waves, and the information processing platform may further include a measurement adjustment unit that adjusts the frequency of measurement by the measurement terminal and the frequency of transmission of the measurement data to the information processing platform based on the attributes of multiple people located within the space in which the measurement terminal is installed.

[0010] In any of the information processing platforms, the measurement terminal may measure the health status of a human being located within the space in which the measurement terminal is installed using radio waves, and the information processing platform may further include a presence determination unit that determines whether a human being is present within the space in which the measurement terminal is installed, and a terminal control unit that transitions the measurement terminal to a power-saving state when it is determined that no human being is present within the space in which the measurement terminal is installed.

[0011] Any of the information processing platforms may further include a memory unit that stores learning data including measurement data when a human's health condition is in a dangerous state, and a model generation unit that uses the plurality of learning data stored in the memory unit as teacher data to generate a judgment model by machine learning that determines whether the human's health condition is in a dangerous state from the measurement data obtained by measuring the human, and the state judgment unit may use the judgment model to judge whether the human's health condition is in a dangerous state from the measurement data obtained by the acquisition unit.

[0012] In any of the information processing platforms, the acquisition unit may further acquire attribute information representing the attributes of the human, and may further include a notification unit that, in response to the state determination unit determining that the human's health condition is in a dangerous state, notifies a notification destination according to the human's attributes of the determination result made by the state determination unit.

[0013] In any of the information processing platforms, the radio waves may be millimeter waves, and the condition determination unit may determine whether the human's health condition is dangerous based on the measurement data obtained by measuring the human using millimeter waves.

[0014] In any of the information processing platforms, the acquisition unit may further acquire risk information indicating the risk of the person being in a dangerous state within the area, and the status determination unit may execute a determination process at a frequency according to the risk information to determine whether the person located within the area is in a dangerous state.

[0015] According to one embodiment of the present invention, there is provided a program that, when executed by a computer, causes the computer to function as the information processing infrastructure.

[0016] According to one embodiment of the present invention, a system is provided. The system may include a plurality of information processing platforms and a management platform that manages the plurality of information processing platforms. Each of the plurality of information processing platforms may include an acquisition unit that acquires, via the plurality of wireless base stations, measurement data that measures the health state of a person located within the coverage area of ​​the plurality of wireless base stations that are located in an area corresponding to the information processing platform. Each of the plurality of information processing platforms may include a state determination unit that determines whether the health state of the person is in a critical state based on the measurement data acquired by the acquisition unit. Each of the plurality of information processing platforms may include a notification unit that, in response to the state determination unit determining that the health state of the person is in a critical state, notifies the management platform of the determination result made by the state determination unit.

[0017] The above summary of the invention does not list all of the necessary features of the present invention, and subcombinations of these features may also constitute inventions.

[0018] 1A and 1B schematically illustrate an example of an information processing infrastructure 100. 1B schematically illustrate an example of a system 60. 1C schematically illustrate an example of the functional configuration of the information processing infrastructure 100. 1D schematically illustrate an example of the hardware configuration of a computer 1200 that functions as the information processing infrastructure 100 or the management infrastructure 600.

[0019] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0020] FIG. 1 schematically illustrates an example of an information processing infrastructure 100. The information processing infrastructure 100 may be communicatively connected to a radio base station 200. The radio base station 200 may provide a radio communication service to communication terminals within a coverage area 20. The communication terminals may be smartphones, tablet terminals, PCs (Personal Computers), IoT (Internet of Things) terminals, etc. The communication terminals include a measurement terminal 300. The information processing infrastructure 100 may manage the radio base station 200. The information processing infrastructure 100 may be communicatively connected to a plurality of radio base stations 200 and may manage a plurality of radio base stations 200.

[0021] The information processing infrastructure 100 may communicate with communication terminals within the coverage area 20 via the wireless base station 200. The information processing infrastructure 100 may manage the communication terminals by transmitting various instructions to the communication terminals within the coverage area 20 via the wireless base station 200. For example, the information processing infrastructure 100 may acquire information held by the communication terminals within the coverage area 20 from the communication terminals. The information processing infrastructure 100 may manage multiple communication terminals via multiple wireless base stations 200.

[0022] The information processing infrastructure 100 may be a data center located in various locations. The information processing infrastructure 100 may be configured by multiple devices. The information processing infrastructure 100 may be realized on a virtualization platform made up of multiple devices. The information processing infrastructure 100 may also be realized by a single device. In other words, the information processing infrastructure 100 may be an information processing device.

[0023] The multiple radio base stations 200 are arranged in a region 10 corresponding to the information processing infrastructure 100. The region 10 corresponding to the information processing infrastructure 100 may be the region in which the information processing infrastructure 100 is installed. The information processing infrastructure 100 does not have to be installed within the corresponding region 10. The region 10 may be, for example, a region having an area equivalent to that of each prefecture in Japan. The region 10 may be, for example, a region having an area smaller than that of each prefecture in Japan. The region 10 may be, for example, a region having an area larger than that of each prefecture in Japan.

[0024] The communication between the information processing infrastructure 100 and the wireless base station 200 may be any communication means that allows communication between the information processing infrastructure 100 and the wireless base station 200. The communication between the information processing infrastructure 100 and the wireless base station 200 may be wired communication such as communication optical fiber, or may be wireless communication.

[0025] The information processing infrastructure 100 may be equipped with one or more central processing units (CPUs). The information processing infrastructure 100 may be equipped with one or more GPUs. The information processing infrastructure 100 may be equipped with multiple super chips, each of which has a CPU and a GPU connected via an interconnect. The interconnect may have memory consistency and may be capable of achieving high bandwidth and low latency. In this way, the information processing infrastructure 100 may have CPU resources and GPU resources as computational resources.

[0026] In the example shown in Fig. 1 , a space 30 in which a measurement terminal 300 is installed is located within the coverage area 20 of a wireless base station 200. The measurement terminal 300 may measure a person 40. The space 30 in which the measurement terminal 300 is installed may be any space 30 as long as it is a space 30 in which the person 40 can be measured. For example, the space 30 in which the measurement terminal 300 is installed may be located in a residential area, an office area, a medical / nursing care facility, an area where factories and the like are concentrated, etc. In the example shown in Fig. 1 , the space 30 in which the measurement terminal 300 is installed is located in an area in which a residential area, an office area, a medical / nursing care facility, etc., and a area where factories and the like are concentrated.

[0027] If the space 30 in which the measurement terminal 300 is installed is located in a residential area, the measurement terminal 300 may be installed in, for example, each residence. When the measurement terminal 300 is installed in each residence, the measurement terminal 300 may be installed in any space 30 as long as it is a space 30 in which a person 40 enters. The space 30 in which the measurement terminal 300 is installed may be, for example, a bedroom, a bathroom, a toilet, a washroom, a kitchen, a living room, a staircase, a hallway, a garden, etc. In the example shown in FIG. 1 , the spaces 30 in which the measurement terminal 300 is installed are a bedroom, a bathroom, a toilet, and a living room.

[0028] If the space 30 in which the measurement terminal 300 is installed is located in an office area, the measurement terminal 300 may be installed in, for example, each office building. When the measurement terminal 300 is installed in each office building, the measurement terminal 300 may be installed in any space 30 as long as it is a space 30 in which a person 40 enters. The space 30 in which the measurement terminal 300 is installed may be, for example, an entrance hall, each elevator car (the part in which a person 40 rides when going up or down), an escalator, a warehouse, a toilet, a security guard's office, etc. When the measurement terminal 300 is installed in each office building, the measurement terminal 300 may be installed on, for example, each floor of each office building. When the measurement terminal 300 is installed on each floor, the measurement terminal 300 may be installed in any space 30 as long as it is a space 30 in which a person 40 enters. The space 30 in which the measurement terminal 300 is installed may be, for example, a conference room, an office space, a common space, a library, a warehouse, a toilet, a washroom, a hallway, etc.

[0029] When the space 30 in which the measurement terminal 300 is installed is located in a medical or nursing care facility, the measurement terminal 300 may be installed in, for example, each medical or nursing care facility. When the measurement terminal 300 is installed in each medical or nursing care facility, the measurement terminal 300 may be installed in any space 30 as long as it is a space 30 in which a person 40 enters. The space 30 in which the measurement terminal 300 is installed may be, for example, a hospital room, a waiting room, a consultation room, an operating room, a nurse's station, a bathroom, a toilet, a washroom, a kitchen, a common space, a hallway, etc. In the example shown in FIG. 1 , the space 30 in which the measurement terminal 300 is installed is a hospital room. When the measurement terminal 300 is installed in each medical or nursing care facility, the number of measurement terminals 300 installed may be increased in spaces 30 in which the risk of a deterioration in the health of people 40 is high.

[0030] If the space 30 in which the measurement terminal 300 is installed is located in an area where factories and the like are concentrated, the measurement terminal 300 may be installed in each factory, for example. When the measurement terminal 300 is installed in each factory, the measurement terminal 300 may be installed in any space 30 as long as it is a space 30 where people 40 enter. The space 30 in which the measurement terminal 300 is installed may be, for example, an indoor workshop, an outdoor workshop, an indoor warehouse, an office, an outdoor passageway, a bathroom, a toilet, a washroom, a common space, a corridor, etc. When the measurement terminal 300 is installed in each factory, the number of measurement terminals 300 installed may be increased in spaces 30 where there is a high risk of deterioration of the health of people 40. For example, this may be the case when the space 30 is hot and humid, or when the work done by people 40 in the space 30 is heavy (such as transporting heavy objects or working in thick clothing that easily raises body temperature).

[0031] When the measurement terminal 300 measures the human 40 using radio waves, the measurement terminal 300 may measure vital information of the human 40 by measuring the human 40 using radio waves. The vital information of the human 40 may be, for example, heart rate, respiratory rate, etc. By measuring the human 40 using radio waves, the measurement terminal 300 may measure information such as position information, posture information (standing, sitting, lying down, etc.), type of movement (walking, running, sitting, lying down, falling, not moving, etc.), and speed of movement of the human 40 within the space 30. The measurement terminal 300 may measure the health condition of the human 40 from information such as vital information, position information, posture information, type of movement, and speed of movement obtained by measuring the human 40 using radio waves.

[0032] When the measurement terminal 300 measures the human 40 using radio waves, the wavelength of the radio waves used by the measurement terminal 300 is not particularly limited. For example, the wavelength of the radio waves used by the measurement terminal 300 may be ultra-high frequency (UHF), microwaves (SHF), extremely high frequency (SHF), millimeter waves, submillimeter waves, or terahertz waves. For example, the information processing infrastructure 100 may determine whether the health condition of the human 40 is critical based on measurement data 400 obtained by measuring the human 40 using millimeter waves.

[0033] 1 , the entity that transmits the measurement data 400 to the information processing infrastructure 100 via the wireless base station 200 is not particularly limited. For example, the measurement terminal 300 itself may be a so-called IoT terminal having a wireless communication function, and the measurement terminal 300 itself may transmit the measurement data 400. For example, instead of the measurement terminal 300 itself, another device that is communicatively connected to the measurement terminal 300 and has a communication function may acquire the measurement data 400 from the measurement terminal 300 and transmit the measurement data 400. In other words, the processes of measuring the measurement data 400 and transmitting the measurement data 400 to the wireless base station 200 may be shared among multiple devices.

[0034] In the example shown in FIG. 1 , the measurement data 400 may be primary data (sometimes referred to as raw data) obtained by measuring the human 40 using the measurement terminal 300, or secondary data (sometimes referred to as analyzed data) generated by analyzing the raw data. For example, when the measurement terminal 300 measures the human 40 using radio waves, the measurement terminal 300 may analyze information such as the phase and intensity of the radio waves reflected from the human 40, which constitutes raw data, to generate information on the human 40's heart rate per unit time, which may then be transmitted to the wireless base station 200 as analyzed data. As a result, for example, if the raw data volume is large, transmitting smaller analyzed data to the wireless base station 200 can reduce communication volume and lower communication costs. Furthermore, since measurement data transmission can be completed in a short time, this can contribute to prompt detection of abnormalities in the human's health condition.

[0035] In this case, the measurement terminal 300 itself may perform the analysis and generate the analysis data. Alternatively, another device communicably connected to the measurement terminal 300, rather than the measurement terminal 300 itself, may acquire raw data from the measurement terminal 300 and generate the analysis data. In other words, the acquisition of raw data and the generation of analysis data by analyzing the raw data may be shared among multiple devices.

[0036] 1 , the information processing infrastructure 100 acquires measurement data 400 from a measurement terminal 300 via a wireless base station 200. The information processing infrastructure 100 acquires, via the wireless base stations 200, measurement data obtained by measuring the health state of a person 40 located within a coverage area 20 of the wireless base stations 200 arranged in an area 10 corresponding to the information processing infrastructure 100 using radio waves. The information processing infrastructure 100 determines whether the health state of the person 40 is in a critical state based on the acquired measurement data 400. A specific method for determining whether the health state of the person 40 is in a critical state will be described later.

[0037] 1 , multiple radio base stations 200 may constitute a RAN 22. An information processing infrastructure 100 may control the RAN. The information processing infrastructure 100 may receive measurement data 400 measured by a measurement terminal 300 located within a coverage area 20 of the multiple radio base stations 200 constituting the RAN 22 from the measurement terminal 300 via the radio base station 200.

[0038] In the example shown in FIG. 1 , the information processing infrastructure 100 may further acquire risk information indicating the risk of the health of humans 40 within the region 10 becoming dangerous. The risk information may be, for example, weather-related advisories and warnings provided by central government agencies, local government agencies, private media, etc., targeting an area including the region 10. The risk information may be, for example, high temperature advisories, low temperature advisories, heatstroke alerts, and dry weather advisories. The risk information may also be, for example, information provided by a monitoring device installed in the region 10. The information provided by the monitoring device may be, for example, information indicating that the risk level of a heat index (WBGT, Wet Bulb Globe Temperature), which indicates the risk of heatstroke, meets a predetermined standard. The predetermined criteria may be, for example, danger (WBGT above 31°C), high alert (WBGT between 28-31°C), caution (WBGT between 25-28°C), and caution (WBGT below 25°C).

[0039] The information processing infrastructure 100 may transmit an instruction to the measurement terminal 300 to increase the frequency of measurement in response to acquiring risk information. The information processing infrastructure 100 may transmit an instruction to the measurement terminal 300 to increase the frequency of transmission of measurement data 400 to the information processing infrastructure 100 in response to acquiring risk information. These instructions from the information processing infrastructure 100 may be examples of an instruction to increase. This makes it possible to conserve communication resources and computational resources when the risk of the human 40's health condition becoming dangerous low, while increasing the frequency of acquiring measurement data when the risk is high, thereby making it possible to determine the human's health condition more accurately and in closer to real time.

[0040] The measurement terminal 300 may use radio waves to measure the health status of a person 40 located within the space 30 in which the measurement terminal 300 is installed. The information processing infrastructure 100 may adjust the frequency of measurement by the measurement terminal 300 and the frequency of transmission of the measurement data 400 to the information processing infrastructure 100 based on the attributes of the multiple people 40 located within the space 30 in which the measurement terminal 300 is installed.

[0041] The attributes of the person 40 may be, for example, age, gender, chronic illnesses, records of previous illnesses and surgeries (medical history), results of health checkups, etc. For example, the information processing infrastructure 100 may increase the frequency of measurement by the measurement terminal 300 and the frequency of transmission of the measurement data 400 to the information processing infrastructure 100 when the person 40 is older. For example, when the age of the person 40 is older than a predetermined threshold, the information processing infrastructure 100 may set the frequency of measurement by the measurement terminal 300 and the frequency of transmission of the measurement data 400 to the information processing infrastructure 100 to a predetermined threshold frequency. For example, when the person 40 is suffering from a specific illness, the information processing infrastructure 100 may set the frequency of measurement by the measurement terminal 300 and the frequency of transmission of the measurement data 400 to the information processing infrastructure 100 to a predetermined threshold frequency. This allows for the saving of communication and computational resources when the attributes of human 40 indicate a low risk of their health becoming dangerous, while increasing the frequency of measurement data acquisition when the risk is high, making it possible to determine the human's health condition more accurately and in closer to real time.

[0042] The attributes of the person 40 may be acquired based on measurement data 400 obtained by measuring the person 40 using the measurement terminal 300. For example, the information processing infrastructure 100 may analyze vital information (heart rate, respiratory rate, etc.) of the person 40 from the measurement data 400, and estimate the age, chronic illnesses, etc. of the person 40 based on the vital information. The attributes of the person 40 may be acquired separately from the measurement data 400 obtained by measuring the person 40 using the measurement terminal 300. For example, the attribute information of the person 40 present in the space 30 may be acquired by identifying the person 40 present in the space 30 from an entry record into the space 30, etc., and comparing the identified person 40 with the attribute information of the person 40 recorded in storage.

[0043] The information processing infrastructure 100 may determine whether or not a person 40 is present in the space 30 in which the measurement terminal 300 is installed. When the information processing infrastructure 100 determines that no person 40 is present in the space 30 in which the measurement terminal 300 is installed, the information processing infrastructure 100 may transition the measurement terminal 300 to a power-saving state. The power-saving state may be, for example, turning the power of the measurement terminal 300 to a sleep state or turning the power of the measurement terminal 300 to an off state. The method for determining whether or not a person 40 is present in the space 30 in which the measurement terminal 300 is installed is not particularly limited. For example, the determination may be made based on the measurement data 400, or may be made based on information other than the measurement data 400, such as an entry record into the space 30.

[0044] The information processing infrastructure 100 may store learning data including measurement data 400 when the health state of the human 40 is in a normal, dangerous state. The information processing infrastructure 100 may further store learning data including measurement data 400 when the health state of the human 40 is in a normal, non-critical state. The information processing infrastructure 100 may use the stored learning data as training data to generate a determination model by machine learning that determines whether the health state of the human 40 is in a dangerous state from the measurement data 400 obtained by measuring the human 40. The information processing infrastructure 100 may use the determination model to determine whether the health state of the human 40 is in a dangerous state from the acquired measurement data 400.

[0045] The information processing infrastructure 100 may further acquire attribute information representing the attributes of the person 40. In response to determining that the health state of the person 40 is at risk, the information processing infrastructure 100 may notify a notification destination according to the attributes of the person 40 of the determination result. For example, if the person 40 is elderly, the notification destination according to the attributes of the person 40 may be the family of the person 40, the person's family doctor, etc. In case the person 40 is suffering from a specific disease, the notification destination according to the attributes of the person 40 may be a specialist in that disease, a medical institution specializing in that disease, etc. For example, if the person 40 is suffering from diabetes, the notification destination may be a diabetes specialist, a dialysis center, etc. In this way, when the health state of the person is determined to be at risk, it becomes possible to provide more appropriate medical treatment that takes into account the risks faced by the person.

[0046] As described above, the radio waves used by the measurement terminal 300 are not particularly limited. As a specific example, the radio waves used by the measurement terminal 300 may be millimeter waves. The information processing infrastructure 100 may determine whether the health condition of the human 40 is critical based on measurement data 400 obtained by measuring the human 40 using millimeter waves. Millimeter waves are known to be able to penetrate fibers such as clothing and are less susceptible to water vapor and dust in the air. Furthermore, they can measure the shape of the object being measured in millimeter units. Therefore, by using millimeter waves, the vital signs, position, and shape of the human 40 can be measured more accurately, even when the human 40 is fully clothed or in a humid environment such as a bathroom.

[0047] The information processing infrastructure 100 may further acquire risk information indicating the risk of a person 40 in the area 10 becoming dangerous. The information processing infrastructure 100 may execute a determination process to determine whether the state of a person 40 located in the area 10 is dangerous, at a frequency according to the risk information. For example, if the risk information is a forecast that the temperature will be high (or low), the information processing infrastructure 100 may increase the determination frequency when the predicted temperature is higher (or lower). For example, if the temperature in the area 10 predicted by the risk information is higher (or lower) than a predetermined threshold temperature, the information processing infrastructure 100 may increase the determination frequency to the predetermined threshold number of times. This makes it possible to conserve communication resources and computational resources when the risk of the health state of the person 40 becoming dangerous is low, while increasing the frequency of health state determination when the risk is high, thereby making it possible to determine the health state of the person more accurately and in closer to real time.

[0048] For example, if the risk information is a heat index, the information processing infrastructure 100 may increase the determination frequency depending on the risk level of the heat index. For example, if the heat index for the region 10 obtained from the risk information falls into a predetermined category, the information processing infrastructure 100 may increase the determination frequency to a predetermined threshold number of times. For example, when the heat index category is "danger," the determination frequency may be 24 times per hour; when the heat index category is "high alert," the determination frequency may be 12 times per hour; when the heat index category is "alert," the determination frequency may be 6 times per hour; when the heat index category is "caution" (WBGT less than 25°C), the determination frequency may be 4 times per hour; and when the heat index category does not fall into the above categories, the determination frequency may be 1 time per hour. The relationship between the heat index and the determination frequency described above is merely an example, and determination may be performed more or less frequently for each heat index category.

[0049] The information processing infrastructure 100 may store the installation locations of the measurement terminals 300. Based on the installation locations of the measurement terminals 300 and the assessment results of the people 40, the information processing infrastructure 100 can determine in which area 10 and at which location there are people 40 whose health is at risk, and how many of them are there. For example, the information processing infrastructure 100 may generate alert generation information indicating the location and severity of symptoms of people 40 whose health is at risk, and notify a predetermined notification destination. The predetermined notification destination may be, for example, an emergency center, a medical institution, or the like in the area 10. By receiving the alert generation information, the emergency center in the area 10 can more quickly and smoothly arrange for an ambulance and a medical institution within the area 10.

[0050] The information processing infrastructure 100 may acquire medical resource information representing information on the activity status of ambulances and medical institutions within the region 10. The information processing infrastructure 100 may generate medical resource planning information that plans the arrangement of ambulances and medical institutions based on the generated alert occurrence information and the acquired medical resource information. The information processing infrastructure 100 may, for example, notify a predetermined notification destination of the medical resource planning information. The predetermined notification destination may, for example, be an emergency center in the region 10. By receiving the medical resource planning information, the emergency center in the region 10 can more quickly and smoothly arrange for ambulances and medical institutions within the region 10.

[0051] 1 , the measurement terminal 300 may have an alarm function. When the information processing infrastructure 100 determines that the health condition of a person 40 located in a space 30 is in a dangerous state based on the measurement data 400 measured by the measurement terminal 300 installed in the space 30, the information processing infrastructure 100 may issue an alarm using the alarm function of another measurement terminal 300 installed in another space 30 in the same building. For example, when the health condition of a person 40 located in a bathroom is determined to be in a dangerous state, the information processing infrastructure 100 may issue an alarm using the alarm function of the measurement terminal 300 installed in the living room, the measurement terminal 300 installed in the bedroom, etc.

[0052] FIG. 2 schematically illustrates an example of a system 60. The system 60 may include multiple information processing infrastructures 100. In the example illustrated in FIG. 2, the configuration of each of the multiple information processing infrastructures 100 is the same as in the example illustrated in FIG. 1. Note that while the measurement terminals 300 and measurement data 400 are omitted in FIG. 2, the measurement terminals 300 are located within the coverage areas 20 of the respective wireless base stations 200, as in the example illustrated in FIG. 1, and each of the multiple information processing infrastructures 100 transmits measurement data 400 to the information processing infrastructure 100 via the wireless base stations 200, as in the example illustrated in FIG. 2. In the example illustrated in FIG. 2, the multiple information processing infrastructures 100 are arranged so that the corresponding areas 10 do not overlap each other. The multiple information processing infrastructures 100 may also be arranged so that the corresponding areas 10 overlap each other.

[0053] The system 60 includes a management infrastructure 600 that manages multiple information processing infrastructures 100. The management infrastructure 600 may be a data center that manages multiple information processing infrastructures 100. The management infrastructure 600 may be configured with multiple devices. The management infrastructure 600 may be realized on a virtualization infrastructure made up of multiple devices. The management infrastructure 600 may also be realized by a single device. In other words, the management infrastructure 600 may be a management device.

[0054] The management infrastructure 600 may be referred to as a Core Brain, and the information processing infrastructure 100 may be referred to as a Regional Brain. While FIG. 2 illustrates an example in which a single-layer information processing infrastructure 100 is arranged below the management infrastructure 600, this is not limiting. The information processing infrastructure 100 may have multiple layers. For example, if a two-layer information processing infrastructure 100 is arranged below the management infrastructure 600, the management infrastructure 600 may be referred to as a Core Brain, the information processing infrastructure 100 below that may be referred to as a Regional Brain, and the information processing infrastructure 100 below that may be referred to as a Sub-Regional Brain. In this case, disaster prediction may be performed in units of Regional Brains.

[0055] Each of the multiple information processing infrastructures 100 may acquire, via the multiple wireless base stations 200, measurement data 400 measuring the health state of a person 40 located within the coverage area 20 of the multiple wireless base stations 200 arranged in the region 10 corresponding to the information processing infrastructure 100. The information processing infrastructure 100 may determine whether the health state of the person 40 is in a dangerous state based on the acquired measurement data 400. In response to determining that the health state of the person 40 is in a dangerous state, the information processing infrastructure 100 may notify the management infrastructure 600 of the determination result by the information processing infrastructure 100.

[0056] The management infrastructure 600 may acquire, from the multiple information processing infrastructures 100, alert occurrence information for each region 10 corresponding to each information processing infrastructure 100. The management infrastructure 600 may notify a predetermined notification destination of the alert occurrence information for each region 10. The predetermined notification destination may be, for example, an emergency center, a medical institution, etc. in each region 10. By receiving the alert occurrence information, for example, the emergency center in each region 10 can coordinate with nearby regions 10 to arrange for an ambulance and a medical institution. The management infrastructure 600 may acquire, from the multiple information processing infrastructures 100, medical resource information for each region 10 corresponding to each information processing infrastructure 100. The management infrastructure 600 may generate wide-area medical resource planning information that aggregates the multiple regions 10 based on the acquired alert occurrence information for each region 10 and the acquired medical resource information for each region. Arranging medical resources over a wide area that combines multiple regions enables more efficient and effective medical resource arrangements than if multiple regions 10 arranged medical resources individually. The information processing infrastructure 100 may, for example, notify predetermined destinations of the medical resource planning information. The predetermined destinations may, for example, be each emergency center in each region 10. By receiving the medical resource planning information, the emergency center in each region 10 can more quickly and smoothly arrange for ambulances and medical institutions within the region 10.

[0057] 3 shows an example of the functional configuration of the information processing infrastructure 100. The information processing infrastructure 100 includes an acquisition unit 110, a state determination unit 120, a storage unit 130, a model generation unit 140, a notification unit 150, a measurement adjustment unit 160, a RAN control unit 170, and a presence determination unit 180. Note that it is not essential for the information processing infrastructure 100 to include all of these units. In addition to these "units," the information processing infrastructure 100 may further include any "unit" for realizing the functions of the information processing infrastructure 100.

[0058] The acquisition unit 110 acquires various types of data. For example, the acquisition unit 110 acquires measurement data 400 measured by the measurement terminal 300. The acquisition unit 110 may store the acquired data in the storage unit 130. For example, the acquisition unit 110 acquires data related to the subordinate radio base station 200. The acquisition unit 110 may acquire location data of the radio base station 200. The location data of the radio base station 200 indicates, for example, the latitude and longitude of the radio base station 200. The acquisition unit 110 may acquire surrounding environment data indicating the surrounding environment of the radio base station 200. The surrounding environment data may be, for example, three-dimensional map data of the area around the radio base station 200.

[0059] The acquisition unit 110 acquires, for example, data related to the space 30 in which the measurement terminal 300 is installed. The acquisition unit 110 may acquire position data of the space 30. The position data of the space 30 indicates, for example, the latitude and longitude of the space 30. The acquisition unit 110 may acquire surrounding environment data indicating the surrounding environment of the space 30. The surrounding environment data may be, for example, three-dimensional map data of the periphery of the space 30.

[0060] The acquiring unit 110 may acquire performance data of the wireless communication service provided by the wireless base station 200. The performance data may include data of the measurement terminals 300 that are present in the range of the wireless base station 200.

[0061] The acquisition unit 110 acquires, via the plurality of wireless base stations 200, measurement data 400 obtained by measuring the health status of people 40 located within the coverage areas 20 of the plurality of wireless base stations 200 arranged in the area 10 corresponding to the information processing infrastructure 100 using radio waves. The state determination unit 120 determines whether the health status of people 40 is in a dangerous state based on the measurement data 400 acquired by the acquisition unit 110. The state determination unit 120 may store the determination result in the storage unit 130.

[0062] The RAN control unit 170 controls the RAN 22 configured by a plurality of radio base stations 200. The acquisition unit 110 may receive measurement data 400 measured by a measurement terminal 300 located within the coverage area 20 of the plurality of radio base stations 200 configuring the RAN 22 from the measurement terminal 300 via the radio base station 200. By providing the information processing infrastructure 100 with a RAN control function, it is possible to improve affinity with functions other than RAN control, and particularly to more quickly perform the process of acquiring the measurement data 400 and the process of notifying the determination result, which are often performed using the RAN.

[0063] The acquisition unit 110 may acquire risk information indicating the risk that the health state of humans 40 in the area 10 will become dangerous. The measurement adjustment unit 160 may transmit an instruction to the measurement terminal 300 to increase the frequency of measurement in response to the acquisition of the risk information by the acquisition unit 110. The measurement adjustment unit 160 may transmit an instruction to the measurement terminal 300 to increase the frequency of transmission of measurement data 400 to the information processing infrastructure 100 in response to the acquisition of the risk information by the acquisition unit 110. These instructions from the measurement adjustment unit 160 may be examples of an instruction to increase. This makes it possible to conserve communication resources and computational resources when the risk of the health state of humans 40 becoming dangerous is low, while increasing the frequency of acquisition of measurement data when the risk is high, thereby making it possible to determine the health state of humans more accurately and in closer to real time.

[0064] In response to the acquisition of risk information by the acquisition unit 110, the measurement adjustment unit 160 may transmit an instruction to increase the number of measurement terminals 300 that transmit measurement data 400 to the information processing infrastructure 100 within the coverage area 20. These instructions from the measurement adjustment unit 160 may be an example of an instruction to increase.

[0065] The measurement terminal 300 may use radio waves to measure the health status of a person 40 located within the space 30 in which the measurement terminal 300 is installed. The measurement adjustment unit 160 may adjust the frequency of measurement by the measurement terminal 300 and the frequency of transmission of the measurement data 400 to the information processing infrastructure 100 based on the attributes of the multiple people 40 located within the space 30 in which the measurement terminal 300 is installed.

[0066] The presence determination unit 180 may determine whether or not a human 40 is present in the space 30 in which the measurement terminal 300 is installed. The terminal control unit 190 may transition the measurement terminal 300 to a power-saving state when the presence determination unit 180 determines that a human 40 is not present in the space 30 in which the measurement terminal 300 is installed. The power-saving state may be, for example, turning the power of the measurement terminal 300 to a sleep state or turning the power of the measurement terminal 300 to an off state.

[0067] The storage unit 130 stores various data. For example, the storage unit 130 may store learning data including measurement data 400 when the health state of the human 40 is in a normal, dangerous state. The storage unit 130 may store learning data including measurement data 400 when the health state of the human 40 is in a normal, non-critical state. The model generation unit 140 may use the multiple learning data stored in the storage unit 130 as training data to generate a determination model by machine learning that determines whether the health state of the human 40 is in a dangerous state from the measurement data 400 obtained by measuring the human 40. The state determination unit 120 may use the determination model to determine whether the health state of the human 40 is in a dangerous state from the measurement data 400 acquired by the acquisition unit 110. The model generation unit 140 may store the generated determination model in the storage unit 130.

[0068] The model generation unit 140 may generate a judgment model that collectively judges multiple types of health condition abnormalities. The model generation unit 140 may generate a judgment model that specializes in a specific health condition abnormality and judges health condition abnormalities. The model generation unit 140 may determine whether the health condition of the human 40 is in a dangerous state by machine learning other than supervised learning. By using a model generated by machine learning, it is possible to generate a highly accurate health condition judgment model based on a large amount of data.

[0069] The acquisition unit 110 may further acquire attribute information representing attributes of the person 40. The notification unit 150 notifies the determination result. In response to the state determination unit 120 determining that the health state of the person 40 is in a critical state, the notification unit 150 may notify a notification destination according to the attributes of the person 40 of the determination result by the state determination unit 120. The notification unit 150 may notify a wireless communication terminal carried by a family member of the person 40 that is within the range of multiple wireless base stations 200 of the determination result of the health state of the person 40. In response to the state determination unit 120 determining that the health state of the person 40 is in a critical state, the notification unit 150 may notify a wireless communication terminal carried by a family member of the person 40 that is within the range of multiple wireless base stations 200 of the determination result of the health state of the person 40. This allows the notification to be transmitted via the shortest communication path connecting the information processing infrastructure 100 and the wireless communication terminal, so that when it is determined that the health state of the person 40 has become critical, the family member of the person 40 can be quickly warned of this. In particular, if the person 40 has a chronic illness or is prone to falling into a dangerous health condition and the symptoms are likely to become serious, it is important that family members receive the notification early and can quickly check the health condition of the person 40.

[0070] The information processing infrastructure 100 may generate alert generation information indicating the location and severity of symptoms of a person 40 whose health is in danger. The notification unit 150 may notify a predetermined notification destination of the alert generation information. The predetermined notification destination may be, for example, an emergency center, a medical institution, or the like in the region 10. By receiving the alert generation information, the emergency center in the region 10 can more quickly and smoothly arrange for an ambulance and a medical institution within the region 10.

[0071] The acquisition unit 110 may further acquire medical resource information representing information on the activity status of ambulances and medical institutions within the region 10. The information processing infrastructure 100 may generate medical resource planning information that plans the arrangement of ambulances and medical institutions based on the generated alert occurrence information and the acquired medical resource information. The notification unit 150 may, for example, notify a predetermined notification destination of the medical resource planning information. The predetermined notification destination may, for example, be an emergency center in the region 10. By receiving the medical resource planning information from the information processing infrastructure, the emergency center in the region 10 can more quickly and smoothly arrange for ambulances and medical institutions within the region 10.

[0072] The state determination unit 120 may execute a determination process to determine whether the state of a person 40 located within the area 10 is in a dangerous state at a frequency according to the risk information.

[0073] The state determination unit 120 may also determine the intensity of the dangerous state, which indicates how dangerous the health state of the person 40 is. For example, it may be predicted that the greater the degree of danger in the vital sign information of the person 40, the greater the intensity of the dangerous state of the health state of the person 40. For example, the intensity of the dangerous state may be determined by detecting a pattern according to the degree of dangerous state of the health state from a combination obtained from a plurality of different types of measurement data 400. Since the degree of danger of the health state is known, it is possible to select a corresponding response action.

[0074] 4 schematically illustrates an example of the hardware configuration of a computer 1200 that functions as the information processing infrastructure 100 or the management infrastructure 600. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of an apparatus according to the present embodiment, or can cause the computer 1200 to execute operations associated with the apparatus according to the present embodiment or one or more "parts," and / or can cause the computer 1200 to execute a process according to the present embodiment or steps of the process. Such a program can be executed by the CPU 1212 to cause the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0075] The computer 1200 according to this embodiment includes a CPU 1212, a GPU 1213, a RAM 1214, and a graphics controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a storage device 1224, a DVD drive, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive may be a DVD-ROM drive, a DVD-RAM drive, or the like. The storage device 1224 may be a hard disk drive, a solid-state drive, or the like. The computer 1200 also includes a ROM 1230 and a legacy input / output unit such as a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0076] The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into the graphics controller 1216 itself, and causes the image data to be displayed on the display device 1218.

[0077] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0078] The ROM 1230 stores therein a boot program or the like that is executed by the computer 1200 upon activation, and / or programs that depend on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0079] The programs are provided by a computer-readable storage medium such as a DVD-ROM or an IC card. The programs are read from the computer-readable storage medium, installed in the storage device 1224, RAM 1214, or ROM 1230, which are also examples of computer-readable storage media, and executed by the CPU 1212. Information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or a method may be configured by implementing operations or processing of information in accordance with the use of the computer 1200.

[0080] For example, when communication is performed between computer 1200 and an external device, CPU 1212 may execute a communication program loaded into RAM 1214 and instruct communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of CPU 1212, communication interface 1222 reads transmission data stored in a transmission buffer area provided in RAM 1214, storage device 1224, a DVD-ROM, or a recording medium such as an IC card, and transmits the read transmission data to a network, or writes received data received from the network to a reception buffer area or the like provided on the recording medium.

[0081] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), an IC card, etc. to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0082] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and may undergo information processing. The CPU 1212 may perform various types of processing on data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries, each having an attribute value of a first attribute associated with an attribute value of a second attribute, are stored on the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0083] The above-described programs or software modules may be stored in a computer-readable storage medium on or near the computer 1200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0084] The blocks in the flowcharts and block diagrams in the present embodiments may represent stages of a process in which an operation is performed or "parts" of a device responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and / or a processor provided with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuitry may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits, such as field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements.

[0085] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture, including instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable storage media may include electronic, magnetic, optical, electromagnetic, and semiconductor storage media. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disc read-only memories (CD-ROMs), digital versatile discs (DVDs), Blu-ray discs, memory sticks, integrated circuit cards, and the like.

[0086] The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0087] The computer-readable instructions may be provided to a general-purpose computer, a special-purpose computer, or another programmable data processing device processor or programmable circuit, either locally or via a local area network (LAN), a wide area network (WAN) such as the Internet, so that the processor or programmable circuit of the programmable data processing device, such as a computer, executes the computer-readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Here, the computer may be a personal computer (PC), a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, a special-purpose computer, or the like, or may be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system, and is a broad definition of computer. In a distributed computing system, multiple computers collectively execute a program by each executing a portion of the program and passing data between the computers as needed during program execution.

[0088] Examples of processors include computer processors, central processing units (CPUs), processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc. A computer may have one processor or multiple processors. In a multiprocessor system with multiple processors, each processor executes a portion of a program and passes data between processors as needed during program execution, allowing the multiple processors to collectively execute the program. For example, in multitasking, each of the multiple processors may execute a portion of each task in small chunks by switching tasks at each time slice. In this case, which portion of a program each processor executes changes dynamically. Which portion of a program each of the multiple processors executes may also be statically determined by multiprocessor-aware programming.

[0089] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0090] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order.

[0091] 10 region, 20 coverage area, 22 RAN, 30 space, 40 human, 60 system, 100 information processing infrastructure, 110 acquisition unit, 120 state determination unit, 130 memory unit, 140 model generation unit, 150 notification unit, 160 measurement adjustment unit, 170 RAN control unit, 180 presence determination unit, 190 terminal control unit, 200 radio base station, 300 measurement terminal, 400 measurement data, 600 management infrastructure, 1200 computer, 1210 host controller, 1212 CPU, 1213 GPU, 1214 RAM, 1216 graphics controller, 1218 display device, 1220 input / output controller, 1222 communication interface, 1224 storage device, 1230 ROM, 1240 input / output chip

Claims

1. An information processing infrastructure comprising: an acquisition unit that acquires, via a plurality of wireless base stations located in an area corresponding to the information processing infrastructure, measurement data that measures the health status of a person located within the coverage area of ​​the plurality of wireless base stations using radio waves; and a condition determination unit that determines whether the health status of the person is in a dangerous state based on the measurement data acquired by the acquisition unit.

2. The information processing infrastructure according to claim 1, further comprising a RAN control unit that controls a RAN (Radio Access Network) constituted by the plurality of radio base stations, wherein the acquisition unit receives the measurement data measured by a measurement terminal located within the coverage area of ​​the plurality of radio base stations that constitute the RAN from the measurement terminal via the radio base station.

3. The information processing infrastructure described in claim 2, wherein the acquisition unit further acquires risk information representing the risk of the health condition of the people within the area becoming dangerous, and the information processing infrastructure further comprises a measurement adjustment unit that, in response to the acquisition unit acquiring the risk information, sends to the measurement terminal an increase instruction to increase the frequency of measurements and the frequency of transmission of the measurement data to the information processing infrastructure.

4. The information processing infrastructure described in claim 2, wherein the acquisition unit further acquires risk information representing the risk of the health condition of the person within the area becoming dangerous, and the information processing infrastructure further comprises a measurement adjustment unit that controls to increase the number of measurement terminals that transmit the measurement data to the information processing infrastructure within the coverage area in response to the acquisition unit acquiring the risk information.

5. The information processing infrastructure described in claim 2, wherein the measurement terminal measures the health status of a person located within the space in which the measurement terminal is installed using radio waves, and the information processing infrastructure further comprises a measurement adjustment unit that adjusts the frequency of measurements by the measurement terminal and the frequency of transmission of the measurement data to the information processing infrastructure based on the attributes of multiple people located within the space in which the measurement terminal is installed.

6. The information processing infrastructure described in claim 2, wherein the measurement terminal measures the health status of a human located within the space in which the measurement terminal is installed using radio waves, and the information processing infrastructure further comprises: a presence determination unit that determines whether a human is present within the space in which the measurement terminal is installed; and a terminal control unit that transitions the measurement terminal to a power-saving state when it is determined that no human is present within the space in which the measurement terminal is installed.

7. An information processing infrastructure as described in any one of claims 1 to 6, further comprising: a memory unit that stores learning data including measurement data when a human's health condition is in a dangerous state; and a model generation unit that uses the plurality of learning data stored in the memory unit as teacher data to generate a judgment model by machine learning that judges whether the human's health condition is in a dangerous state from the measurement data measured on the human, wherein the condition judgment unit uses the judgment model to judge whether the human's health condition is in a dangerous state from the measurement data acquired by the acquisition unit.

8. An information processing infrastructure as claimed in any one of claims 1 to 6, wherein the acquisition unit further acquires attribute information representing the attributes of the person, and further comprises a notification unit that, in response to the state determination unit determining that the health condition of the person is in a dangerous state, notifies a notification destination according to the attributes of the person of the determination result made by the state determination unit.

9. An information processing infrastructure as described in any one of claims 1 to 6, wherein the radio waves are millimeter waves, and the condition determination unit determines whether the human's health condition is dangerous based on the measurement data obtained by measuring the human using millimeter waves.

10. An information processing infrastructure as described in claim 1 or 2, wherein the acquisition unit further acquires risk information indicating the risk of the person being in a dangerous state within the area, and the state determination unit executes a determination process to determine whether the state of the person located within the area is in a dangerous state at a frequency corresponding to the risk information.

11. A program that, when executed by a computer, causes the computer to function as the information processing infrastructure described in any one of claims 1 to 6.

12. A system comprising: a plurality of information processing platforms; and a management platform that manages the plurality of information processing platforms, each of the plurality of information processing platforms having: an acquisition unit that acquires, via the plurality of wireless base stations, measurement data that measures the health status of a person located within the coverage area of ​​the plurality of wireless base stations that are located in an area corresponding to the information processing platform; a status determination unit that determines whether the health status of the person is in a dangerous state based on the measurement data acquired by the acquisition unit; and a notification unit that notifies the management platform of the determination result made by the status determination unit in response to the status determination unit determining that the health status of the person is in a dangerous state.

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