JP2014035712A - Method and device for measuring business situation - Google Patents

Abstract

PROBLEM TO BE SOLVED: To acquire data indicating relationship not only with a person but also entirety of working environment such as facility, spot, and the like, as a target; convert the data into, and represent it as, information indicating a work efficiency (state); comprehend work efficiency quantitatively; and put an improving measure to practice.SOLUTION: An information processing system includes: a trap device for transmitting a signal; a node device for receiving the signal from the trap device existing within a given distance; a computer for processing information obtained on the basis of an infrared reception situation of the node device; and a display device for displaying the information processed by the computer. Further, the trap device is disposed to plural stationary targets whose positions are stationary; the node device is disposed to a mobile target whose position is mobile; and the computer displays, on the display device, a stay information on the mobile target staying with the plural stationary targets, on the basis of information of a signal transmitted from any of the plural stationary target and received by the node device disposed to the node device.

Description

The present invention relates to a business situation measurement method and measurement device, and more particularly to a technique for measuring business information and performing and expressing data processing for quantifying business efficiency and the like.

  In general, work efficiency is measured by the amount of final results per unit time. For example, the final result can be measured by the number of pages in an electronic document or the number of parts produced.

  On the other hand, there are cases where it is inappropriate (insufficient) to measure business efficiency based on the final result alone. This is the case when there are multiple processes until the final result that can be measured is present, or when the work of that process is shared by many people. In such a case, it is necessary to devise measures such as measuring by dividing by process, period, person or business group.

  Furthermore, it may be difficult to measure directly when the assigned work is qualitative. For example, it corresponds to “inquiry” that is different from the main purpose of the business, “support for business execution of another person in charge”, and the like. Such work that contributes to other work cannot be measured by the result of the work.

  In actual work, the percentage of such support work is large, and how to solve this is the key to improving work efficiency. For example, when considering the work of using a device to produce results for inspection, the time spent for a series of work, the time for responding to inquiries, the time being investigated to know how to use, etc. If it can be measured quantitatively, the actual situation of the required man-hour allocation in each business can be seen. In this way, by clarifying the expected man-hour allocation and the gap between the actual conditions for each business, the business efficiency can be quantified, and further improvement points and methods can be seen.

  Therefore, in order to improve business efficiency by using limited resources, it is necessary to grasp the entire business. As methods for grasping the business status, there are Patent Literature 1, Patent Literature 2, and Non-Patent Literature 1.

  Patent Document 1 discloses a technique for quantifying the relationship between persons constituting an organization. The technology quantifies the correlation between organizational productivity and the amount of face-to-face communication between people.

  Patent Document 2 discloses a technique for expressing the current state of cooperation between persons in an organization and future expectations. This technology uses interaction data and questionnaire response data between persons wearing sensor terminals.

Non-Patent Document 1 discloses a technique for analyzing the position and state of a person / object based on a camera image, and analyzing attribute information obtained from a sensor or the like and a combination flow line.

JP 2008-210363 A JP 2010-198261 A

Noriaki Harada et al., Flow line analysis technology to “visualize” human behavior and examples, NEC Technical Bulletin Vol.64 No.3 / 2011

  In an operation such as an inspection room where a plurality of people and facilities are involved and perform a single function, for example, inspection, manufacturing, cooking, etc., the amount of communication between people does not directly relate to the production volume or operational efficiency. For example, in the case of highly specialized single-person work such as inspection work using a microscope, a large amount of communication between persons means a low engagement rate in the main charge work. For work that is more important to face with facilities and places than people, it means face-to-face with equipments and places or staying time there.

  Furthermore, even if the flow line information of a person or an object is visualized by matching the analysis result with the camera image and the detection record of the object obtained by the sensor, it is impossible to indicate when and what kind of work is performed.

The problem to be solved by the present invention is that not only people but also the entire work environment, such as equipment and location, is acquired and converted into information indicating business efficiency (state). It is to be able to quantitatively grasp business efficiency and implement improvements.

  A trap device that periodically emits infrared light is installed in the business action range, and a business worker wears a node device that receives and records infrared light from the trap device. The node equipment periodically performs infrared transmission / reception between the node equipments. Furthermore, the node device records the reception of infrared rays with trap devices installed at various places and other node devices in the process in which the business worker acts as the business is performed.

  The recorded data is transferred to the PC via a cradle having charging and communication functions. The collected data is aggregated for each node device and becomes raw data. This is time series data of infrared reception logs with time-ordered trap devices and node devices. Using this raw data, data processing is performed to quantify the business situation of the business workers. What is generated from the raw data is information about when and what kind of business has been performed.

  There are two types of means for expressing the business efficiency (situation): one that focuses on a business worker and one that focuses on the place where the business is performed. The work efficiency expression method focusing on the business workers express when and what kind of work is performed in time series. In the data processing focusing on the place where the work is performed, an activity place is defined for each work, and the time series change of the number of workers at the place is shown.

As described above, collection of data for grasping business efficiency (state), conversion to information indicating business efficiency, and display thereof can be automatically performed for the entire business.

The business situation that cannot be grasped from the final results can be grasped objectively and quantitatively without relying on the person's declaration. By clarifying the gap between the expected man-hour allocation and the actual situation for each business, the business efficiency can be quantified, and further improvement points and methods can be seen. You will be able to understand the differences in operational efficiency between departments.

Schematic of apparatus configuration for carrying out the present invention Example of data structure of infrared reception log Example of defining a business by location (group) Example of visualizing the business situation using the business definition and interpretation method shown in Figure 3 An example of applying the work definition / interpretation methods shown in Figs. 3 and 4 to work with different working styles Example of quantifying the hours of work done outside the main work area An example showing a business location where a person wearing any node device stayed An example of visualizing the regular work and non-steady work Example of data that visualizes the amount of movement to a remote room Example of data collected by attaching node devices to objects A graph showing the number of times a trap device has detected a node device in time series A figure showing the total number of node devices detected for each business area and the number of detections for each node device that is a breakdown of the total number of detections A diagram representing the number of detections for each node device in the total number of detections of node devices for each business area as a schematic diagram Example of displaying the information in Fig. 13 without using a schematic diagram of the work area Example of associating business status data with operation logs acquired from devices

  The best mode for carrying out the present invention will be described below with reference to the accompanying drawings.

  FIG. 1 is a schematic view showing a device configuration for carrying out the present invention.

In FIG. 1, a trap device 101 periodically transmits its identification information via infrared rays. The node device 102 includes a function for recording the identification information of the trap device 101 that is an infrared transmission source, the infrared transmission / reception time, and a battery. The cradle 103 has an information acquisition function from the node device 102, a charging function for the node device 102, a communication function with the connected general-purpose computer 104, and a function for synchronizing the node device 102 and the general-purpose computer 104.
When the node device 102 is placed on the cradle 103, the measurement information stored in the node device 102 is transferred to the general-purpose computer 104 via the cradle 103. While the node device 102 is placed on the cradle 103, the node device 102 is charged and synchronized with the general-purpose computer 104. The node device 102 can also transmit infrared rays, and has a function of recording transmission / reception times between node devices.

  The raw data 105 is information accumulated by the node device 102. The data is transferred onto the general-purpose computer 104 via the cradle 103.

The core server 106 is a general-purpose computer having a function of collecting and processing “information indicating business efficiency”. The core server 106 processes the raw data 105 acquired from the general-purpose computer 104 into a graph or the like that is easy for the user to understand, and outputs it to the display terminal 107.

  The node device 102 or the trap device 101 is attached to the item related to the business to be visualized. The guideline for mounting is shown below. The node device 102 is attached to a device whose location changes during business execution, such as a person or a return box. A trap device 101 is attached to a place that does not change, for example, a desktop PC, an inspection device, or a workbench.

  Next, in order to grasp the business situation more accurately, a threshold value for distinguishing between stay and passage is defined. For example, in the case of inspection work, the threshold is defined as 20 seconds. Using this value as a boundary, in front of a certain operating terminal, “If it was detected continuously for 20 seconds or more, a single task such as data entry or browsing was performed”, “Detected data less than 20 seconds Is just passing in front of the trap device 101, and there is no work there. " Even if it is less than 20 seconds, it is assumed that “when the same location was detected intermittently, the work was performed while changing the direction and position of the body” and combined with the business data before and after that Interpret.

  If the same device is used as the node device 102 and the trap device 101 for the person, object, and place to be measured during the measurement period, the data accumulated in the node device 102 and the trap device 101 can be easily associated.

  Furthermore, if the person-in-charge information is associated with the person, object, and place to be measured with an identification name, it becomes easy to extract the work status data for each person in charge.

  In order to accumulate the collected data of the day in the general-purpose computer, the node device 102 is placed on the cradle at least once a day. Thereby, the user can acquire and browse the daily business situation from the core server 106.

The raw data collected by each node device 102 is transferred to a general-purpose computer via a cradle. The raw data is further transferred from the general-purpose computer to the backbone server. When there is a display request from the user, the basic server processes the raw data into an expression method required by the user and outputs it to the display terminal.

  Next, how various measurement data are accumulated in the node device 102 will be described.

  The node device 102 includes a sensor for infrared transmission / reception and a storage unit that collects a reception log.

  The collection interval can be arbitrarily set according to the nature of the information to be collected and the type of “information related to business efficiency” to be visualized. The following is an example when the collection interval is 10 seconds.

In the case of an infrared reception log, the node device 102 performs infrared transmission / reception at intervals of 10 seconds, and records the information when received. If there is a trap device 101 in the vicinity thereof, the identification information of the trap device 101 is recorded together with the transmission / reception time. By using the recorded data, it is possible to quantify the time that the wearer of the node device 102 has performed work at the place where the trap device 101 is installed. Further, when the node device 102 is put on an object, the time that the object attached with the node device 102 is used at the place where the trap device 101 is installed can be quantified.

  The data stored in the node device 102 is accumulated on the PC.

  FIG. 2 is an example of the data structure of one of the raw data 105 stored in the node device 102 and transferred to the general-purpose computer 104 via the cradle 103, that is, the infrared reception log.

The data of the infrared reception log is the trap device 101 or node device ID.
201, measurement date 202, measurement time 203, trap device ID 204, and node device ID 205. All data recorded in the measurement date 202 and the measurement time 203 are accumulated in the trap device ID 204 and the node device ID 205. Therefore, each is not necessarily one.

  206 is an example of infrared reception log data accumulated by this configuration. Trap device 101 or node acquired by trap device 101 having identification information “TID_device 1” between “2011/09/02 18:42:00” and “2011/09/02 18:42:30” The identification information of the device 102 is accumulated in time series.

Reference numeral 207 denotes another example of infrared reception log data accumulated by this configuration. The trap device 101 acquired between “2011/09/02 15:05:10” and “2011/09/02 15:15:00” by the node device 102 having the identification information “NID_return box 2” or The identification information of the node device 102 is accumulated in time series.

Next, a data interpretation method will be described. Based on the data of the infrared reception log collected and stored by the node device 102, information on when and what type of business is performed is derived to obtain a quantitative value indicating the business status.

  FIG. 3 is an example in which a business is defined by location (group) in order to identify the type of business.

  The type of business is determined by defining the business by location (group). That is, in the case of laboratory work, if the urinalysis is performed, the urinalysis area 301 is first defined. Further, a place 302 for receiving urine, a place 303 for receiving a test paper and viewing the reaction, a place 304 for analyzing with an analyzer, a place 305 for viewing and inputting results, and a place 306 for performing additional examination with a microscope are defined. Then, the trap device 101 is installed at the defined location, and the trap device 101 and the location are related (312 to 316).

By defining the business place in this way and installing the trap device 101 at each defined place, if there is a detection record at the place defined as the urine test work, it can be interpreted that the urine test work was being performed.

  FIG. 4 is an example in which the business situation is visualized by the business definition and interpretation method shown in FIG.

   From the business status data 401 in which the business status of the person wearing the node device 102 having the identification information “NID_Examiner 1” is defined as “group”, the total business time 402 and the business time 403 in each business area I understand. That is, it can be understood that about 47 minutes out of the total work time of 480 minutes was work in the blood collection area.

  Further, when the main task of the person wearing the node device 102 having the identification information “NID_test engineer 1” is a urine test, only the task status performed in the urinalysis area 301 is displayed instead of the “group”. You can see in detail. Reference numeral 405 denotes an example of data obtained by extracting details of the work 404 in the urinalysis area 301. The business situation in the urinalysis area 301 is shown for each business place.

  Reference numeral 406 denotes an example in which data 401 is displayed as a bar graph.

  Reference numeral 407 denotes an example in which the data 405 is displayed as a bar graph.

The data collected at 10-second intervals using the node device 102 is processed into a roughness that is easy for the user to use and visualized, thereby making it easier to grasp the business situation.

  FIG. 5 shows an example in which the job definition and interpretation methods shown in FIGS. 3 and 4 are applied to jobs of different working styles.

  For example, in the case of reception work in an examination room, first, a reception area 501 is defined. Then, a reception window 502 for patients and a data shelf 503 such as a medical record are defined as main business places. Then, the trap device 101 is installed at the defined location, and the trap device 101 is associated with the location (each has identification information 512 “TID_response window” and identification information 513 “TID_sample shelf”). However, the reception work often leaves the office to support the patient, and the destinations vary. In such a case, the time that has not been detected in the reception area 501 is interpreted as the time spent on the patient support operation.

FIG. 6 is an example of quantifying the time of work performed outside the main work area. In this figure, patient support work is taken as an example.
Reference numeral 601 denotes work status data of a person wearing the node device 102 having identification information “NID_reception 1”. The time 602 in which neither the node device 102 nor the trap device 101 is detected can be interpreted as being out of the defined work area, that is, in the patient support work.

On the other hand, in the blood collection area 604, there is a record facing a person wearing the node device 102 having identification information “NID_blood collection 1”. From the time of this recording until the next service window, that is, until it is detected in the main work area of the person wearing the node device 102 having the identification information of “NID_reception 1”, the re-examination support work was performed. Can be interpreted.

Hereinafter, other embodiments for carrying out the present invention will be described with reference to the accompanying drawings.

  The business situation can be visualized from the time the business person is in contact with the place where the business is performed, the equipment used, and other people.

  FIG. 7 is an example showing a business place where a person wearing the node device 102 with the identifier “NID_inspection engineer 1” stayed. By classifying the information collected by the node device 102 for each detected trap device 101 and displaying it in a bar graph, it is possible to indicate which device at what location and in what proportion the worker used when performing the work.

If the user of the business situation data sees FIG. 7, the business situation that the most frequently used place in the urine examination area 301 is the TID_microscopy 701 can be seen at a glance.

  The occurrence status and amount of non-stationary work can be visualized from the time when the person performing the work was in contact with the place where the non-steady work is performed, the equipment used, and other people.

  FIG. 8 is an example in which a steady business and an unsteady business are correlated and visualized.

  In this example, “telephone reception” and “inspection request by air shooter” are defined as non-stationary work, and the node device 102 is accessed when each non-steady work occurs, and the air shooter outlet 803. It is attached to.

  A graph 801 is a result of arranging the data collected by the node device 102 of the identification information “NID_examiner 1” in time series and color-coding.

  From this graph, it can be seen that the time spent at the business place “TID_test paper inspection” and the usage time of “NID_telephone” overlap (interruption time due to telephone use 804). That is, it is possible to grasp the fact that the test paper inspection work of “NID_Inspection Engineer 1” was interrupted by telephone reception and the interruption time.

Similarly, the fact that the microscope inspection work of “NID_inspection engineer 1” was interrupted by telephone reception and the interruption time can also be grasped (interruption time 805 by telephone use).

  The business situation can be visualized from the time when a person who goes back and forth between multiple rooms is in contact with the place where the work is performed, equipment used, and other people.

  FIG. 9 is an example of data for visualizing the amount of movement to a remote room.

  The data 901 records the fact that the wearer of the node device 102 with the identifier “NID_reception 1” leaves the reception desk and goes to the blood collection room (record data 902 of facts made to the blood collection room). From this, it is understood that the wearer of the node device 102 with the identifier “NID_reception 1” needs to come and go to the blood collection room in order to perform the work.

  Furthermore, based on this fact, if the reception worker defines the work to be performed in the blood collection room and attaches the node device 102 or the trap device 101, the time required for movement, the equipment and work used in the blood collection room, etc. Detailed information such as location can be collected.

In addition, by continuously measuring the work status and accumulating data, it is possible for the receptionist worker to determine whether the blood collection room work is steady or non-stationary.

  Visualize the time required to move and stay at each location for equipment that affects multiple locations and operations.

10 is an example of data collected by attaching the node device 1003 having the identifier “NID_return box 1” to the return box 1002.
This graph makes it possible to grasp at a glance how the returnable box has moved during the inspection work of the day. In addition, by continuously measuring the work status and accumulating data, it becomes possible to grasp places and time zones where movement is likely to be delayed.

  Visualize changes in the number of business workers for each business area.

  FIG. 11 is a graph showing, in chronological order, the number of times the node device 102 is detected by the trap device 101 installed in each area constituting the laboratory operation.

  Looking at the change in the number of detections 1101 in the blood collection area, the peak continued from 8:30 to 11:30 when the reception desk was open, and the number of detections was still high after 12:00. You can see that you ca n’t leave.

  From the transition of the number of detections 1102 in the urinalysis area, it can be seen that the number of detections increases from the time when the reception desk closes, and the situation where the number of detections is higher than other areas continues thereafter. In urinalysis, microscopic examinations are performed on specimens that require retesting in the morning urinalysis using an analyzer.

If a user who knows the contents and characteristics of the business to be measured looks at the transition of the number of node device detections using this graph, it can be intuitively determined whether the work rate in each area is changing appropriately. I can grasp.

  You can visualize the staying time for each business area and the type of business of the visitor.

  FIG. 12 is a diagram showing the total number of detections of the node device 102 for each area where work is performed and the number of detections for each node device 102 that is a breakdown of the total number of detections.

  It can be seen from the blood collection area detection result 1201 that seven types of node devices 102 have been detected in the blood collection area. On the other hand, it can be understood from the detection result 1202 in the urine examination area that only two types of node devices 102 are detected. That is, it can be visualized that the number of workers in the urinalysis area is smaller than that in the blood collection area.

  FIG. 13 is a schematic diagram illustrating the number of detections for each node device in the total number of detections of the node device for each area where work is performed. The difference in the number of types of detected node devices 102 is relatively expressed by the size of a circle. A large circle indicates that there are many people or things that use the business area, that is, an area that affects the performance of a plurality of business operations. A small circle indicates that there are few people or things using the business area, that is, the number of users is limited.

  The user changes the parameters according to the business information to be expressed and calls the target graph on the display terminal. For example, the number of detections in an arbitrary business area / the total number of detections, the number of detections in an arbitrary node device / the total number of detections in an arbitrary business area, and the like. These calculation results are used for the diameter of the circle, processed appropriately according to the size of the display screen, and displayed on the display terminal.

  When a schematic diagram of a business area can be easily created as shown in FIG. 13, the user inputs a schematic diagram of the business area in advance. And this system draws the circle based on the above-mentioned calculation and processing result on the schematic diagram. Of course, even when there is no schematic diagram, the above-described calculation / processing results can be displayed on the display terminal.

FIG. 14 shows an example in which the information in FIG. 13 is displayed without using a schematic diagram of the business area.

  As another example that can be visualized by this system, a means for indicating the business situation in association with the processing performed on the analyzer is shown.

  Some analyzers used in laboratories have a function of accumulating operation logs such as user login IDs and processing contents. If the time data recorded in the operation log and the time data of a person staying in the vicinity of the device are associated with each other, the work performed on the device can be specified.

  FIG. 15 is an example in which business situation data is associated with an operation log acquired from the apparatus. The business status data 1501 and 1502 indicate the identification information of the node device 102 detected by the trap device 101 having the identification information “TID_device 1 operation unit” and “TID_device 1 sample storage unit” every minute. It is an example. The “TID_device 1 operation unit” is a part used in a task of requesting the analysis device to perform analysis or confirming the analysis result. The “TID_device 1 sample storage section” is a place where containers of analyzed samples are stored. The collected containers are collected by the laboratory technician and transferred to the designated storage location.

  If the operation log 1503 of the device is compared with the time and analyzed, it is understood that the work performed by “NID_Examiner 1” in the “TID_device 1 operation unit” was an analysis request (device operation log Part 1505).

  Further, it can be seen from the business status data 1502 that “NID_Examiner 1” and “NID_Examiner 2” have stayed in “TID_Device 1 Sample Storage Unit” for at least 3 minutes (part 1507 of the business status data). . Since the first analysis completion report in the operation log is “2012/01/27 10:28:01” (part 1506 of the operation log of the device), the sample container is near “TID_device 1 sample storage”. It can be seen that work other than the collection was done.

In the above case, if it is desired to pursue what the work performed in the “TID_device 1 specimen storage unit” is, this system may be combined with means such as interviewing and recording using a camera.

  In addition, this system can record the person who operates the analysis apparatus more accurately than the operation log of the apparatus.

The task status data 1501 in FIG. 15 indicates that “NID_Examiner 3” has performed some task at “TID_device 1 operation unit”. On the other hand, the change log of the login user name is not recorded in the operation log 1503 of the apparatus. In other words, all the operations are performed by the same person on the record, which does not match the actual situation.

  As described above, according to the present system, it is possible to automatically collect data for grasping the business situation, convert it into information indicating line efficiency, and display the conversion result for the entire business.

In addition, since the trap device 101 used for measuring the activity location for each business can be installed in any location, the measurement area and target can be set and changed arbitrarily according to the content of the business that the user wants to visualize. can do.

DESCRIPTION OF SYMBOLS 101 ... Trap apparatus 102 ... Node apparatus 103 ... Cradle 104 ... General-purpose computer 105 ... Elementary data 106 ... Core server 107 ... Display terminal 201 ... Trap apparatus 101 or node Device ID
202 ... Measurement date 203 ... Measurement time 204 ... Trap device ID
205 ... Node device ID
206, 207 ... Infrared reception log data example 301 ... Urine test area 302 ... Urine receiving location 303 ... Reaction viewing location 304 ... Analyzing device analysis location 305 ... Results Location 306 for browsing or inputting information 401 Location for additional examination with a microscope 401 Business status data 402 Total business time 403 Business time 404 In urinalysis area 301 Business 405... Example of data obtained by extracting details of business 404 in urinalysis area 301. Example 406... 401 displaying data in bar graph. Example 407.・ Reception area 502: Patient contact window 503: Document shelf 512: Reception window identification information 513: Sample shelf identification information 601: Business situation data 602 ... time when no detection 604 ... face-to-face recording 701 ... TID microscopic examination 801 ... graph 802 ... telephone 803 ... air shooter outlet 804 ... interruption time due to telephone use 805 ..Interruption time due to use of telephone 901... Data 902... Recorded data 1001 of facts that have been made to the blood collection room 100... Example of collected data 1002. Number of detections in area 1102 ... Number of detections in urinalysis area 1201 ... Detection results in blood collection area 1202 ... Detection results in urinalysis area 1501, 1502 ... Business condition data 1503 ... Device operation log 1504... Operation status data part 1505. Device operation log part 1506. Device operation log part 1 07 ... business situation part of some 1508 ... business situation data of the data

Claims (13)

A trap device that emits a signal;
A node device for receiving a signal from the trap device within a predetermined distance;
A computer for processing information obtained based on the infrared medical examination status of the node device;
An information processing system having a display device for displaying information processed by the computer,
The trap device is provided for a plurality of fixed objects whose positions are fixed,
The node device is prepared for a movement object whose position moves,
The computer is based on information of a signal transmitted from any of the plurality of fixed objects by the node device to be moved,
An information processing system, wherein the staying state in which the moving object stays in the plurality of fixed objects is displayed on the display device.
The information processing system according to claim 1,
When the node device to be moved detects a signal from the trap device for a predetermined time or more,
It is determined that the moving object has stayed at the fixed object.
The information processing system according to claim 1,
Classifying a predetermined plurality of fixed objects among the plurality of fixed objects as one fixed object group;
An information processing system, wherein a staying situation in which the moving object stays in the fixed object group is displayed on the display device.
The information processing system according to claim 1,
An information processing system, wherein the fixed object on which the moving object stays is displayed on the display device in time series.
The information processing system according to claim 3.
An information processing system, wherein a fixed target group in which the moving target stays is displayed on the display device in time series.
The information processing system according to claim 1,
Predetermining a fixed object in which the moving object stays constantly among the plurality of fixed objects,
The information processing system, wherein the display device displays the plurality of fixed objects that the stationary object stays on and the plurality of other fixed objects that stay on the display device.
The information processing system according to claim 1,
An information processing system characterized in that the display device displays a stay time during which the moving object stays on a fixed object.
The information processing system according to claim 1,
An information processing system for displaying a relationship between a plurality of fixed objects in which the moving object stays and the number of times of staying in the plurality of fixed objects within a predetermined time.
A trap device that emits a signal;
A node device for receiving a signal from the trap device within a predetermined distance;
A computer for processing information obtained based on the infrared medical examination status of the node device;
An information processing system having a display device for displaying information processed by the computer,
The trap device is provided for a plurality of fixed objects whose positions are fixed,
The node device is prepared for a plurality of moving objects whose positions move,
The computer is based on information of a signal transmitted from any of the plurality of fixed objects by the plurality of node devices to be moved,
An information processing system, wherein the staying state in which the plurality of moving objects stay on the plurality of fixed objects is displayed on the display device.
The information processing system according to claim 9.
Classifying a predetermined plurality of fixed objects among the plurality of fixed objects as one fixed object group;
An information processing system, wherein a staying situation in which the moving object stays in the fixed object group is displayed on the display device.
The information processing system according to claim 9.
The number of times that the moving object stays is displayed in time series for each of the fixed objects.
The information processing system according to claim 10.
An information processing system for displaying the number of objects to be moved that have stayed in the fixed object group.
The information processing system according to claim 1 or 9,
An information processing system, wherein the moving object, a staying situation staying in the plurality of fixed objects, and a usage history of the fixed object are displayed in association with each other on the display device.