JP2012098901A - Environmental monitoring system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To monitor an environment by collecting, accumulating, managing and providing environmental data for each place and upon guaranteeing accuracy of the data at a certain level or higher, without fixing every kind of sensor at each place.SOLUTION: An environmental monitoring system includes: a step for utilizing every kind of sensor attached to a moving object; a step for using the sensor to measure an environment around the moving object and acquire environmental measurement values; a step for measuring a position of the moving object to which the sensor is attached or of the sensor itself; a step for associating a result of the measurement with the environmental measurement value to monitor the environment at the position; a step for detecting an error in measurement time through mutual comparison of acquired environmental measurement values; and a step for guaranteeing the accuracy of acquired data, based on a result of error detection.

Description

  The present invention relates to a technology for measuring, collecting, storing, managing, and providing environment-related data such as temperature and humidity and performing environment monitoring, for example, an environment monitoring system.

  In logistics, items such as fresh food and some pharmaceuticals require delicate temperature control. Warehouses, factories, distribution centers, etc. that handle these items are classified into buildings, indoor compartments, rooms, shelves, etc. It is important to monitor the temperature. As a multi-point environment monitoring apparatus that measures and monitors the environment in such a plurality of places, there is a method disclosed in Patent Document 1. In Patent Document 1, an environment measuring device such as a temperature sensor or a humidity sensor is installed in each of a plurality of locations to realize multipoint monitoring. More specifically, the temperature or humidity of a plurality of locations can be individually monitored, and by registering identification numbers automatically based on the installation location information previously written in the temperature or humidity sensor, specialized knowledge and This makes it possible to easily replace or add a temperature or humidity sensor without requiring any technology.

JP 2004-239871 A

  According to the technique described in Patent Document 1, in order to acquire environmental measurement values such as temperature data and humidity data for each location, at least one environmental measurement device such as a temperature sensor and a humidity sensor is installed for each location. ing.

  However, when monitoring the environment of a plurality of locations in a site such as a general warehouse, factory, or distribution center, a large number of environmental measuring devices are required, and installation work becomes complicated. In addition to the above problem, there is a problem that it is necessary to ensure the accuracy of the time when the environmental measurement is performed. For example, if you try to monitor the environment inside or outside a warehouse, factory, or distribution center by moving an environmental measurement device, if there is an error in the measurement time, the environment outside the building will be mistaken as the environment inside the building. There is a problem such as.

  Accordingly, an object of the present invention is to enable environmental monitoring using environmental measurement values such as temperature data and humidity data for each place with a simple device.

  In order to achieve the above object, according to the present invention, when environmental monitoring is performed by continuously recording the measurement value of a sensor, the environment of an arbitrary place can be obtained by moving the sensor or an article in which the sensor is installed. Even if the data cannot be recorded cumulatively, the measurement results from other sensors are cumulatively estimated using the historical information recorded in association with the attribute information, and the estimated environmental value for a predetermined time is estimated. It is what is used. In this case, it is an embodiment of the present invention that the environment estimated value uses an average value or variance of history information. The attributes include the type of sensor (and / or information for identifying the sensor), location, measurement date and time, and the like.

  More specifically, the present invention uses a sensor that acquires environmental measurement values such as a temperature sensor and a humidity sensor attached to an article such as a box or a pallet, and a positioning device that measures a location where the article is stored. Thus, it is possible to measure, collect, and accumulate environmental measurement values such as temperature data and humidity data for each location. Note that the positioning device includes a device using a GPS and a device using a storage medium such as an RFID tag installed at a predetermined location. For the latter, information specifying the location is recorded on the storage medium and read, or information identifying itself is stored on the storage medium, and the database is associated with the information identifying the storage medium. Using information indicating the location stored in the.

  Furthermore, the sensor and the positioning device are diverted, for example, for the purpose of temperature management or humidity management of foods and pharmaceuticals, and the positioning device is also installed for the purpose of location management or flow line management of people and forklifts. It is possible to divert the positioning device provided.

The environment monitoring apparatus according to the present invention that realizes the above-described features includes a place data recording unit that holds a relation period between an article identifier and a place identifier as place data in order to record the location of the article.
Environmental data recording means for storing the sensor identifier, the environmental measurement value measured by the sensor and the measurement date and time as environmental data in order to record the environmental measurement value measured by the sensor attached to the article;
Relation data recording means for holding a relation period between the identifier of the article and the identifier of the sensor;
An article that existed in an arbitrary place at an arbitrary date and time is acquired from the location data recording means, a sensor associated with the article is acquired from the related data recording means, and environmental data measured by the sensor is further obtained. By obtaining from the environmental data recording means, a processing unit for calculating the environmental data of the place at the date and time,
The environmental history recording means for holding the calculated environmental data as an environmental data history for each place, and the time series data measured by various environmental measuring devices registered in the environmental data recording means are compared with each other. Thus, for the time error detection program for detecting an error in the measurement time of each time series data and the time series data in which an error occurs in the measurement time detected by the time error detection program, the environment in which the time series data is measured Based on the error data recording means for registering the identifier of the measuring device and the identifier data of the environmental measuring device registered in the error data recording means, if there is a certain number of registrations, the measurement of the environment measuring means And a time error determination program for determining that an error has occurred on the day and time.

  In addition, the problem which this application discloses, and its solution means will become clear from the column of the best mode for carrying out the invention and the drawings.

  According to the present invention, it is possible to perform environmental measurement or control using the same while suppressing the number of environmental measurement devices (sensors) with a simple mechanism.

1 is a block diagram illustrating an overall configuration of an environment monitoring system according to an embodiment of the present invention. It is an example of the scene where the environmental monitoring system regarding one Embodiment of this invention is applied. It is an example of the scene where the environmental monitoring system regarding one Embodiment of this invention is applied. It is an example of the place data table which the place data recording means regarding one Embodiment of this invention hold | maintains. It is an example of the environmental data table which the environmental data recording means regarding one Embodiment of this invention hold | maintains. It is an example of the relationship data table which the relationship data recording means regarding one Embodiment of this invention hold | maintains. It is an example of the environmental history table which the environmental history recording means regarding one Embodiment of this invention hold | maintains. It is a processing flow of the place environment calculation program regarding one Embodiment of this invention. It is an example of the processing flow of the place environment estimation program regarding one Embodiment of this invention. It is an example of the processing flow of the place environment estimation program regarding one Embodiment of this invention. It is an example of the processing flow of the place environment estimation program regarding one Embodiment of this invention. It is an example of the place relation table which the place relation recording means regarding one Embodiment of this invention hold | maintains. It is an example of the processing flow of the failure detection program regarding one Embodiment of this invention. It is an example of the processing flow of the time error detection program regarding one Embodiment of this invention. It is an example of the detection processing flow of the sensor which has produced the error in the time regarding one Embodiment of this invention. It is a conceptual diagram of the time error detection process regarding one Embodiment of this invention. It is a conceptual diagram of the time error detection process regarding one Embodiment of this invention. It is a conceptual diagram of the time error detection process regarding one Embodiment of this invention. It is an example of the error data table which the error data recording means regarding one Embodiment of this invention hold | maintains. It is an example of the processing flow of the time error detection program regarding one Embodiment of this invention. It is an example of the processing flow of the time error detection program regarding one Embodiment of this invention. It is an example of the place relation table which the place relation recording means regarding one Embodiment of this invention hold | maintains. It is a conceptual diagram of the time error detection process regarding one Embodiment of this invention. It is a conceptual diagram of the time error detection process regarding one Embodiment of this invention. It is an example of the processing flow of the time error determination program regarding one Embodiment of this invention.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
First, a configuration example of the present embodiment and each element in the configuration example will be described.
FIG. 1 is a block diagram of an environment monitoring system according to the present embodiment. The environmental monitoring system includes a place data collection device 107 that measures the location of goods such as boxes and pallets entering and leaving a warehouse and the like, and is attached to the goods for state management of the goods, such as temperature and humidity around the goods. The environment measurement device 101 is a sensor that measures the environment and acquires environmental measurement values such as temperature data and humidity data that are digital data, and the environment measurement values measured by the environment measurement device 101 are acquired by wireless communication or wired communication. The environmental data collection device 104 that passes the environmental measurement value, the identifier of the environmental measurement device, and the measurement date and time as environmental data to the environmental monitoring device 111, and the data collected by the environmental data collection device 104 and the location data collection device 107 are used. The environment monitoring device 111 converts the environment data for each location and monitors the location environment.

  The environment measurement device 101 is a sensor device attached to an article such as a box or a pallet for the purpose of state management, and includes an environment measurement unit 102 that measures an environment around the article and obtains an environmental measurement value converted into digital data. In addition to the acquired environmental measurement value, environmental data transmission means 103 is provided for transmitting the identifier of the environmental measurement device to the environmental data collection device 104.

  The environment measuring means 102 measures the environment such as temperature, humidity, atmospheric pressure, illuminance, sound volume, suspended particle amount, etc., and temperature data, humidity data, atmospheric pressure data, illuminance data, sound volume data, suspended particle amount data, etc., which are digital data. It is various digital sensors which acquire the environmental measurement value.

  The environmental data transmission unit 103 transmits an environmental measurement device identifier such as a sensor ID for uniquely identifying the measured environmental measurement device 101, an environmental measurement value measured by the environmental measurement unit 102, and a measurement date and time to the environmental data collection device 104. Wireless LAN, infrared communication, wireless communication such as UWB, and wired communication such as USB. The measurement date and time need not be transmitted. In this case, the environmental data collection device 104 needs to add the acquisition date and time that is the date and time when the environmental data collection device 104 received the environmental data. In addition, since there is an error between the measurement date and time and the acquisition date and time, when registering data in the environmental data recording unit 120, the data registration program 125 performs registration after converting the acquisition date and time to the measurement date and time. Also good. As this conversion processing, it is possible to subtract a preset value from the acquisition date and time to obtain a measurement date and time. Further, when data is transferred from the environmental measurement apparatus 101 to the environmental data collection apparatus 104, it may be transmitted from the environmental data transmission means 103 in a push type, or may be acquired from the environmental data collection apparatus 104 in a pull type. . Moreover, the timing of delivery of environmental data by the means may be sequentially transmitted after measurement, or may be transmitted after a memory is provided in the environmental measurement device and accumulated according to a predetermined condition such as a fixed period. In addition, instead of communication, the environmental data measured by the environmental measuring unit 102 may be stored in a memory card or the like that can be separated and transported from the environmental measuring device 101, and the environmental data may be transported to the environmental data collecting device 104. In this case, the system side reads and reads data from a reading position (including a slot or the like) manually inserted or inserted.

  The environment data collection device 104 is a device that acquires the environment measurement value measured by the environment measurement device 101 and the identifier of the related measurement device, and transmits it to the environment monitoring device 111 as environment data. The environment data transmission unit 103 transmits the environment data. Environmental data receiving means 105 for receiving data and environmental data transmitting means 106 for transmitting the environmental data to the communication device 115 in the environmental monitoring apparatus 111 are provided. The temperature, humidity, atmospheric pressure, illuminance, volume, suspended particle amount, etc. transmitted by the environmental data transmission means 103 by wireless LAN, infrared communication such as wireless communication, wired communication such as USB, or data exchange using a memory card, etc. In addition to the environmental measurement value, environmental data receiving means 105 for receiving an identifier of the environmental measurement device for uniquely identifying the environmental measurement device is provided. The environmental data collection device 104 may be a device such as an independent base station that receives environmental data, or the environmental monitoring device 111 includes the environmental data receiving means 105 and is integrated with the environmental monitoring device 111. Good.

  When the environmental measurement device 101 does not add the measurement date and time, the environmental data collection device 104 sets the environmental data acquisition date and time via the wired or wireless network 110 in addition to the environmental measurement value and the identifier. And sent to the environmental monitoring device 111 as environmental data. Here, when an error occurs between the measurement date and time and the acquisition date and time, correction is performed as appropriate.

The place data collection device 107 is a device for acquiring a two-dimensional or three-dimensional coordinate of a place where an article to which the environment measuring device 101 is attached, or a place identifier for uniquely specifying a place such as a room code or a shelf code. And positioning means 108 for acquiring the coordinates or location identifier, and location data transmission means 109 for transmitting the coordinates or location identifier to the communication means 115 in the environment monitoring device 111.
The positioning means 108 has the following four implementation forms.

  In the first embodiment, data carriers such as RFIDs and barcodes are installed in both a place and an article, and a location identifier and an article identifier are stored in each. For example, when storing an article in the place, the place identifier is obtained by reading an RFID or barcode installed in the place with a reader, and the identifier of the article is linked to this, and the relationship between the place and the article is started. The date and time of acquisition, which is the date and time, is recorded in the location data recording means 121 as location data, thereby collecting location data.

  In the second embodiment, a reader is fixedly installed at a place instead of a tag. In this case, a location identifier is stored in advance in the memory of the reader body, or correspondence information between the reader identifier and the location identifier is held in an external storage, and one or more readers are fixedly installed in the location. When an article is stored in the place, a reader fixedly installed in the place obtains an article identifier from a tag attached to the article, and a place identifier recorded in its own memory or external storage, and a place Location data is collected by adding the acquisition date and time that is the relationship start date and time of the article and registering it in the location data recording means 121 as location data.

  In the third embodiment, radio waves such as GPS, wireless LAN, and UWB are used. A radio wave transmitter / receiver is attached to an article or a container that moves with the article, and the radio wave transmitter / receiver acquires its own two-dimensional or three-dimensional coordinate position. In this method, an article identifier is acquired by, for example, recording an article identifier in a memory in a radio wave receiver and transmitting the article identifier on the memory when transmitting the article identifier together with the coordinates to the environment monitoring device 111. The radio wave transmitter / receiver's own identifier is acquired as an article identifier, the correspondence information between the radio wave transmitter / receiver identifier and the article identifier is recorded in advance in the external storage means as related data, and the location data is stored in the environmental monitoring device. It is possible to obtain a method by converting the identifier of the radio wave receiver into an article identifier before or after transmission. Further, the acquired coordinate value may be recorded as it is in the location data recording means 121 as a location identifier, or may be converted into a location ID or a shelf ID and the location ID or shelf ID may be registered as a location identifier. .

As a fourth embodiment, in addition to the positioning method using the data carrier or wireless communication, it is possible to perform positioning by directly inputting a location identifier such as a room code or a shelf code from an input device such as a keyboard. Good.
The place identifier and the article identifier acquired by the various means described above are the place data collection device 107, the date and time when the identifier of the article existing at the place is acquired in addition to the location identifier such as the coordinates and the place ID. To the environment monitoring device 111 via the network 110.

  When the storage of the article is ended, the date and time when the relation between the article and the place ends is recorded in the place data recording unit 121. This is performed by the data registration program 125. For example, when there is a signal indicating the end of storage in the location data received from the location data transmission means 109, the end date / time has not yet been received from the location data recording means 121 using the article identifier as a key. A method may be used in which a record that is not recorded is searched and the acquisition date and time of the location data is recorded as the end date and time.

  In the second embodiment, the method for obtaining the end date and time is the first embodiment, and when the item is taken out of the place, the date and time when the tag placed on the item and the place is read is the end date and time. If the reader installed at the location reads peripheral tags regularly, the date and time when the tag reading failure exceeds the preset number of times is set as the end date and time. The device 111 includes a central processing unit 112, an input device 113 such as a mouse and a keyboard, an output device 114 such as a display, a communication device 115 such as a wireless LAN and a wired LAN, and a storage device 116 such as a memory and a hard disk drive. Computer devices such as personal computers, server computers, and handheld computers.

  The storage device 116 includes an environmental data recording unit 120 that records the environmental data transmitted from the environmental data collection device 104, a location data recording unit 121 that records the location data transmitted from the location data collection device 107, and the environmental measurement device 101. Based on the relationship data recording means 122 for recording the association information with the article to which the apparatus is attached and the data recorded in the three recording means 120, 121, 122, the temperature and humidity for each place at a certain date and time , A place environment calculation program 118 for calculating environment data such as atmospheric pressure, illuminance, sound volume and suspended particle amount, and an environment history recording means 123 for holding the environment data for each place calculated by the 118 in time series.

  In addition, when the environmental data at a certain place at a certain date / time cannot be calculated by the location environment calculation program 118 because the collected environmental data is insufficient or missing, the environmental data at that date / time is estimated. The location environment estimation program 117 for complementation, the location relationship recording means 124 for recording information about the location near the location, which is information used for the estimation, and the environment monitoring device 111 are input. The data registration program 125 for performing the process of registering the registered data in each recording unit, the coordinate relationship recording unit 127 for recording the relationship information between the coordinate value and the location identifier, and the coordinate relationship recording unit 127 are used as the coordinates. A coordinate conversion program 126 that performs mutual conversion processing between a value and a location identifier.

  Furthermore, a failure detection program 119 for performing failure detection by determining whether or not the data value of the environmental data acquired by the environment measurement apparatus 101 is an abnormal value is provided.

  When the environment measuring device 101 includes a timer for acquiring the measurement time, a time error detection program 128 for detecting an error of the built-in timer, and a sensor ID detected by the time error detection program 128. And error data recording means 129 used for determining whether or not there is a final time error.

Next, the environmental monitoring method for a plurality of locations according to the above-described embodiments will be described based on a specific example.
2 and 3 show application examples of the environmental monitoring system in a distribution warehouse.
First, the process of recording location data in the location data recording unit 121 using the location data collection device 107 will be described with reference to FIGS. 2, 3, and 4.

Before describing the processing, first, the location data collected using the location data collection device 107 will be described with reference to FIG.
FIG. 4 shows an example of a location data table recorded in the location data recording means 121. In this table, the start date and time 401 records the date and time when the article began to be stored in the place, the end date and time 402 records the date and time when the article was stored, and the article ID 403 records the item acquired from the tag attached to the article. An article ID that is an identifier is recorded, and a shelf code that is a place identifier acquired from a tag attached to the place is recorded in the place ID 404. In this example, the start date and time 401 is the date and time when the article tag 202 and the shelf tag 205 are read using the RFID reader that is the location data acquisition device 106 shown in FIG. The date and time when the article tag 202 and the shelf tag 205 are read using the RFID reader.

  For example, the second line starts storing items by acquiring the item ID “Tag0034” from the item tag and the shelf code “A” from the tag attached to the place at 09/12/01 10:01:32 After that, it means that the article was taken out from the place “A” at 09/12/05 09:12:44. In line 3, the item ID “Tag0231” is acquired from the item tag and the shelf code “A” is acquired from the tag attached to the place at 09/12/01 10:12:32, and storage is started. However, since the value of the end date 402 is null, it means that the article has not been taken out from the place “A”.

Next, a method for acquiring and collecting the location data shown in FIG. 4 using the location data collection device 107 shown in FIG. 1 will be described with reference to FIGS.
FIG. 2 shows a scene in which an article 201 to which an article tag 202 and a sensor 203 are attached is stored in a shelf of a shelf code 204a in the distribution warehouse after being received in the distribution warehouse 204. Here, the shelf code is a place identifier for uniquely identifying a shelf. Each shelf is attached with an RFID storing the shelf code of the shelf. FIG. 3 shows a more specific example in which the article 201 is stored on the shelf. In this example, the location data collection device 107 includes a tag 305, an article tag 202, and a tag reader 306. In this example, the location data is acquired two times when the article 201 starts to be stored at the location “A” and when it is taken out from the location “A”.

First, a procedure for acquiring location data when the article 201 starts to be stored in the location “A” will be described.
As described above, the place “A” is attached with the RFID tag 205 that records the place ID for uniquely identifying the place, and when the article is to be stored in the place “A”, it is shown in FIG. The RFID reader 306 as the location data collection device 107 acquires the location ID “A” as location data from the tag 305 using the tag reading function as the positioning means 108 shown in FIG. Further, the product ID is acquired from the product tag 202, the acquisition date and time are added to the location ID and the product ID, and transmitted to the environment monitoring device 111 via the location data transmission unit 109 shown in FIG. The environment monitoring device 111 receives the location data through the communication device 115 and records it in the location data recording means 121 using the function of the data registration program 125. The acquisition date and time transmitted here is registered by the data registration program 125 shown in FIG. 1 as a start date and time 401 when an article is complemented to the place, and as an end date and time 402 when the article is taken out from the place. For example, in the example of the second line in FIG. 4, “Tag0034” and “A” are read from the article tag 202 and the tag 305 at “09/12/01 10:01:32”, respectively, and the environment monitoring apparatus shown in FIG. 111 shows that the data was recorded in the location data recording means 121 after being transmitted to the computer 111.

Next, a procedure for acquiring location data when taken out from the location “A” will be described.
In the example of FIGS. 2 and 3, the environment monitoring apparatus shown in FIG. 1 is obtained by acquiring the product ID and the location ID from the product tag 202 and the tag 305 using the RFID reader 306, and adding the acquisition date and time, as in the above procedure. The environment monitoring device 111 receives the location data through the communication device 115 and records it in the location data recording means 121 using the function of the data registration program 125. At this time, the data registration program 125 searches the table shown in FIG. 4 for a record whose end date is null with the received article ID and shelf code as keys, and records the received acquisition date as the end date of this record. . For example, in the example of the second line in FIG. 4, the data registration program 125 that has received the location data by the above procedure searches the item ID “Tag0034” and the shelf code “A” as a key, and as a result, the second line record is obtained. Therefore, it indicates that the acquisition date “09/12/05 09:12:44” is recorded at this end date and time.

  Although the above is an example of the location data acquisition method, the specific means of the location positioning may be acquired through an explicit reading operation by a person using a handy type or installation type reader, a shelf, etc. The reader may be acquired by sensing the proximity of the tag and automatically reading it.

  Next, a process for recording environmental data in the environmental data recording unit 120 using the environmental measuring device 101 and the environmental data collecting device 104 shown in FIG. 1 will be described with reference to FIGS. 2, 3, and 5. FIG.

Before describing the processing, first, the environmental data collected using the environmental data collection device 104 will be described with reference to FIG.
FIG. 5 shows an example of the environmental data table recorded in the environmental data recording means 120 shown in FIG. In this environmental data table, the measurement date and time 501 records the date and time when the temperature data as the environmental measurement value is measured and transmitted to the temperature data receiver 304, and the sensor ID 502 records the ID of the temperature sensor that measured the temperature data. In the temperature 503, an environmental measurement value which is measured temperature data is recorded. For example, the second line means that a temperature sensor having “S001234” as an ID at “09/12/01 13:00:00” measured “23.4 ° C.”.

Next, a method for acquiring and collecting the environmental data shown in FIG. 5 using the environmental measuring device 101 and the environmental data collecting device 104 will be described with reference to FIG.
In the example shown in FIGS. 3 and 5, the temperature sensor 203 which is the environment measuring apparatus 101 shown in FIG. 1 acquires temperature data by measuring the environment at intervals of 5 minutes, and the temperature data receiver 304 after acquiring the temperature data. Are sequentially transmitted to the environmental monitoring device 111 as environmental data. The environmental data received by the environmental monitoring device 111 is sequentially registered in the environmental data recording unit 120 by the data registration program 125. At this time, the data registration program registers the measurement date and time, sensor ID, and temperature data as environmental data in the order received.

  Here, a temperature sensor is taken as an example of the environmental measurement device 101, but an environmental measurement device such as a humidity sensor, an atmospheric pressure sensor, an illuminance sensor, a volume sensor, or a suspended particle amount sensor is also effective. Similarly, in this example, the environment data collection device 104 is a wireless communication type temperature sensor reader, but it is also effective for a dedicated device having a wireless communication function or a general-purpose device such as a notebook PC, The environment data transmission means is also effective by a wired communication function such as USB, or data exchange using a memory card.

  By applying the above procedure to each article that is stored in each place after entering the warehouse and to which a temperature sensor and a tag for identifying the article are attached, the place data and the environment data are exchanged with the place data recording means 121. Collected and accumulated in the environmental data recording means 120, respectively.

  Next, a method for calculating and obtaining environmental data of an arbitrary place at an arbitrary date and time from the place environment calculation program 118 from the place data and environment data collected / accumulated by the above procedure is shown in FIGS. A description will be given with reference to FIGS.

  The procedure for calculating environmental data at an arbitrary location at an arbitrary date and time by the location environment calculation program 118 is mainly (1) using the location data recording means 121, the environmental data recording means 120, and the related data recording means 122. Extract environmental data measured at any location. (2) From the extracted environment data, a representative value of the environment data of the place at the date and time is calculated and recorded as an environment history for each place. Therefore, prior to the description of the environmental data calculation procedure, the relationship data and the environmental history for each location will be described with reference to FIGS.

  FIG. 6 shows an example of a relation data table of the relation data recording means 122 that records the relation between the article tag and the sensor attached to the same article. In this table, the article ID 601 records the ID of the tag attached to the article, the sensor ID 602 is the sensor ID that is the identifier of the sensor attached to the same article as the article tag, and the start date and time 603 of those relationships. And end date and time 604 are recorded. For example, in the second line, an article tag having “Tag0034” as an ID for an article and a sensor having “S001234” as an ID are attached to the same article at “09/11/30 09:00:04” Furthermore, it means that either or both were removed at "09/12/12 16:03:01". In the sixth line, an article tag having “Tag0111” as an ID for an article and a sensor having “S000045” as an ID are attached to “09/11/30 09:07:34” and are still attached. It means to remain.

  This relational data is recorded in the relational data table in advance by a registration operation by a person after adding the sensor ID and the reading date and time after reading the article ID with, for example, an RFID reader when the tag and the sensor are attached to the article. It is possible to register by such means.

  Further, this relationship data is not necessarily required to realize this embodiment, and this relationship data may be omitted as long as a means for uniquely identifying the environmental measurement device from the article ID is provided. For example, when using an RFID having a sensor function to make the article ID and the sensor ID the same, it is not necessary to use this relationship data. Alternatively, even when an operation rule is set such that the upper 10 digits of the article ID are sensor IDs, this relationship data need not be used.

Next, an explanation will be given of an environment history in which the result output by the place environment calculation program 118 is held as a history with reference to FIG.
FIG. 7 shows an example of an environment history table recorded in the environment history recording means 123 by the place environment calculation program 118 shown in FIG. In this table, the update date / time 701 records the update date / time of the history information, and the column 702 to the column 708 record the environmental data at the update date / time at the locations “A” to “G”, respectively. For example, in the second line, at 08/12/01 12:40:00, the temperature of the place “A” is 20.3 ° C., the temperature of the place “B” is 19.8 ° C., As for the temperatures of “F” and “G”, since environmental data cannot be acquired, null is recorded as a value. This environment history table is information output by the environment monitoring system.

  Registration of data in the environment history table is executed by the place environment calculation program 118 through two steps as described above. Here, an example of calculating the environmental data of the location “A” at 09/12/01 13:00:00 is shown.

  As the first step, for example, if the time interval of environmental monitoring is set to 10 minutes, it exists in the location “A” for 10 minutes from 09/12/01 12:50:01 to 09/12/01 13:00:00 Acquire environmental data measured by the sensor. From the records of the second, third, and fifth lines in the location data table of FIG. 4, it can be seen that the articles that existed at the location “A” within the time are “Tag0034”, “Tag0231”, and “Tag0123”. Next, from the records on the second, third, and fifth lines in the relational data table of FIG. 6, it is found that the sensors associated with the article “Tag0231” within the time are “S001234”, “S003333”, and “S008888”. Accordingly, from the second, third, and fifth lines in the environmental data table of FIG. 5, the environmental data measured at the location “A” within the time is “23.4 ° C.”, “23.1 ° C.”, “22.9”. It can be specified using the environmental data table.

  The next step is to calculate the value as the environmental data of the place “A” at 09/12/01 13:00:00 based on the acquired environmental data. In this example, the average value “23.1 ° C.” is calculated from the environmental data “23.4 ° C.”, “23.1 ° C.”, and “22.9 ° C.” obtained above, and this is calculated as 09/12/01. The temperature of location “A” at 13:00:00. Any method other than the average value may be used as long as it is a method for calculating one value from one or more data such as the median value “23.1 ° C.” and the maximum temperature “23.4 ° C.”. May be.

In the first step, the time width may be set to zero, that is, data recorded at 09/12/01 13:00:00 may be acquired. Further, when no recorded environment data can be acquired in the time width set to zero or more, for example, (1) the location recorded in the environment history recording unit 123 or the environment data recording unit 120 (2) The environmental data immediately before and immediately after recorded in the environmental data recording means 120 is acquired, and the representative value is calculated by linear interpolation of both data. (3) The location Applying the methods such as (1) using the values calculated in (1) and (2) as they are, (4) obtaining environmental data around the location, and calculating representative values by linear interpolation, etc. Is possible. In addition to the above four methods, any method may be applied as long as it is a method for complementing missing data.
A method of calculating the environmental data of an arbitrary place at an arbitrary date and time, which is executed by the place environment calculation program 118, will be described in more detail with reference to FIG.

  FIG. 8 shows a flowchart of the location environment calculation process executed by the location environment calculation program 118 for calculating environment data such as temperature, humidity, atmospheric pressure, illuminance, volume, and suspended particle amount for each location at an arbitrary date and time. Yes. The processing routine of the location environment calculation program 118 may be automatically executed at regular time intervals, or may be executed by manually starting the processing at an arbitrary date and time.

  First, the place where the environment is calculated is determined (S802). It is necessary to select one of the locations from each location, and the specific means for the selection may be performed by a person, or may be selected mechanically in order or randomly. . Here, as an example, it is determined that processing is performed for the location “A”.

  Next, a start date and time and an end date and time are determined in order to determine from what time to what time environmental data is handled as information used in the calculation (S803). The means for determining the start date and time and the end date and time may be determined by manual input or may be automatically determined mechanically. The start date and time and the end date and time may be the same date and time. As an example, assume that the current date and time is 09/12/01 13:10:00, and information from 10 minutes ago is handled. That is, the update start target time is 09/12/01 13:00:01, and the update end target date is 09/12/01 13:10:00.

  Next, information is retrieved and acquired from the location data table recorded in the location data recording unit 121 shown in FIG. 1 using the information set in steps S802 and S803 as a key. Specifically, from the information regarding the place “A” determined in step S802, (1) the article ID in which the end date and time (column 402) recorded in the place data recording unit 121 is recorded as null, or (2) Search for and acquire article IDs whose end date and time (column 402) recorded in the location data recording means 121 are after the update start date and time determined in step S803 (S804). For example, in FIG. 4, the record in which the place “A” is recorded in the place ID 404 in FIG. 4 is the second line, the third line, the fifth line, and the tenth line. The third line that matches condition 1 and the second and fifth lines that match condition 2 are shown. Accordingly, the product IDs acquired as a result are “Tag 0231”, “Tag 0034”, and “Tag 0 123”. In other words, an article that exists in the location “A” between 09/12/01 13:00:01 and 09/12/01 13:10:00 has “Tag0231”, “Tag0034”, and “Tag0123” as IDs. An article with a tag attached.

  Further, the article ID acquired in step S804 is converted into a sensor ID with reference to the relational data recording means 122 shown in FIG. 1 (S805). For example, here, the ID of the sensor attached to the article having the article ID “Tag0231” is “S003333” referring to the third line in FIG. 6, and attached to the article having the article ID “Tag0034”. The ID of the sensor was “S001234” when referring to the second line in FIG. 6, and the ID of the sensor attached to the article whose article ID is “Tag0123” is referred to the fifth line in FIG. “S008888”. In other words, the sensor that existed in the location “A” between 09/12/01 13:00:01 and 09/12/01 13:10:00 has “S003333”, “S001234”, and “S008888” as IDs. It is a sensor.

  Environment data is acquired from the environment data recording unit 120 using the sensor ID and the start date and time and end date determined in step S803 as keys (S806). For example, in FIG. 5, the measurement date and time 501 is 09/12/01 13:00:01 to 09/12/01 13:10:00, and the sensor ID 402 is any of “S003333”, “S001234”, and “S008888”. The records that are are the second line, the third line, the fifth line, and the tenth line. Therefore, the temperatures acquired as environmental data here are 23.4 ° C, 23.1 ° C, and 23.3 ° C. 23.6 ° C.

Through the above operations (S802 to S806), it is possible to identify the sensors that exist within the time determined in step S803 at the location determined in step S802, and to acquire the environmental data measured by these sensors. The acquired environmental data is stored in the memory and used for subsequent processing (S815). However, the location where the environmental data is stored may be external storage means such as a database in addition to the memory.
However, on the other hand, it is assumed that the sensor cannot be specified at the location within the time, and therefore environmental data is not recorded. For example, in FIG. 4, within the time period from 09/12/01 13:00:01 to 09/12/01 13:10:00, article IDs are assigned to places “D”, “E”, “F”, and “G”. There is no recorded history, so there was no sensor at each location during the time period. Therefore, in the next step (S807), it is determined whether or not environmental data has been acquired.

  If two or more pieces of environment data are acquired as a result of the processing up to step S806, a representative value is calculated from the acquired environment data (S809). For example, here, the environmental data of the place “A” from 09/12/01 13:00:01 to 09/12/01 13:10:00 is 23.4 ° C., 23.1 ° C., 23.3 ° C., 23 Since four values of .6 ° C. can be obtained, an average value is calculated as a representative value of these to obtain 23.4 ° C. As the representative value, a median value or the like can be applied in addition to the average value. Then, the representative value calculated in step S809 is regarded as the environment data of the place at the time, and is recorded in the environment history table of the environment history recording unit 123. In this example, the information to be recorded is “09/12/01 13:10:00” for the update date and time 701 and “23.4” for the shelf A 702 in FIG.

On the other hand, if no environmental data is acquired as a result of the processing from step S802 to step S806, in order to estimate the environmental data of the location, it is recorded in the memory as the environmental data estimation target location, and the environmental history is recorded. Recording on the table of the means 123 is not performed (S808).
Thereafter, the processing from step S802 to step S810 is repeatedly executed for each location (S801, S811).

  After the loop processing is completed, it is determined whether or not the location where the environmental data is estimated is stored in step S808 (S812). When the location where the environmental data is to be estimated is not stored, it is considered that the environmental data has been acquired by the sensor at each location, and after the update result is presented (S814), the process is terminated. However, if the place where the environment data should be estimated is stored in step S808, the place environment estimation program 117 executes the environment data estimation process for the place (S813).

  9, 10, and 11 are flowcharts showing examples of processing in the place environment estimation program 117. The processing routine of the place environment estimation program will be described below.

  FIG. 9 shows a case where environmental data such as temperature data, humidity data, barometric pressure data, illuminance data, volume data, and suspended particle amount data for each place has not been recorded within the time specified when the place environment calculation program is executed. As an example of the estimation program for interpolating the information, an example in which the environment history information immediately before the place is used is shown.

Specifically, first, one location where environment data is estimated is selected from the locations recorded in step S808 (S902).
For example, here the place where environmental data between 09/12/01 13:00:01 and 09/12/01 13:10:00 was not recorded is “D” “E” “F” “G” Therefore, first, the place “D” is selected as the estimated place of the environmental data. Next, the immediately preceding environmental history information related to the location “D” is retrieved and acquired from the environmental history table of the location history recording means 122 (S903). Here, the record on the eighth line in FIG. 6 is the immediately preceding environmental history information, and the information of the place “D” is a value from which 22.7 of the shelf D705 is acquired. Then, the acquired environment data is recorded in the environment history table of the environment history recording means 123 (S904). Here, information that the update date 601 is 09/12/01 13:10:00 and the shelf D705 is 22.7 is recorded.

At this time, if the previous environment history information is null, the estimation result is similarly recorded as null. For example, here, the place “G” is also stored as the estimation target place of the environmental data in the same way as the place “D”, so the processing from step S902 to step S903 is performed. Since the value acquired as a result is “null” from the shelf G708 in the eighth row in FIG. 7, the update date and time is “09/12/01 13:10:00” and the shelf G708 is “ Record as "null". Therefore, in this estimation method, the value of the environment history is always null for a place where the environment history information has not been updated with actual measurement values.
Thereafter, the processing from step S902 to step S904 is repeatedly executed for each environment estimation target location stored in the memory in step S808 (S901, 905).

  FIG. 10 shows a processing routine in the case of estimating the current environment data using the environment history information recorded in the past similar situation as an example of the place environment estimation means. However, the similar situation described here refers to the date and time when the month (for example, January, February, etc.) and the time zone (for example, 9 o'clock, 15 o'clock, etc.) match in the update date of the environmental history. pointing. Therefore, first, the current month and time zone are acquired (S1002).

  For example, since the processing date and time is 09/12/01 13:10:00, the month is “December” and the time zone is “13:00”. Next, one place from which the environmental data is estimated is stored in step S808 (S1003). Here, since the target locations for environment estimation stored in step S1008 are “D”, “E”, “F”, and “G”, the location “D” is selected first. Then, from the environment history table recorded in the environment history recording unit 123, history information that matches the month and time zone determined in step S1002 is retrieved and acquired from the environment history related to the place determined in step S1003 (S1004). ).

  Therefore, in this case, in the environment history table of FIG. 6, the records recorded in “December” at “13:00” are the 4th row, the 5th row, the 7th row, and the 8th row. The environmental data of the location “D” in one record is obtained from the shelf D605 as “22.2”, “22.2”, “23.3”, and “23.4”, respectively. Here, since it is assumed that no environmental history in a similar situation is recorded at the location, it is determined whether or not the value of history information has been acquired as a result of the processing in step S1004 (S1005). For example, for the location “G”, the values of all the environmental data in the 4th, 5th, 7th, and 8th rows are “null”. When one or more pieces of environment history information can be acquired as in the place “D”, a representative value is calculated from the environment data, and the environment history table of the environment history recording unit 123 is updated with the numerical value. For example, since the average value “22.8” is obtained from the values “22.2”, “22.2”, “23.3”, and “23.4”, the update date / time 601 of the environment history table is “09/12/01 13:10:00” D705 is updated as “22.8”. The median value can be applied to the representative value here in addition to the average value. On the other hand, as a result of the processing up to step S1004, when no value as history information can be acquired as in the place “G”, new environment data is also null, and the environment history table of the environment history recording unit 123 is updated. . Thereafter, the processing from step S1002 to step S1008 is repeatedly executed for each environment data estimation target location stored in the memory in step S708 (S1001, S1009).

  FIG. 11 shows a processing routine in the case of estimating the environmental data of the estimation target location using the environmental history information of the location physically adjacent to the estimation target location. This estimation method is based on the assumption that the environment of a place and its surroundings should be similar if there is no physical shield such as a wall. That is, if there is a place “α” and a surrounding place “β”, the place “α” and the surrounding place “β” are not separated by a wall or the like and belong to the same physical space. The environmental data such as the temperature and humidity of the place “α” is similar to the temperature and humidity of the place “β”. Here, there is a need for information that a certain place and its surrounding places are connected as a space without a physical shield, but this information is recorded in advance in the place relation recording means 124 by a warehouse manager or the like. For example, it is recorded in a format such as a location relation table shown in FIG.

  FIG. 11 shows which section in the warehouse each place belongs to. For example, in the record in the second row, a place whose location ID 1201 is “A” belongs to a section whose section ID 1203 is “1”. It means that In addition, the records whose section ID is “1” are the third and sixth lines, and the place IDs are “B” and “E”, respectively. That is, it can be seen that the places “A”, “B”, and “E” belong to the same space. Next, a method for estimating environmental data will be specifically described. First, a place where environmental data is estimated is determined (S1102). For example, here the location is “E”. Then, based on the information recorded in the location relationship recording means 124, the location around the estimation target location is searched and acquired (S1103). Here, the section ID “1” of the place “E” is acquired first, and then the other places “A” and “B” of the section ID “1” are acquired. One of the peripheral locations acquired in step S1003 is selected, and the reciprocal of the linear distance between the selected peripheral location and the estimation target location is calculated (S1105). In calculating the distance, information on the coordinates 1102 in the place relation table is used. The coordinates 1202 records the local coordinates of the representative point of each place. Here, the representative point may be the center of the place or an arbitrary point related to the place. Therefore, first, the location “A” is designated as the peripheral location. Here, the coordinates of the place “A” are “(10,9)” from the coordinates 1202 on the third line, and the coordinates of the place “E” are “(10,20)” from the coordinates 1202 on the third line. Therefore, the linear distance between the two places is “11”. Further, the latest environment history information of the selected peripheral location is acquired from the environment history recording means 123 shown in FIG. 1 (S1106). Here, the latest environmental history of the place “A” is “21.5” from D702 in the eighth line in FIG.

  Next, the inverse of the distance calculated in the previous step S1105 is multiplied (S1107). This is because the influence of the environmental data in the nearby surrounding places becomes stronger and the influence of the environmental data in the far surrounding places becomes weaker by weighting the environmental data in the surrounding places with the distance. Here, since the distance from the place “E” to the place “A” is “11”, the environmental data “22.7” of the place “A” acquired in step S1106 is multiplied by “1/11” to obtain “2.1”. obtain. Thereafter, the processing from step S1105 to step S1007 is executed for the acquired peripheral place (S1104, S1108). Here, the operation from step 1105 to step S1107 is performed for another peripheral place “B”, and “1.2” is obtained as a result. Then, normalization is performed by summing up the processing results from step S1005 to step S1107 for each peripheral location, and further dividing by the sum of the reciprocal of the distance to each peripheral location (S1109). Therefore, (2.1 + 1.2) / ((1/11) + (1/17)) = 22.9 is obtained here. Based on this calculation result, the environment history recording means 123 is updated as the estimated environment data of the place. Thereafter, the processing from step S1102 to step S1010 is repeatedly executed for each environment data estimation target place (S1101, S1111). Therefore, when the environmental data is estimated by this processing method, it is possible to estimate the environmental data of the place in the same area if there is even one place where the environmental history information is recorded. It becomes.

  Also, as the environmental data estimation means using the environmental data of the adjacent location, for example, the latest environmental history of the place with the closest distance is used as it is, for example, the environmental data before and after the date and time of the place. 1 may be acquired from the environmental data recording unit 120 shown in FIG.

  As described above, the environmental history table recorded in the environmental history recording means 123 is updated after the environmental data for each location is acquired by the processing routine shown in FIG. It is possible to monitor the environment in a plurality of locations without any problem. In addition, when there is a place where the actual measured value of the environmental data cannot be acquired during the environmental history update process, the estimated value of the environmental data is calculated by the processing routine shown in FIGS. To update the environment history.

In the above-described embodiment, it is also possible to perform failure determination of the environmental measurement device by detecting abnormal values of environmental data. FIG. 13 is a flowchart showing a failure determination processing routine. Details of the failure determination means will be described below.
First, the location where the environmental measurement device which is going to perform failure determination exists is determined (S1301). Next, environmental history information related to the location is acquired from the environmental history recording means 123 (S1302), and the information is used as information to be compared. However, when there is only one piece of information to be compared, for example, it is impossible to determine which is an abnormal value, so that the amount of information to be compared requires a certain amount. Therefore, it is determined whether a sufficient amount of environmental history has been acquired as information to be compared (S1303). The criterion for “a sufficient amount as information for comparison” here is defined in advance. When an environmental history having an amount satisfying the criteria in S1303 can be acquired, it is determined whether or not there is an abnormal value by comparing these information and the measured value of the environmental measuring device that is about to perform the failure determination. Is performed (S1305).

  As a method for determining an abnormal value, a method of setting some threshold value or a statistical method such as Smirnov-Graphs test can be applied. Thereafter, the process of step S1305 is executed for the measuring device that currently exists at the location. Thereafter, the ID of the measuring device that measures the abnormal environmental data is presented (S1307). In step S1303, if a sufficient amount of history information cannot be acquired as information to be compared, abnormal value detection is not performed and the failure determination processing routine is terminated.

  Further, in the above-described embodiment, it is possible to detect an error of a timer built in the environmental measurement device. By detecting the error of the timer, the accuracy of environmental measurement can be increased.

  An example of the time error detection process will be described with reference to FIG. FIG. 14 is a flowchart showing a time error detection processing routine for detecting an error of the timer with a built-in measuring device. In this processing example, an environmental measurement device that may have an error in the timer is detected by detecting a temporal error in the environmental measurement value by the environmental measurement device that exists in the detection target space.

  For example, as shown in FIG. 16, the process will be described by taking as an example a case where four temperature sensors exist in a place called “shelf B” between 09:00 and 10:00.

  First, in S1402, “B” is designated as the detection target space. In step S1403, the current time is set as the starting point and the last hour is designated. If the current time is 10:00, then 09:00 to 10:00 are specified. The designated time may not be 1 hour. Then, using the designated place and time as a key, the place data recording means 121, the relational data recording means 122, and the environmental data recording means 120 are used to exist at the place “B” from 09:00 to 10:00. The time series data of the sensor IDs and their measured temperature values are acquired (S1404). This series of processing is equivalent to S804 to S806, and in this example, time series data of measurement values stored in the memory in S815 is used. If time series data of temperature values by two or more sensors can be acquired, a sensor that may cause an error in the timer is detected using these data (S1406). If a sensor that may cause an error in time is detected in S1406, the sensor ID is registered in the error data recording unit 129 (S1407, S1408). Thereafter, S1401 to S1409 are repeated for each detection target space. It is desirable that the detection target spaces have the same environmental measurement values as much as possible, and that a plurality of environmental measurement devices exist in the same space. Therefore, the detection target space may be a place where the same place ID is touched or may include a nearby shelf.

  Next, an example of a method for detecting a sensor that may have an error in time performed in S1406 will be described with reference to FIG.

  First, two sets of time series data are selected from the time series data of the environmental measurement values measured by two or more sensors extracted by the processes of S1402 to S1404, and a polynomial is obtained for each time series data. Is performed (S1501, S1502). However, the fitting function is not limited to a polynomial, and the fitting means is not limited to the least square method. Only one of the two functions obtained above is shifted by a preset time in both positive and negative directions with respect to the time axis. In this case, the interval for shifting at a time is several seconds (S1503). After the shift, the temperature value at intervals of several seconds is calculated using two functions, and the sum of the absolute values of the differences (hereinafter, absolute error) is calculated. The total value and the shifted number of seconds are paired and stored in the memory (S1504).

  The operation is shifted by a preset time and repeated (S1505). After the repetition, a minimum value is selected from the absolute errors recorded in the memory, and it is determined whether or not this value falls below a preset threshold value (S1506). By this processing, it can be determined whether or not the two fitting functions are similar. For example, as shown in the left plot of FIG. 17, when two functions are similar, the minimum absolute error is “a” on the right side of the figure, which is below the threshold. Accordingly, it can be said that the two sensors on the left side of FIG. 17 both normally record the temperature change at the same location. If it is determined that the error between the two functions is small, it is next determined whether or not the time width shifted until the absolute error is minimized exceeds a preset threshold value (S1507). When the shifted time width exceeds the threshold, it can be determined that there is an error in the built-in timer of either sensor. Therefore, both sensor IDs are recorded in the error data recording unit 129 as sensors that may have an error in the timer (S1408). For example, in FIG. 17, since the value “b” exceeds the threshold value in the plot on the right side of the drawing, there is a possibility that an error has occurred in either the timer of S1111 or the sensor of S2222. Accordingly, in S1408, the sensor ID “S1111” and the field sensor ID “S2222” are registered. On the other hand, as in the example of FIG. 18, in the right plot, the value “a” is below the threshold value, but the value “b” is also below the threshold value. It is determined that there is no abnormality in both sections, and nothing is registered in the error data recording means 129. The processes from S1502 to S1508 are repeated while changing the group selection in S1501.

  In addition, as a means for calculating the error between the time series data described above, each time series data is linearly complemented, one time series data is a theoretical value obtained by linear interpolation, the other using the measured value, A method of calculating the absolute difference between them may be used.

  Further, as means for detecting two time series errors, in addition to the above-described calculation of errors of the entire time series data by function fitting or linear interpolation, for example, the occurrence time of the feature point of each time series data The timer error may be detected based on whether or not the time difference exceeds a preset threshold value. The feature point at this time may be, for example, a maximum value or a minimum value, or a point where a change amount in a certain time width exceeds a preset threshold value.

Another example of the time error detection process will be described with reference to FIGS. 20, 21, 22, and 23.
In this detection method, when a measured value such as temperature changes due to some event, the change is propagated to a relatively wide range. In other words, in a place far from a place where a certain event has occurred, the timing of the change in the measured value should be delayed as compared with a close place. Therefore, for example, if the change in the measured value in a place far from the place where the event occurred is confirmed, if the change timing is the same or reversed, the sensor that measured the change in the measured value is Detects that the built-in timer may have an error.

  Hereinafter, a specific example will be described with reference to FIG. The upper diagram in FIG. 23 shows a space in which nine shelves from A to I are arranged in 3 rows and 3 columns. Further, each shelf has one article on which a sensor is installed. Here, for example, it is assumed that an event occurs in which the freezer door near the shelf D is released for a certain period from 09:00. In this case, the temperature change due to this event diffuses isotropically as indicated by a dotted line 2302. Here, the time error detection program starts the time error detection process when the temperature change within a certain period exceeds a preset threshold value.

  This time error detection processing routine is shown in FIGS. In this example, since the temperature change within a certain period of time at the location D quickly exceeded the threshold, the central location of the event is set to “D” and processing is started (S2001). Next, the nearby location of the location “D” is acquired from the location relationship table shown in FIG. 22 as an example of the location relationship recording means 124 (S2003). For example, the record in which the neighboring place of the place “D” is registered is the fifth row, and the first of the neighboring places is the place “A” shown in the column 2202. Similarly, neighboring locations registered in the same record are repeatedly acquired and stored in the memory (S2002 to S2006). In this example, the remaining neighborhood locations are location “E” in column 2203 and location “G” in column 2204. The time error detection process of FIG. 21 is performed on the acquired nearby location. In this processing, any location can be specified when specifying the location of S1402 in the processing example of FIG. 14, whereas when specifying the location of S2102 in the processing example of FIG. The part which designates the location acquired in FIG. 20 and stored in the memory is different.

  The result of comparing the temperature changes at the locations “A”, “E”, and “G” by the above processing is shown as a conceptual diagram on the lower side of FIG. In the lower diagram of FIG. 23, the locations “A”, “E”, and “G” are equidistant from the location “D” that is the central location of the event, and the degree of temperature change and the timing are the same. Therefore, the sensor “S001” existing at the location “A”, the sensor “S005” existing at the location “E”, and the sensor “S007” existing at the location “G” are all error in time. Is determined not to occur.

  Next, using the property that the change in the measured value due to the event propagates through the space, the temperature change is also compared for the places near the places “A”, “E”, and “G”.

  Therefore, as before, the neighboring location of the location “A”, the neighboring location of the location “E”, and the neighboring location of the location “G” are acquired by the processing routine of FIG. However, when acquiring a nearby location, care must be taken to acquire only the nearby location in the event propagation direction. For example, when acquiring a nearby location of the location “A”, the location relationship is acquired from the location relationship recording table of FIG. Therefore, the location “B” can be acquired from the column 2202 in the second row in FIG. 22 and the location “D” can be acquired from the column 2203 in the second column. However, when viewed from the location “A”, the location “D” is not the propagation destination of the event but the propagation source, and thus must be excluded from the target. Therefore, in S2004, the place “D” is excluded from the neighboring places that are the subject of this time, as the place where the event has been propagated previously. As a result of performing the same processing for the places “E” and “G”, the places “B”, “F”, and “H” are set as neighboring places to which events from the places “A”, “E”, and “G” are propagated. Can be acquired. Further, the processing of FIG. 21 is similarly performed on the acquired locations “B”, “F”, and “H”.

  A conceptual diagram of the result is shown in the lower diagram of FIG. In this figure, when the degree of temperature change at the places “B”, “F”, and “H” is compared, it can be seen that the start timing of the temperature change at the place “B” is delayed compared to the places “F” and “H”. . Therefore, it is determined that the sensor “S002” existing at the location “B” may have an error in the timer. If it is determined that an error has occurred, it is registered in the error data recording means 129 as in S1408 of FIG. In this example, the location “B” and the sensor ID “S002” are registered.

  In the above example, the propagation of the event is expressed in a discretized space of nine shelves. However, for example, in a continuous space such as a coordinate value acquired by GPS or the like, the time error due to the same process is represented. A detection method can be applied.

  For example, the upper side of FIG. 24 shows a state where six articles and sensors attached to them exist in a certain space. In this example, it is assumed that the event that the freezer door is released for a certain period from 09:00 occurs at the coordinates (124, 72), and an error occurs in time using the spatial propagation property of this event. An example of sensor detection processing will be described.

  For the discretized space of nine shelves described above, the relationship information between places as shown in FIG. 22 can be described. However, in the continuous space expressed by coordinate values, the relationship information between coordinates is displayed. It is difficult to describe. Therefore, as an example of a method for detecting a time error in a continuous space, an event occurrence place and a detection target place are connected by a straight line, and the environment is set in a place where the shortest distance to the straight line is within a preset threshold. When the measured data exists, the data is compared with the measurement data at the detection target location. In this case, an error in the measurement time is detected depending on whether a reverse phenomenon occurs at the event occurrence time of both data.

  A specific example of this will be described with reference to FIG. In FIG. 24, there is an event that the sensors S0001 to S0006 exist in the space with the upper figure, and the freezer door is released for a certain time at the location of coordinates (124, 72) at time 09:00. Shows the scene. On the other hand, the lower diagram shows the temperature change for one hour at each location from the event occurrence time.

  Here, when the occurrence location of the event is connected to the coordinates (124, 72) and the detection target location is the coordinates (268, 12) with a straight line, the physical distance from the straight line is within the threshold. In the upper diagram of FIG. 24, there are two circles surrounded by a circle: coordinates (165, 59) where the sensor “S005” was present and coordinates (204, 32) where the sensor “S002” was present. is there.

  Looking at the temperature change from 09: 00 to 10:00 in these four places in the lower diagram of FIG. 24, from this temperature change of coordinates (124, 72) that is the place where the event occurred, this place The arrival time of the event is “time a”. The arrival time here is, for example, the time when the temperature change amount in a certain time exceeds a preset threshold value.

  Next, when the temperature change of the coordinates (165, 59) is confirmed, the arrival time of the event at this location is “time b”, which is the coordinates (124, 72) at “time a”. This means that the event that has occurred has reached “time b”, which is slightly delayed from the coordinates (165, 59), which is a distant location, and matches the nature of event propagation.

  Furthermore, looking at the temperature change of the coordinates (204, 32), which is a place farther away from the coordinates (165, 59), the arrival of the event can be confirmed at “time c”, which is further delayed from the time b. It matches the propagation characteristics of the above-mentioned events.

  On the other hand, when looking at the temperature change of the coordinates (268, 12) that are the detection target locations, the arrival time of the event although this location is further from the event occurrence location than the coordinates (204, 32). It can be confirmed that “time d” is earlier than time c. Therefore, there is a possibility that the sensor “S003” measuring the environment at this place has an error in the time of the built-in timer, and this sensor ID is registered in the error data recording means 129.

  As described above, in the method of FIGS. 14 and 21, the error of the built-in timer of the measuring device can be detected by detecting the temporal error of the time series data measured by the environmental measuring device. However, it cannot be determined whether the error of the built-in timer of the measuring device described so far is an error of the environment measuring device 101 or an error of the location data collecting device 107. Therefore, in the time error determination program 130 shown as an example in FIG. 25, it is determined which of the built-in timers of the environment measurement device and the location data measurement device has an error. An example of processing of the time error determination program 130 will be described with reference to FIG.

  When registering the sensor ID in S1408 or S2108, the location ID specified in S1402 or S2102 is registered in addition to the sensor ID. For example, in the description of FIG. 14 described above, the sensor “S1111” and the sensor “S2222” are registered in the error data recording unit 129, but these sensors exist in “B” at the location specified in S1402. Therefore, the sensor ID “S1111” for the location “B” and the sensor ID “S2222” for the location “B” are registered as shown in the second and third rows of the table of FIG.

  Here, as described above, when registering in the error data recording unit 129, there is only a possibility that the registering sensor has an error in the time timer. However, if the possibility has been pointed out more than a certain number of times, it is determined that an error has occurred in the timer of the sensor. Therefore, the record of the sensor is extracted from the error data recording means 129 (S2501). For example, the sensor ID “S1111” record is extracted from the table of FIG. 19 which is the error data recording unit 129. In this case, the extracted record is the second line.

  Here, when the threshold value for determining that an error has occurred in the timer is, for example, that the number of registrations in the error data recording unit 129 is 4 or more, it can be determined that no error has occurred in the timer of the sensor “S1111”. On the other hand, since the sensor “S2222” is registered four times in the third, fifth, eighth, and tenth lines in FIG. 19, it is determined that an error has occurred in the built-in timer of the sensor. I can do it.

  However, it cannot be denied that there is an error in the built-in timer of the location measurement sensor only by the registration number of the sensor ID. In order to solve this problem, the location ID recorded in the 1901 column of FIG. 19 is used. For example, the place where it is determined that an error has occurred in the built-in timer of the sensor “S2222” is the place “B” in the third and fifth lines, but the place “E” and the tenth line in the eighth line. Then, the location “C” is also registered in a different location. In other words, it can be said that the timer error of the sensor is not related to the location measurement sensor.

  Through the above processing, the accuracy of environmental monitoring in a plurality of locations, which is the object of the present invention, is improved by detecting the time error of the timer built in the sensor and determining whether or not the error has occurred. It can be made.

  As mentioned above, although one Embodiment of this invention was described concretely, this invention is not limited to this, A various change is possible in the range which does not deviate from the summary. For example, in the above-described embodiment, an example using a temperature sensor has been described, but a humidity sensor, a suspended particle sensor, or the like may be used as the sensor.

Further, in the above embodiment, the storage operation in the warehouse has been described as an example, but the target scene is the relationship between the article identifier and the article location, the relation between the article identifier and the sensor identifier, and any scene in which environmental data can be collected. It is also applicable to.
In addition to the RFID tag, any tag may be used as long as it is a data carrier holding a unique identifier for identifying an object, such as a barcode tag or a two-dimensional code tag. .

  Further, in the above embodiments, the server has been described as centrally managing related information, route information, and the like. However, even when information and functions are distributed and held, the server is free to perform virtual centralized management. As long as it can be used and referenced, the actual information and functions can be located anywhere.

  According to the present embodiment, it is possible to measure the environment for each place by reducing the number of dedicated environment measuring devices (sensors) as much as possible. For example, as an example, an environmental measurement device such as a temperature sensor, a humidity sensor, an atmospheric pressure sensor, an illuminance sensor, a volume sensor, or a suspended particle amount sensor that is originally attached to an article entering or leaving a place for the purpose of managing the condition of the article By using this, it is possible to realize environmental monitoring in a plurality of locations without installing an environmental measuring device as a dedicated device for each location.

DESCRIPTION OF SYMBOLS 101 Environmental measurement apparatus 102 Environmental measurement means 103 Environmental data transmission means 104 Environmental data collection apparatus 105 Environmental data reception means 106 Environmental data transmission means 107 Location data collection apparatus 108 Positioning means 109 Location data transmission means 110 Network 111 Environmental monitoring apparatus 112 Central processing Processing device 113 Input device 114 Output device 115 Communication device 116 Storage device 117 Location environment estimation program 118 Location environment calculation program 119 Failure detection program 120 Environment data recording means 121 Location data recording means 122 Related data recording means 123 Environment history recording means 124 Location Relation recording means 125 Data registration program 126 Coordinate conversion program 127 Coordinate relation recording means 128 Time error detection program 129 Error data recording means 130 Time error determination Program

Claims (10)

In an environmental monitoring system that collects environmental data at multiple locations using multiple sensors that measure environmental data,
Environmental data recording means for recording history data in which environmental data measured by the plurality of sensors is associated with attribute information including measurement values and measurement dates and times of the environment at the installation position of the sensors;
A location data recording means for detecting a time change of a location due to movement of the sensor or an article in which the sensor is arranged, and recording a location indicating the change, a location period;
The location after the movement is specified from the location data recording means, the sensor that measured the environmental data corresponding to the specified location and the location period of the sensor are specified, and history information at the location of the sensor is stored in the environment. A pre-processing unit that identifies from the data recording means and estimates environmental data based on the identified history information and location period;
An environmental monitoring system comprising: The environmental monitoring system according to claim 1,
The processing unit calculates one representative value from the history information, and estimates the calculated representative value as environmental data of the place at the date and time or within the time,
Environmental monitoring system characterized by The environmental monitoring system according to claim 1 or 2,
The environmental monitoring system, wherein the processing unit estimates environmental data of the place estimated by the processing unit in the past as environmental data at the date and time. The environmental monitoring system according to claim 1 or 2,
The processing unit extracts an environmental measurement value of an environmental condition within a certain range of the date and the similarity from the environmental data measured at the location recorded in the environmental data recording unit, and extracted An environmental monitoring system characterized in that it is estimated as environmental data of the location at the date and time based on environmental measurement values. The environmental monitoring system according to claim 1 or 2,
The environmental monitoring system characterized in that the processing unit estimates environmental data of the location based on environmental data of a sensor installed at a location within a certain range of the location at the date and time. An environment monitoring system according to any one of claims 1 to 5,
The processing unit determines whether the environmental data measured and recorded at the location is a normal value or an abnormal value based on the history information, and measures the environmental measurement value based on the determination result An environmental monitoring system characterized by determining whether or not a failure has occurred. The environment monitoring system according to any one of claims 1 to 6,
The processing unit outputs the environmental data as time-series data, and extracts a plurality of sets of time-series data measured by different environmental measurement devices from the time-series data, and is collected by comparing them with each other. Whether or not there is an error in the built-in timer of the environmental measurement device that measures the time series data of the environmental measurement value by determining whether or not there is a temporal error in the environmental measurement value that is time series data Environmental monitoring system characterized by distinguishing The environmental monitoring system according to claim 7,
The processing unit utilizes the property that an event that changes a physical quantity propagates in space, and extracts and compares time-series data of environmental measurement values at a plurality of physically separated locations from the time-series data. In addition, an error in measurement time is detected by determining whether or not there is a contradiction in the correlation between the property of spatial propagation and a change in physical quantity. The environmental monitoring system according to claim 7,
The processing unit extracts time-series data of local environmental measurement values measured by different measurement devices from the time-series data, and compares the time-series data with each other, thereby measuring time error. Environmental monitoring system characterized by detecting An environment monitoring system according to any one of claims 7 to 9,
The processing unit records an identifier of a measuring device in which an error in measurement time is detected, and determines that an error has occurred in the measurement time of the measuring device having the identifier when the recorded number exceeds a threshold value. Environmental monitoring system characterized by that.

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