Patent Publication Number: US-11034551-B2

Title: Escalator controls data to internet of things

Description:
BACKGROUND 
     The embodiments herein relate to the field of conveyance systems, and specifically to a method and apparatus for monitoring a conveyance apparatus of a conveyance system. 
     A health of a conveyance apparatus within a conveyance systems, such as, for example, elevator systems, escalator systems, and moving walkways may be difficult and/or costly to determine. 
     BRIEF SUMMARY 
     According to an embodiment, a monitoring system for an escalator is provided. The monitoring system including: a local gateway device; an analytic engine in communication with the local gateway device through a cloud computing network; a sensing apparatus in wireless communication with the local gateway device through a short-range wireless protocol, the sensing apparatus including: an inertial measurement unit sensor configured to detect acceleration data of the escalator, wherein at least one of the sensing apparatus and the local gateway device is configured to determine a condition based monitoring (CBM) health score of the escalator in response to at least the acceleration data, and wherein the local gateway is configured wirelessly transmit the CBM health score of the escalator to the cloud computing network in a data package via a long-range wireless communication protocols. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: a microphone configured to detect sound data of the escalator, wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: an application for a computing device in wireless communication with the network, the application being configured to display the CBM health score of the escalator on a display device of the computing device. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the application is configured to display a user input interface for adjusting the CBM health score through a user input. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the data packages are transmitted using MQTT data compression. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is configured to determine the CBM health score of the escalator in response to at least one of the acceleration data and the sound data. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is configured to transmit the acceleration data and the sound data to the local gateway device and the local gateway device is configured to determine the CBM health score of the escalator in response to at least one of the acceleration data and the sound data. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is located within a handrail of the escalator and moves with the handrail. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is attached to a step chain of the escalator and moves with the step chain. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is stationary and located proximate to a step chain of the escalator or a drive machine of the escalator. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus is attached to a moving component of a drive machine of the escalator. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the moving component of the drive machine is an output sheave that drives a step chain of the escalator. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus uses the inertial measurement unit sensor to detect low frequency vibrations less than 10 Hz. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include that the sensing apparatus uses the microphone to detect high frequency vibrations greater than 10 Hz. 
     According to another embodiment, a method of monitoring an escalator is provided. The method including: detecting acceleration data of the escalator using an inertial measurement unit sensor located in a sensing apparatus; determining a condition based monitoring (CBM) health score of the escalator in response to at least the acceleration data; and wirelessly transmitting the CBM health score of the escalator to a cloud computing network in a data package via a long-range wireless communication protocol. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: detecting sound data of the escalator using a microphone located in the sensing apparatus, wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: displaying the CBM health score of the escalator on a display device of a computing device, the computing device being in wireless communication with the network. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: displaying a user input interface for adjusting the CBM health score through a user input using the application for the computing device. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include: receiving a user input to adjust adjusting the CBM health score; and adjusting the CBM health score in response to the user input. 
     In addition to one or more of the features described herein, or as an alternative, further embodiments may include compressing the data package using MQTT data compression. 
     Technical effects of embodiments of the present disclosure include monitoring an escalator using at least one of accelerations and sound to determine a health score and transmitting the health score of the escalator to the cloud computing network in a data package via a long-range wireless communication protocols. 
     The foregoing features and elements may be combined in various combinations without exclusivity, unless expressly indicated otherwise. These features and elements as well as the operation thereof will become more apparent in light of the following description and the accompanying drawings. It should be understood, however, that the following description and drawings are intended to be illustrative and explanatory in nature and non-limiting. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements. 
         FIG. 1  is a schematic illustration of an escalator system and a monitoring system, in accordance with an embodiment of the disclosure; 
         FIG. 2  is a schematic illustration of a sensing apparatus of the monitoring system of  FIG. 1 , in accordance with an embodiment of the disclosure; 
         FIG. 3  is a flow chart of a method of monitoring an escalator, in accordance with an embodiment of the disclosure; and 
         FIG. 4  is an illustration of graphical user interface displaying a condition based monitoring health score of the escalator system, in accordance with an embodiment of the disclosure. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  illustrates an escalator  10 . It should become apparent in the ensuing description that the invention is applicable to other passenger conveyor systems, such as moving walks. The escalator  10  generally includes a truss  12  extending between a lower landing  14  and an upper landing  16 . A plurality of sequentially connected steps or tread plates  18  are connected to a step chain  20  and travel through a closed loop path within the truss  12 . A pair of balustrades  22  includes moving handrails  24 . A drive machine  26 , or drive system, is typically located in a machine space  28  under the upper landing  16 ; however, an additional machine space  28 ′ can be located under the lower landing  14 . The drive machine  26  is configured to drive the tread plates  18  and/or handrails  24  through the step chain  20 . The drive machine  26  operates to move the tread plates  18  in a chosen direction at a desired speed under normal operating conditions. 
     The tread plates  18  make a 180 degree heading change in a turn-around area  19  located under the lower landing  14  and upper landing  16 . The tread plates  18  are pivotally attached to the step chain  20  and follow a closed loop path of the step chain  20 , running from one landing to the other, and back again. 
     The drive machine  26  includes a first drive member  32 , such as motor output sheave, connected to a drive motor  34  through a belt reduction assembly  36  including a second drive member  38 , such as an output sheave, driven by a tension member  39 , such as an output belt. The first drive member  32  in some embodiments is a driving member, and the second drive member  38  is a driven member. 
     As used herein, the first drive member  32  and/or the second drive member, in various embodiments, may be any type of rotational device, such as a sheave, pulley, gear, wheel, sprocket, cog, pinion, etc. The tension member  39 , in various embodiments, can be configured as a chain, belt, cable, ribbon, band, strip, or any other similar device that operatively connects two elements to provide a driving force from one element to another. For example, the tension member  39  may be any type of interconnecting member that extends between and operatively connects the first drive member  32  and a second drive member  38 . In some embodiments, as shown in  FIG. 1 , the first drive member  32  and the second drive member may provide a belt reduction. For example, first drive member  32  may be approximately 75 mm (2.95 inches) in diameter while the second drive member  38  may be approximately 750 mm (29.53 inches) in diameter. The belt reduction, for example, allows the replacement of sheaves to change the speed for 50 or 60 Hz electrical supply power applications, or different step speeds. However, in other embodiments the second drive member  38  may be substantially similar to the first drive member  32 . 
     As noted, the first drive member  32  is driven by drive motor  34  and thus is configured to drive the tension member  39  and the second drive member  38 . In some embodiments the second drive member  38  may be an idle gear or similar device that is driven by the operative connection between the first drive member  32  and the second drive member  38  by means of tension member  39 . The tension member  39  travels around a loop set by the first drive member  32  and the second drive member  38 , which herein after may be referred to as a small loop. The small loop is provided for driving a larger loop which consists of the step chain  20 , and is driven by an output sheave  40 , for example. Under normal operating conditions, the tension member  39  and the step chain  20  move in unison, based upon the speed of movement of the first drive member  32  as driven by the drive motor  34 . 
     The escalator  10  also includes a controller  115  that is in electronic communication with the drive motor  34 . The controller  115  may be located, as shown, in the machine space  28  of the escalator  10  and is configured to control the operation of the escalator  10 . For example, the controller  115  may provide drive signals to the drive motor  34  to control the acceleration, deceleration, stopping, etc. of the tread plates  18  through the step chain  20 . The controller  115  may be an electronic controller including a processor and an associated memory comprising computer-executable instructions that, when executed by the processor, cause the processor to perform various operations. The processor may be, but is not limited to, a single-processor or multi-processor system of any of a wide array of possible architectures, including field programmable gate array (FPGA), central processing unit (CPU), application specific integrated circuits (ASIC), digital signal processor (DSP) or graphics processing unit (GPU) hardware arranged homogenously or heterogeneously. The memory may be but is not limited to a random access memory (RAM), read only memory (ROM), or other electronic, optical, magnetic or any other computer readable medium. 
     Although described herein as a particular escalator drive system and particular components, this is merely exemplary, and those of skill in the art will appreciate that other escalator system configurations may operate with the invention disclosed herein. 
     The elements and components of escalator  10  may suffer from fatigue, wear and tear, or other damage such that diminish health of the escalator  10 . The embodiments disclosed herein seek to provide a monitoring system  200  for the escalator  10  of  FIG. 1 . 
     A monitoring system  200  is illustrated in  FIG. 1 , according to an embodiment of the present disclosure. The monitoring system  200  includes one or more sensing apparatus  210  configured to detect sensor data  202  of the escalator  10 , process the sensor data  202 , and transmit the processed sensor data  202   a  (e.g., a condition based monitoring (CBM) health score  318 ) to a cloud connected analytic engine  280 . Alternatively, the sensor data  202  may be sent raw to at least one of a local gateway device  240  and an analytic engine  280 , where the raw sensor data  202   b  will be processed. The processed sensor data  202   a  may simply be the CBM heath score  318 . 
     The raw sensor data  202   b  and/or the processed sensor data  202   a  may be transmitted in data packages  207  between the local gateway device  240  and the network  250 . The data packages  207  may be transmitted using secure internet protocols (e.g., UDP, TCP) with payload and messaging encryption (e.g., AES  256 ). The data packages  207  may be transmitted in an efficient manor at a selected frequency. For example, the data packages  207  may be transmitted every 2 minutes to establish an uninterrupted connection using a dynamic IP address or a static IP address. The data packages  207  may be transmitted using data compression (e.g., MQTT) to have to have bi-directional communication with network  250 . Information such as, for example, heart beat data, remote (intervention) commands, Over the air updates to firmware may be communicated. Heartbeat data may include information regarding the status of the escalator  10 . Intervention commands may include commands that can be sent to the device to change operation of the device. In embodiment, the data compression is MQTT data compression. 
     Sensor data  202  may include but is not limited to pressure data  314 , vibratory signatures (i.e., vibrations over a period of time) or acceleration data  312 , and sound data  316 . The acceleration data  312  may derivatives or integrals of acceleration data  312  of the escalator  10 , such as, for example, location distance, velocity, jerk, jounce, snap . . . etc. Sensor data  202  may also include light, humidity, and temperature data, or any other desired data parameter. It should be appreciated that, although particular systems are separately defined in the schematic block diagrams, each or any of the systems may be otherwise combined or separated via hardware and/or software. For example, the sensing apparatus  210  may be a single sensor or may be multiple separate sensors. 
     The monitoring system  200  may include one or more sensing apparatus  210  located in various locations of the escalator  10 . In one example, a sensing apparatus  210  may be located attached to or within the handrails  24  and move with the handrails  24 . In another example, a sensing apparatus  210  is stationary and is located proximate the drive machine  26  or step chain  20 . In another example, a sensing apparatus  210  may be attached to the step chain  20  and moving with the moving step chain  20 . In another example, a sensing apparatus  210  may be attached to the tread plate  18  and moving with the tread plate  18 . In another example, a sensing apparatus  210  may be attached to the drive machine  26  and moving relative to the moving step chain  20 . In another embodiment, the sensing apparatus  210  may be attached to a moving component of the drive machine  26 . The moving component of the drive machine  26  may be output sheave  40  that drives a step chain  20  of the escalator  10 . 
     In an embodiment, the sensing apparatus  210  is configured to process the sensor data  202  prior to transmitting the sensor data  202  to the analytic engine  280  through a processing method, such as, for example, edge processing. Advantageously, utilizing edge processing helps save energy by reducing the amount of data that needs to be transferred. In another embodiment, the sensing apparatus  210  is configured to transmit the raw sensor data  202   b  that is raw and unprocessed to an analytic engine  280  for processing. 
     The processing of the sensor data  202  may reveal data, such as, for example, vibrations, vibratory signatures, sounds, temperatures, acceleration of the escalator  10 , deceleration of the escalator, escalator ride performance, emergency stops, etc. 
     The analytic engine  280  may be a computing device, such as, for example, a desktop, a cloud based computer, and/or a cloud based artificial intelligence (AI) computing system. The analytic engine  280  may also be a computing device that is typically carried by a person, such as, for example a smartphone, PDA, smartwatch, tablet, laptop, etc. The analytic engine  280  may also be two separate devices that are synced together, such as, for example, a cellular phone and a desktop computer synced over an internet connection. 
     The analytic engine  280  may be an electronic controller including a processor  282  and an associated memory  284  comprising computer-executable instructions that, when executed by the processor  282 , cause the processor  282  to perform various operations. The processor  282  may be, but is not limited to, a single-processor or multi-processor system of any of a wide array of possible architectures, including field programmable gate array (FPGA), central processing unit (CPU), application specific integrated circuits (ASIC), digital signal processor (DSP) or graphics processing unit (GPU) hardware arranged homogenously or heterogeneously. The memory  284  may be but is not limited to a random access memory (RAM), read only memory (ROM), or other electronic, optical, magnetic or any other computer readable medium. 
     The sensing apparatus  210  is configured to transmit the raw sensor data  202   b  or processed sensor data  202   a  to a local gateway device  240  via short-range wireless protocols  203 . Short-range wireless protocols  203  may include but are not limited to Bluetooth, BLE, Wi-Fi, LoRa, insignu, enOcean, Sigfox, HaLow (801.11ah), zWave, ZigBee, Wireless M-Bus or other short-range wireless protocol known to one of skill in the art. In an embodiment, the local gateway device  240  may utilize message queuing telemetry transport (MQTT or MQTT SN) to communicate with the sensing apparatus  210 . Advantageously, MQTT minimizes network bandwidth and device resource requirements, which helps reduce power consumption amongst the local gateway device  240  and the sensing apparatus  210 , while helping to ensure reliability and message delivery. Using short-range wireless protocols  203 , the sensing apparatus  210  is configured to transmit the sensor data  202  that is raw or processed directly the local gateway device  240  and the local gateway device  240  is configured to transmit the sensor data  202  that is raw or processed to the analytic engine  280  through a network  250  or to the controller  115 . The network  250  may be a computing network, such as, for example, a cloud computing network, cellular network, or any other computing network known to one of skill in the art. Using long-range wireless protocols  204 , the sensing apparatus  210  is configured to transmit the sensor data  202  to the analytic engine  280  through a network  250 . Long-range wireless protocols  204  may include but are not limited to cellular, 3G, 4G, 5G, Cat M1, weightless, LTE (NB-IoT, CAT M1), LoRa, Satellite, Ingenu, or SigFox. The local gateway device  240  may be in communication with the controller  115  through a hardwired and/or wireless connection using short-range wireless protocols  203 . 
     The sensing apparatus  210  may be configured to detect sensor data  202  including acceleration in any number of directions. In an embodiment, the sensing apparatus  210  may detect sensor data  202  including acceleration data  312  along three axis, an X axis, a Y axis, and a Z axis. As illustrated in  FIG. 1 , the X axis and Y axis may form a plane parallel to the tread plate  18  and the Z axis are perpendicular to the tread plate  18 . The Z axis is parallel to the vertical direction or direction of gravity. The X is parallel to the horizontal movement of the tread plates  18 , whereas the Y axis is perpendicular to the horizontal movement of the tread plates  18 . 
     Also shown in  FIG. 1  is a computing device  400 . The computing device  400  may belong to an escalator mechanic/technician working on or monitoring the escalator  10 . The computing device  400  may be a computing device such as a desktop computer or a mobile computing device that is typically carried by a person, such as, for example a smart phone, PDA, smart watch, tablet, laptop, etc. The computing device  400  may include a display device  450  so that the mechanic may visually see a CBM health score  318  of the escalator  10  or sensor data  202 . The computing device  400  may include a processor  420 , memory  410 , a communication module  430 , and an application  440 , as shown in  FIG. 1 . The processor  420  can be any type or combination of computer processors, such as a microprocessor, microcontroller, digital signal processor, application specific integrated circuit, programmable logic device, and/or field programmable gate array. The memory  410  is an example of a non-transitory computer readable storage medium tangibly embodied in the computing device  400  including executable instructions stored therein, for instance, as firmware. The communication module  430  may implement one or more communication protocols, such as, for example, short-range wireless protocols  203  and long-range wireless protocols  204 . The communication module  430  may be in communication with at least one of the controller  115 , the sensing apparatus  210 , the network  250 , and the analytic engine  280 . In an embodiment, the communication module  430  may be in communication with the analytic engine  280  through the network  250 . 
     The communication module  430  is configured to receive a CBM health score  318  and/or sensor data  202  from the network  250 , and the analytic engine  280 . The application  440  is configured to generate a graphical user interface on the computing device  400  to display the CBM health score  318 . The application  440  may be computer software installed directly on the memory  410  of the computing device  400  and/or installed remotely and accessible through the computing device  400  (e.g., software as a service). 
       FIG. 2  illustrates a block diagram of the sensing apparatus  210  of the monitoring system  200  of  FIG. 1 . It should be appreciated that, although particular systems are separately defined in the schematic block diagram of  FIG. 2 , each or any of the systems may be otherwise combined or separated via hardware and/or software. As shown in  FIG. 2 , the sensing apparatus  210  may include a controller  212 , a plurality of sensors  217  in communication with the controller  212 , a communication module  220  in communication with the controller  212 , and a power source  222  electrically connected to the controller  212 . 
     The plurality of sensors  217  includes an inertial measurement unit (IMU) sensor  218  configured to detect sensor data  202  including acceleration data  312  of the sensing apparatus  210  and the escalator  10 . The IMU sensor  218  may be a sensor, such as, for example, an accelerometer, a gyroscope, or a similar sensor known to one of skill in the art. The acceleration data  312  detected by the IMU sensor  218  may include accelerations as well as derivatives or integrals of accelerations, such as, for example, velocity, jerk, jounce, snap . . . etc. The IMU sensor  218  is in communication with the controller  212  of the sensing apparatus  210 . 
     The plurality of sensors  217  includes a pressure sensor  228  configured to detect sensor data  202  including pressure data  314 , such as, for example, atmospheric air pressure proximate the escalator  10 . The pressure sensor  228  may be a pressure altimeter or barometric altimeter in two non-limiting examples. The pressure sensor  228  is in communication with the controller  212 . 
     The plurality of sensors  217  includes a microphone  230  configured to detect sensor data  202  including sound data  316 , such as, for example audible sound and sound levels. The microphone  230  may be a  2 D (e.g., stereo) or  3 D microphone. The microphone  230  is in communication with the controller  212 . 
     The plurality of sensors  217  may also include additional sensors including but not limited to a light sensor  226 , a pressure sensor  228 , a humidity sensor  232 , and a temperature sensor  234 . The light sensor  226  is configured to detect sensor data  202  including light exposure. The light sensor  226  is in communication with the controller  212 . The humidity sensor  232  is configured to detect sensor data  202  including humidity levels. The humidity sensor  232  is in communication with the controller  212 . The temperature sensor  234  is configured to detect sensor data  202  including temperature levels. The temperature sensor  234  is in communication with the controller  212 . 
     The plurality of sensors  217  of the sensing apparatus  210  may be utilized to determine various operating modes of the escalator  10 . Any one of the plurality of sensors  217  may be utilized to determine that the escalator  10  is running. For example, the microphone  230  may detect a characteristic noise indicating that the escalator  10  is running or the IMU sensor  218  may detect a characteristic acceleration indicating that the escalator  10  is running. The pressure sensor  228  may be utilized to determine a running speed of the escalator  10 . For example, if the sensing apparatus  210  is located on the step chain  20  or the tread plate  18 , a continuous or constant air pressure change may indicate movement of the step chain  20  and thus the running speed may be determined in response to the change in air pressure. The IMU sensor  218  may be utilized to determine a height of the escalator  10 . For example, if the sensing apparatus  210  is located on the handrail  24  or the tread plate  18 , a change in direction of velocity (e.g., step is moving up and then suddenly moving down) may indicate that the handrail  24  or tread plate  18  has reached a maximum height. The IMU sensor  218  may be utilized to determine a braking distance of the escalator  10 . For example, if the sensing apparatus  210  is located on the handrail  24 , the step chain  20 , or the tread plate  18 , the second integral of deceleration of the sensing apparatus  210  may be calculated to determine braking distance. Braking distance may be determined from acceleration data  312  indicating an acceleration above threshold to a first zero-crossing of filtered sensor data (integrated speed from measured vibration of the acceleration data  312 ). The IMU sensor  218  may be utilized to determine an occupancy state of the escalator  10 . For example, if the sensing apparatus  210  is located on the step chain  20  or the tread plate  18 , vibrations detected by the sensing apparatus  210  using the IMU sensor  218  may indicate entry of passengers onto the escalator  10  or exit of passengers off the escalator  10 . 
     The controller  212  of the sensing apparatus  210  includes a processor  214  and an associated memory  216  comprising computer-executable instructions that, when executed by the processor  214 , cause the processor  214  to perform various operations, such as, for example, edge pre-processing or processing the sensor data  202  collected by the IMU sensor  218 , the light sensor  226 , the pressure sensor  228 , the microphone  230 , the humidity sensor  232 , and the temperature sensor  234 . In an embodiment, the controller  212  may process the acceleration data  312  and/or the pressure data  314  in order to determine an elevation of the sensing apparatus  210  if the sensing apparatus  210  is on a component that rises or falls during operation of the escalator  10 , such as, for example, on the handrail  24  and step chain  20 . In an embodiment the controller  212  of the sensing apparatus  210  may utilize a Fast Fourier Transform (FFT) algorithm to process the sensor data  202 . 
     The processor  214  may be but is not limited to a single-processor or multi-processor system of any of a wide array of possible architectures, including field programmable gate array (FPGA), central processing unit (CPU), application specific integrated circuits (ASIC), digital signal processor (DSP) or graphics processing unit (GPU) hardware arranged homogenously or heterogeneously. The memory  216  may be a storage device, such as, for example, a random access memory (RAM), read only memory (ROM), or other electronic, optical, magnetic or any other computer readable medium. 
     The power source  222  of the sensing apparatus  210  is configured to store and/or supply electrical power to the sensing apparatus  210 . The power source  222  may include an energy storage system, such as, for example, a battery system, capacitor, or other energy storage system known to one of skill in the art. The power source  222  may also generate electrical power for the sensing apparatus  210 . The power source  222  may also include an energy generation or electricity harvesting system, such as, for example synchronous generator, induction generator, or other type of electrical generator known to one of skill in the art. The power source  222  may also be a hardwired power supply that is hardwired to and receives electricity from an electrical grid and/or the escalator  10 . 
     The sensing apparatus  210  includes a communication module  220  configured to allow the controller  212  of the sensing apparatus  210  to communicate with the local gateway device  240  through short-range wireless protocols  203 . The communication module  220  may be configured to communicate with the local gateway device  240  using short-range wireless protocols  203 , such as, for example, Bluetooth, BLE, Wi-Fi, LoRa, insignu, enOcean, Sigfox, HaLow (801.11ah), zWave, ZigBee, Wireless M-Bus or other short-range wireless protocol known to one of skill in the art. Using short-range wireless protocols  203 , the communication module  220  is configured to transmit the sensor data  202  to a local gateway device  240  and the local gateway device  240  is configured to transmit the sensor data  202  to an analytic engine  280  through a network  250 , as described above. 
     The communication module  220  may also allow a sensing apparatus  210  to communicate with other sensing apparatus  210  either directly through short-range wireless protocols  203  or indirectly through the local gateway device  240  and/or the cloud computing network  250 . Advantageously, this allows the sensing apparatuses  210  to coordinate detection of sensor data  202 . 
     The sensing apparatus  210  includes an elevation determination module  330  configured to determine an elevation or (i.e., height) of a sensing apparatus  210  that is located on a moving component of the escalator  10 , such as for example the tread plate  18 , the step chain  20  and/or the handrail  24 . The elevation determination module  330  may utilize various approaches to determine an elevation or (i.e., height) of the sensing apparatus  210 . The elevation determination module  330  may be configured to determine an elevation of the sensing apparatus  210  using at least one of a pressure elevation determination module  310  and an acceleration elevation determination module  320 . 
     The acceleration elevation determination module  320  is configured to determine a height change of the sensing apparatus in response to the acceleration of the sensing apparatus  210  detected along the Z axis. The sensing apparatus  210  may detect an acceleration along the Z axis shown at  322  and may integrate the acceleration to get a vertical velocity of the sensing apparatus at  324 . At  326 , the sensing apparatus  210  may also integrate the vertical velocity of the sensing apparatus  210  to determine a vertical distance traveled by the sensing apparatus  210  during the acceleration data  312  detected at  322 . The direction of travel of the sensing apparatus  210  may also be determined in response to the acceleration data  312  detected. The elevation determination module  330  may then determine the elevation of the sensing apparatus  210  in response to a starting elevation and a distance traveled away from that starting elevation. The starting elevation may be based upon tracking the past operation and/or movement of the sensing apparatus  210 . Unusual changes in acceleration and/or the velocity of the escalator may indicate poor CBM health score  318 . 
     The pressure elevation determination module  310  is configured to detect an atmospheric air pressure when the sensing apparatus is in motion and/or stationary using the pressure sensor  228 . The pressure detected by the pressure sensor  228  may be associated with an elevation through either a look up table or a calculation of altitude using the barometric pressure change in two non-limiting embodiments. The direction of travel of the sensing apparatus  210  may also be determined in response to the change in pressure detected via the pressure data  314 . For example, the change in the pressure may indicate that the sensing apparatus  210  is either moving up or down. The pressure sensor  228  may need to periodically detect a baseline pressure to account for changes in atmospheric pressure due to local weather conditions. For example, this baseline pressure may need to be detected daily, hourly, or weekly in non-limiting embodiments. In some embodiments, the baseline pressure may be detected whenever the sensing apparatus is stationary, or at certain intervals when the sensing apparatus  210  is stationary and/or at a known elevation. The acceleration of the sensing apparatus  210  may also need to be detected to know when the sensing apparatus  210  is stationary and then when the sensing apparatus  210  is stationary the sensing apparatus  210  may need to be offset to compensate the sensor drift and environment drift. 
     In one embodiment, the pressure elevation determination module  310  may be used to verify and/or modify an elevation of the sensing apparatus  210  determined by the acceleration elevation determination module  320 . In another embodiment, the acceleration elevation determination module  320  may be used to verify and/or modify an elevation of the sensing apparatus determined by the pressure elevation determination module  310 . In another embodiment, the pressure elevation determination module  310  may be prompted to determine an elevation of the sensing apparatus  210  in response to an acceleration detected by the IMU sensor  218 . 
     The health determination module  311  is configured to determine a CBM health score  318  of the escalator  10 . The CBM health score  318  may be associated with a specific component of the escalator  10  or be a CBM health score  318  for the overall escalator  10 . The health determination module  311  may be located in the analytic engine  280 , local gateway device  240 , or the sensing apparatus  210 . In an embodiment, the health determination module  311  is located in the sensing apparatus  210  to perform the edge processing. The health determination module  311  may use a FFT algorithm to process the sensor data  202  to determine a CBM health score  318 . In one embodiment, a health determination module  311  may process at least one of the sound data  316  detected by the microphone  230 , the light detected by the light sensor  226 , the humidity detected by the humidity sensor  232 , the temperature data detected by the temperature sensor  234 , the acceleration data  312  detected by the IMU sensor  218 , and/or the pressure data  314  detected by the pressure sensor  228  in order to determine a CBM health score  318  of the escalator  10 . 
     In an embodiment, the health determination module  311  may process at least one of the sound data  316  detected by the microphone  230  and the acceleration data  312  detected by the IMU sensor  218  to determine a CBM health score  318  of the escalator  10 . 
     Different frequency ranges may be required to detect different types of vibrations in the escalator  10  and different sensors (e.g., microphone, IMU sensor  218 , . . . etc.) of the sensing apparatus  210  may be better suited to detect different frequency ranges. In one example, a vibration in the handrail  24  may consist of a low frequency contribution vibration of less than 5 hz and a higher frequency vibration that is caused on the point where friction in the handrail  24  may be occurring. The low frequency vibration may be best detected using the IMU sensor  218 , whereas the higher frequency vibrations (e.g., in the kHz region) may be best detected using the microphone  230  is more power efficient. Advantageously, using the microphone to detect higher frequency vibrations and the IMU sensor  218  to detect lower frequency vibrations is more energy efficient. In an embodiment, higher frequency may include frequencies that are greater than or equal to 10 Hz. In an embodiment, lower frequency may include frequencies that are less than or equal to 10 Hz. 
     The sensing apparatus  210  may be placed in specific locations to capture vibrations from different components. In an embodiment, the sensing apparatus  210  may be placed in the handrail  24  (i.e., moving with the handrail  24 ). When located in the handrail  24 , the sensing apparatus  210  may utilize the IMU sensors  218  to capture low frequency vibrations. Any variance in the low frequency vibration from a baseline may indicate a low CBM health score  318 . A foreign object (e.g., dirt, dust, pebbles) may get stuck in the handrail  24 , thus leading to increased vibration. In one example, low frequency oscillations may appear because of dust or dirt causing friction. These low frequency oscillations may be identified using a low pass filter of less than 2 Hz. In another example, singles spikes or noise may appear by dirt sticking on tracks or wheels of the step chain  20 . These single spikes or noise may be detected by identifying spikes in vibrations greater than 100 mg. 
     In an embodiment, the sensing apparatus  210  may be attached to (e.g., in or on) the step chain  20  or tread plate  18  (i.e., moving with the step chain  20  or tread plate  18 ). In another embodiment, the sensing apparatus  210  located stationary proximate the drive machine  26 . The temperature sensor  234  may best measure temperature of the drive machine  26  when the sensing apparatus  210  is attached to the drive machine  26 . The IMU sensor  218  may best measure accelerations when the sensing apparatus  210  is attached to the output sheave  40  or tread plate  18 . When attached to the step chain  20  or located stationary proximate the drive machine  26 , the sensing apparatus  210  may utilize the IMU sensors  218  to capture low frequency vibrations that may indicate a bearing problem with a main pivot of the step chain  20 , a step roller of the step chain  20 , or a handrail pivot of the handrail  24 . Alternatively, when attached to the step chain  20  or located stationary proximate the drive machine  26 , the sensing apparatus  210  may utilize the microphone  230  to capture high frequency vibrations that may indicate a bearing problem. A FFT algorithm may be utilized to help analyze the high frequency vibrations captures by the microphone. Advantageously, FFT algorithms use pre-defined special electronic hardware resulting in an easy, low cost, and low power consuming way to detect deviations. When attached to the step chain  20  or located stationary proximate the drive machine  26 , the sensing apparatus  210  may utilize the temperature sensor  234  to measure temperatures. Increasing temperatures may be indicative of increased machine load on the drive machine  26  or increased friction. When attached to the step chain  20 , the sensing apparatus  210  may utilize the IMU sensors  218  to capture accelerations in multiple axis (e.g., X axis, Y axis, and Z axis) to determine tread plate  18  direction (e.g., up or down), a  3 D acceleration profile of the tread plate  18  to determine, amongst other things, when the tread plate  18  is turning, a tread plate  18  misalignment, and bumps in the step chain  20  that may be indicative of foreign objects (dirt, pebbles, dust, . . . etc.) in the step chain  20  or tread plates  18 . The combination of multiple sensor information from different sensors of the plurality of sensors  217  leads to the ability of the sensor fusion within the sensing apparatus, thus allowing the sensors to work in concert to confirm, adjust, or deny data readings. For example, an increase in acceleration values within the acceleration data  312  (at certain frequencies (FFT)) may be associated with an increase in temperature detected by the temperature sensor  234  (e.g., machine heat of the drive machine  26  due to higher load) and an increase in relative humidity detected by the humidity sensor  232  (excluding variations of frictions due to external weather conditions). 
     The CBM health score  318  may be a graded scale indicating the health of the escalator  10  and/or components of the escalator  10 . In a non-limiting example, the CBM health score  318  may be graded on a scale of one-to-ten with a CBM health score  318  equivalent to one being the lowest CBM health score  318  and a CBM health score  318  equivalent to ten being the highest CBM health score  318 . In another non-limiting example, the CBM health score  318  may be graded on a scale of one-to-one-hundred percent with a CBM health score  318  equivalent to one percent being the lowest CBM health score  318  and a CBM health score  318  equivalent to one-hundred percent being the highest CBM health score  318 . In another non-limiting example, the CBM health score  318  may be graded on a scale of colors with a CBM health score  318  equivalent to red being the lowest CBM health score  318  and a CBM health score  318  equivalent to green being the highest CBM health score  318 . The CBM health score  318  may be determined in response to at least one of the acceleration data  312 , the pressure data  314 , and/or the temperature data. For example, acceleration data  312  above a threshold acceleration (e.g., normal operating acceleration) in any one of the X axis, a Y axis, and a Z axis may be indicative of a low CBM health score  318 . In another example, elevated temperature data above a threshold temperature for components may be indicative of a low CBM health score  318 . In another example, elevated sound data  316  above a threshold sound level for components may be indicative of a low CBM health score  318 . 
     Referring now to  FIGS. 3 and 4 , while referencing components of  FIGS. 1-2 .  FIG. 3  shows a flow chart of a method  500  of monitoring an escalator, in accordance with an embodiment of the disclosure. In an embodiment, the method  500  may be performed by at least one of the sensing apparatus  210 , the local gateway device  240 , the application  440 , and the analytic engine  280 . 
     At block  504 , acceleration data  312  of an escalator  10  is detected using an inertial measurement unit sensor  218  located in a sensing apparatus  210 . In one embodiment, the sensing apparatus  210  is located within a handrail  24  of the escalator  10  and moves with the handrail  24 . In another embodiment, the sensing apparatus  210  is attached to a step chain  20  of the escalator  10  and moves with the step chain  20 . In another embodiment, the sensing apparatus  210  is attached to a tread plate  18  of the escalator  10  and moves with the tread plate  18 . In another embodiment, the sensing apparatus  210  is stationary and located proximate to a step chain  20  of the escalator  10  or a drive machine  26  of the escalator  10 . At block  506 , sound data  316  of the escalator  10  is detected using a microphone  230  located in the sensing apparatus  210 . 
     At block  508 , a CBM health score  318  of the escalator  10  is determined in response to at least one of the acceleration data  312  and the sound data  316 . Alternatively, the CBM health score  318  may be determined in response to at least the acceleration data  312 . In one embodiment, the sensing apparatus  210  is configured to determine the operating mode of the escalator  10  in response to at least one of the acceleration data  312  and the sound data  316 . 
     In another embodiment, the acceleration data  312  and the sound data  316  is transmitted to a local gateway device  240  in wireless communication with the sensing apparatus  210  through a short-range wireless protocol  203  and the local gateway device  240  is configured to determine the operating mode of the escalator  10  in response to at least one of the acceleration data  312  and the sound data  316 . 
     In another embodiment, the acceleration data  312  and the sound data  316  is transmitted to a local gateway device  240  in wireless communication with the sensing apparatus  210  through a short-range wireless protocol  203  and the local gateway device  240  transmits the acceleration data  312  and the sound data  316  to an analytic engine  280  through a cloud computing network  250 . The analytic engine  280  is configured to determine the operating mode of the escalator  10  in response to at least one of the acceleration data  312  and the sound data  316 . 
     In an embodiment, low frequency vibrations less than 10 Hz are detected using the inertial measurement unit sensor  218 . In another embodiment high frequency vibrations greater than 10 Hz are using the microphone  230 . In another embodiment, high frequency vibrations are between 10 Hz and 1 kHz. In another embodiment, high frequency vibrations are greater than 1 kHz. 
     At block  510 , the CBM health score of the escalator  10  is wirelessly transmitted to a cloud computing network in a data package  207  via a long-range wireless communication protocol. The method  500  may also comprise that the data package  207  is compressed using MQTT data compression. 
     The method  500  may yet further comprise that CBM health score  318  is displayed on a display device. The display device may be a display device  450  of the computing device  400 , as illustrated in  FIG. 4 . The computing device  400  of FIG.  4  may be belong to an employee or operator of the escalator  10 . The computing device  400  may be a desktop computer, laptop computer, smart phone, tablet computer, smart watch, or any other computing device known to one of skill in the art. In the example shown in  FIG. 4 , the computing device  400  is a touchscreen smart phone. The computing device  400  includes an input device  452 , such as, for example, a mouse, a keyboard, a touch screen, a scroll wheel, a scroll ball, a stylus pen, a microphone, a camera, etc. In the example shown in  FIG. 4 , since the computing device  400  is a touchscreen smart phone, then the display device  450  also functions as an input device  452 .  FIG. 4  illustrates a graphical user interface  470  generated on the display device  450  of the computing device  400 . A user may interact with the graphical user interface  470  through a user input, such as, for example, a “click”, “touch”, verbal command, gesture recognition, or any other input to the graphical user interface  470 . 
       FIG. 4  illustrates a computing device  400  generating a graphical user interface  470  via display device  450  for viewing the CBM health score  318  through the application  440 . The application  440  is configured to display the CBM health score  318  of the escalator  10  on the display device  450  of the computing device  400 . As illustrated in  FIG. 4 , the CBM health score  318  may be displayed as a weighted scale from one-to-ten but it is understood that the CBM health score  318  is not limited to being displayed as a weighted scale from one-to-ten and the CBM health score  318  may be displayed using various other methods. The application  440  is also configured to display a user input interface  718  for adjusting the CBM health score  318  through a user input. As illustrated in  FIG. 4 , the user input interface  718  may be displayed as a weighted scale from one-to-ten that is adjusted by the user input sliding the weighted scale left or right but it is understood that the user input interface  718  is not limited to being displayed as a weighted scale from one-to-ten and the user input interface  718  may be displayed using various other methods. 
     While the above description has described the flow process of  FIG. 3  in a particular order, it should be appreciated that unless otherwise specifically required in the attached claims that the ordering of the steps may be varied. 
     As described above, embodiments can be in the form of processor-implemented processes and devices for practicing those processes, such as processor. Embodiments can also be in the form of computer program code (e.g., computer program product) containing instructions embodied in tangible media (e.g., non-transitory computer readable medium), such as floppy diskettes, CD ROMs, hard drives, or any other non-transitory computer readable medium, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes a device for practicing the embodiments. Embodiments can also be in the form of computer program code, for example, whether stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an device for practicing the exemplary embodiments. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits. 
     The term “about” is intended to include the degree of error associated with measurement of the particular quantity and/or manufacturing tolerances based upon the equipment available at the time of filing the application. 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, element components, and/or groups thereof. 
     Those of skill in the art will appreciate that various example embodiments are shown and described herein, each having certain features in the particular embodiments, but the present disclosure is not thus limited. Rather, the present disclosure can be modified to incorporate any number of variations, alterations, substitutions, combinations, sub-combinations, or equivalent arrangements not heretofore described, but which are commensurate with the scope of the present disclosure. Additionally, while various embodiments of the present disclosure have been described, it is to be understood that aspects of the present disclosure may include only some of the described embodiments. Accordingly, the present disclosure is not to be seen as limited by the foregoing description, but is only limited by the scope of the appended claims.