Patent Description:
A precise position 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.

<CIT> discloses a method of setting the floor associations of operating units of an elevator installation, where the operating units are distributed over multiple floors that can be travelled to by an elevator car having a transmitter unit. <CIT> discloses a method for determining an elevator landing table from within an elevator car including obtaining landing information from a position indicator, communicating the landing information from the position indicator, and associating the landing information to a building landing reference to determine a position of the elevator car.

From a first aspect of the invention, a method of monitoring motion of an elevator car within an elevator system as claimed in claim <NUM> is provided.

Further embodiments may include: detecting, using a sensing apparatus, a first pair of corresponding data at a first time, the first pair of corresponding data including a first detected elevator car height at the first time and a first landing corresponding to the first detected elevator car height at the first time; transmitting the first pair of corresponding data to the remote device for processing; and matching, using the remote device, the first pair of corresponding data to one of the correct pairs to determine an actual landing of the elevator car at the first time.

Further embodiments may include: determining, using the remote device, that pairs of corresponding data of the plurality of pairs of corresponding data that do not have a minimum number of hits or visits are incorrect pairs.

Further embodiments may include: determining, using the remote device, that pairs of corresponding data of the plurality of pairs of corresponding data that do not include a landing with a number of reoccurrences above the selected threshold are incorrect pairs.

Further embodiments may include: removing, using the remote device, the incorrect pairs from a landing table generated and stored on the remote device.

Further embodiments may include: saving, using the remote device, the correct pairs in a landing table generated and stored on the remote device.

Further embodiments may include that the sensing apparatus further includes: at least one of a pressure sensor and a inertial measurement sensor, wherein the plurality of pairs of corresponding data are detected using at least one of the pressure sensor and the inertial measurement sensor.

Further embodiments may include that the sensing apparatus further includes: at least one of a temperature sensor and a humidity sensor, wherein the plurality of pairs of corresponding data are detected using at least one of the temperature sensor and the humidity sensor.

Further embodiments may include: normalizing, using a sensing apparatus, at least one of the plurality of pairs of corresponding data within the selected period of time.

From a further aspect of the invention, a computer program product embodied on a non-transitory computer readable medium as claimed in claim <NUM> is provided.

Further embodiments may include that the operations further include: detecting, using a sensing apparatus, a first pair of corresponding data at a first time, the first pair of corresponding data including a first detected elevator car height at the first time and a first landing corresponding to the first detected elevator car height at the first time; transmitting the first pair of corresponding data to the remote device for processing; and matching, using the remote device, the first pair of corresponding data to one of the correct pairs to determine an actual landing of the elevator car at the first time.

Further embodiments may include that the operations further include: determining, using the remote device, that pairs of corresponding data of the plurality of pairs of corresponding data that do not include a landing with a number of reoccurrences above the selected threshold are incorrect pairs.

Further embodiments may include that the operations further include: determining, using the remote device, that pairs of corresponding data of the plurality of pairs of corresponding data that do not have a minimum number of hits or visits are incorrect pairs.

Further embodiments may include that the operations further include: removing, using the remote device, the incorrect pairs from a landing table generated and stored on the remote device.

Technical effects of embodiments of the present disclosure include determining a location of an elevator car through statistical analysis and/or displaying that location of the elevator car via a heat map.

Referring now to <FIG>, with continued referenced to <FIG>, a view of a sensor system <NUM> including a sensing apparatus <NUM> is illustrated, according to an embodiment of the present disclosure. The sensing apparatus <NUM> is configured to detect sensor data <NUM> of the elevator car <NUM> and transmit the sensor data <NUM> to a remote device <NUM>. Sensor data <NUM> may include but is not limited to pressure data <NUM>, vibratory signatures (i.e., vibrations over a period of time) or accelerations <NUM> and derivatives or integrals of accelerations <NUM> of the elevator car <NUM>, such as, for example, distance, velocity, jerk, jounce, snap. etc. Sensor data <NUM> may also include light, sound, humidity, and temperature data <NUM>, or any other desired data parameter. The pressure data <NUM> may include atmospheric air pressure within the elevator shaft <NUM>. 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 <NUM> may be a single sensor or may be multiple separate sensors that are interconnected.

In an embodiment, the sensing apparatus <NUM> is configured to transmit sensor data <NUM> that is raw and unprocessed to the controller <NUM> of the elevator system <NUM> for processing. In another embodiment, the sensing apparatus <NUM> is configured to process the sensor data <NUM> prior to transmitting the sensor data <NUM> to the controller <NUM> through a processing method, such as, for example, edge processing. In another embodiment, the sensing apparatus <NUM> is configured to transmit sensor data <NUM> that is raw and unprocessed to a remote device <NUM> for processing. In yet another embodiment, the sensing apparatus <NUM> is configured to process the sensor data <NUM> prior to transmitting the sensor data <NUM> to the remote device <NUM> through a processing method, such as, for example, edge processing.

The processing of the sensor data <NUM> may reveal data, such as, for example, a number of elevator door openings/closings, elevator door time, vibrations, vibratory signatures, a number of elevator rides, elevator ride performance, elevator flight time, probable car position (e.g. elevation, floor number), releveling events, rollbacks, elevator car <NUM> x, y acceleration at a position: (i.e., rail topology), elevator car <NUM> x, y vibration signatures at a position: (i.e., rail topology), door performance at a landing number, nudging event, vandalism events, emergency stops, etc..

The remote device <NUM> 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 remote device <NUM> 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 remote device <NUM> 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 remote device <NUM> may be an electronic controller including a processor <NUM> and an associated memory <NUM> comprising computer-executable instructions that, when executed by the processor <NUM>, cause the processor <NUM> to perform various operations. The processor <NUM> 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 <NUM> 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 <NUM> is configured to transmit the sensor data <NUM> to the controller <NUM> or the remote device <NUM> via short-range wireless protocols <NUM> and/or long-range wireless protocols <NUM>. Short-range wireless protocols <NUM> may include but are not limited to Bluetooth, BLE, Wi-Fi, HaLow (<NUM>. 11ah), zWave, ZigBee, or Wireless M-Bus. Using short-range wireless protocols <NUM>, the sensing apparatus <NUM> is configured to transmit the sensor data <NUM> directly to the controller <NUM> or to a local gateway device <NUM> and the local gateway device <NUM> is configured to transmit the sensor data <NUM> to the remote device <NUM> through a network <NUM> or to the controller <NUM>. The network <NUM> 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 <NUM>, the sensing apparatus <NUM> is configured to transmit the sensor data <NUM> to the remote device <NUM> through a network <NUM>. Long-range wireless protocols <NUM> may include but are not limited to cellular <NUM>, <NUM>, LTE (NB-IoT, CAT M1), LoRa, Satellite, Ingenu, or SigFox.

The sensing apparatus <NUM> may be configured to detect sensor data <NUM> including acceleration in any number of directions. In an embodiment, the sensing apparatus may detect sensor data <NUM> including accelerations <NUM> along three axis, an X axis, a Y axis, and a Z axis, as show in in <FIG>. The X axis may be perpendicular to the doors <NUM> of the elevator car <NUM>, as shown in <FIG>. The Y axis may be parallel to the doors <NUM> of the elevator car <NUM>, as shown in <FIG>. The Z axis may be aligned vertically parallel with the elevator shaft <NUM> and pull of gravity, as shown in <FIG>. The acceleration data <NUM> may reveal vibratory signatures generated along the X-axis, the Y-axis, and the Z-axis.

The sensor system <NUM> includes a static pressure sensor 228A configured to detect static pressure data 314A, which includes a static atmospheric air pressure. The static pressure sensor 228A is located at a static or stationary location off of the elevator car <NUM>. Thereby, a change in static atmospheric air pressure may be solely caused by the weather and not by movement of the elevator car <NUM>.

The static pressure sensor 228A is configured to transmit the static pressure data 314A to the controller <NUM> or the remote device <NUM> via short-range wireless protocols <NUM> and/or long-range wireless protocols <NUM>. Short-range wireless protocols <NUM> may include but are not limited to Bluetooth, BLE, Wi-Fi, HaLow (<NUM>. 11ah), zWave, ZigBee, or Wireless M-Bus. Using short-range wireless protocols <NUM>, the static pressure sensor 228A is configured to transmit the static pressure data 314A directly to the controller <NUM> or to a local gateway device <NUM> and the local gateway device <NUM> is configured to transmit the static pressure data 314A to the remote device <NUM> through a network <NUM> or to the controller <NUM>. The network <NUM> 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 <NUM>, the static pressure sensor 228A is configured to transmit the static pressure data 314A to the remote device <NUM> through a network <NUM>. Long-range wireless protocols <NUM> may include but are not limited to cellular, <NUM>, <NUM>, LTE (NB-IoT, CAT M1), LoRa, Satellite, Ingenu, or SigFox.

Also shown in <FIG> is a computing device <NUM>. The computing device <NUM> may belong to an elevator mechanic/technician working on the elevator system <NUM>. The computing device <NUM> 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 <NUM> may include a display device <NUM> (see <FIG>) so that the mechanic may visually see a health level (i.e., health score) of the elevator system <NUM>. The computing device <NUM> may include a processor <NUM>, memory <NUM>, a communication module <NUM>, and an application <NUM>, as shown in <FIG>. The processor <NUM> 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 <NUM> is an example of a non-transitory computer readable storage medium tangibly embodied in the computing device <NUM> including executable instructions stored therein, for instance, as firmware. The communication module <NUM> may implement one or more communication protocols, such as, for example, short-range wireless protocols <NUM> and long-range wireless protocols <NUM>. The communication module <NUM> may be in communication with at least one of the controller <NUM>, the sensing apparatus <NUM>, the network <NUM>, and the remote device <NUM>. In an embodiment, the communication module <NUM> may be in communication with the remote device <NUM> through the network <NUM>.

The communication module <NUM> is configured to receive a health level of the elevator system <NUM> from at least one of the controller <NUM>, the sensing apparatus <NUM>, the network <NUM>, and the remote device <NUM>. In an embodiment, the communication module <NUM> is configured to receive a health level from the remote device <NUM>. The remote device <NUM> may generate the health level after receiving sensor date <NUM> from the sensing apparatus <NUM>. The application <NUM> is configured to generate a graphical user interface on the computing device <NUM> (see <FIG>). The application <NUM> may be computer software installed directly on the memory <NUM> of the computing device <NUM> and/or installed remotely and accessible through the computing device <NUM> (e.g., software as a service).

The computing device <NUM> may also include a pressure sensor <NUM> configured to detect an ambient air pressure local to the computing device <NUM>, such as, for example, atmospheric air pressure. The pressure sensor <NUM> may be a pressure altimeter or barometric altimeter in two non-limiting examples. The pressure sensor <NUM> is in communication with the processor <NUM> and the processor <NUM> may be configured to determine a height or elevation of the computing device <NUM> in response to the ambient air pressure detected local to the computing device <NUM>. A height or elevation of the computing device <NUM> may be determined using other location determination methods, including, but not limited to, cell triangulation, a global positioning system (GPS) and/or detection of wireless signal strength (e.g., received signal strength (RSS) using Bluetooth, BLE, Wi-FI,.

<FIG> shows a possible installation location of the sensing apparatus <NUM> within the elevator system <NUM>. The sensing apparatus <NUM> may include a magnet (not show) to removably attach to the elevator car <NUM>. In the illustrated embodiment shown in <FIG>, the sensing apparatus <NUM> may be installed on the door hanger 104a and/or the door <NUM> of the elevator system <NUM>. It is understood that the sensing apparatus <NUM> may also be installed in other locations other than the door hanger 104a and the door <NUM> of the elevator system <NUM>. It is also understood that multiple sensing apparatus <NUM> are illustrated in <FIG> to show various locations of the sensing apparatus <NUM> and the embodiments disclosed herein may include one or more sensing apparatus <NUM>. In another embodiment, the sensing apparatus <NUM> may be attached to a door header 104e of a door <NUM> of the elevator car <NUM>. In another embodiment, the sensing apparatus <NUM> may be located on a door header 104e proximate a top portion 104f of the elevator car <NUM>. In another embodiment, the sensing apparatus <NUM> is installed elsewhere on the elevator car <NUM>, such as, for example, directly on the door <NUM>.

As shown in <FIG>, the sensing apparatus <NUM> may be located on the elevator car <NUM> in the selected areas <NUM>, as shown in <FIG>. The doors <NUM> are operably connected to the door header 104e through a door hanger 104a located proximate a top portion 104b of the door <NUM>. The door hanger 104a includes guide wheels 104c that allow the door <NUM> to slide open and close along a guide rail 104d on the door header 104e. Advantageously, the door hanger 104a is an easy to access area to attach the sensing apparatus <NUM> because the door hanger 104a is accessible when the elevator car <NUM> is at landing <NUM> and the elevator door <NUM> is open. Thus, installation of the sensing apparatus <NUM> is possible without taking special measures to take control over the elevator car <NUM>. For example, the additional safety of an emergency door stop to hold the elevator door <NUM> open is not necessary as door <NUM> opening at landing <NUM> is a normal operation mode. The door hanger 104a also provides ample clearance for the sensing apparatus <NUM> during operation of the elevator car <NUM>, such as, for example, door <NUM> opening and closing. Due to the mounting location of the sensing apparatus <NUM> on the door hanger 104a, the sensing apparatus <NUM> may detect open and close motions (i.e., acceleration) of the door <NUM> of the elevator car <NUM> and a door at the landing <NUM>. Additionally mounting the sensing apparatus <NUM> on the hanger 104a allows for recording of a ride quality of the elevator car <NUM>.

<FIG> illustrates a block diagram of the sensing apparatus <NUM> of the sensing system of <FIG> and <FIG>. It should be appreciated that, although particular systems are separately defined in the schematic block diagram of <FIG>, each or any of the systems may be otherwise combined or separated via hardware and/or software. As shown in <FIG>, the sensing apparatus <NUM> may include a controller <NUM>, a plurality of sensors <NUM> in communication with the controller <NUM>, a communication module <NUM> in communication with the controller <NUM>, and a power source <NUM> electrically connected to the controller <NUM>.

The plurality of sensors <NUM> includes an inertial measurement unit (IMU) sensor <NUM> configured to detect sensor data <NUM> including accelerations <NUM> of the sensing apparatus <NUM> and the elevator car <NUM> when the sensing apparatus <NUM> is attached to the elevator car <NUM>. The IMU sensor <NUM> 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 accelerations <NUM> detected by the IMU sensor <NUM> may include accelerations <NUM> as well as derivatives or integrals of accelerations, such as, for example, velocity, jerk, jounce, snap. etc. The IMU sensor <NUM> is in communication with the controller <NUM> of the sensing apparatus <NUM>.

The plurality of sensors <NUM> includes a pressure sensor <NUM> is configured to detect sensor data <NUM> including pressure data <NUM>, such as, for example, atmospheric air pressure within the elevator shaft <NUM>. The pressure sensor <NUM> may be a pressure altimeter or barometric altimeter in two non-limiting examples. The pressure sensor <NUM> is in communication with the controller <NUM>.

The plurality of sensors <NUM> may also include additional sensors including but not limited to a light sensor <NUM>, a pressure sensor <NUM>, a microphone <NUM>, a humidity sensor <NUM>, and a temperature sensor <NUM>. The light sensor <NUM> is configured to detect sensor data <NUM> including light exposure. The light sensor <NUM> is in communication with the controller <NUM>. The microphone <NUM> is configured to detect sensor data <NUM> including audible sound and sound levels. The microphone <NUM> is in communication with the controller <NUM>. The humidity sensor <NUM> is configured to detect sensor data <NUM> including humidity levels. The humidity sensor <NUM> is in communication with the controller <NUM>. The temperature sensor <NUM> is configured to detect sensor data <NUM> including temperature levels. The temperature sensor <NUM> is in communication with the controller <NUM>.

The controller <NUM> of the sensing apparatus <NUM> includes a processor <NUM> and an associated memory <NUM> comprising computer-executable instructions that, when executed by the processor <NUM>, cause the processor <NUM> to perform various operations, such as, for example, edge pre-processing or processing the sensor data <NUM> collected by the IMU sensor <NUM>, the light sensor <NUM>, the pressure sensor <NUM>, the microphone <NUM>, the humidity sensor <NUM>, and the temperature sensor <NUM>. In an embodiment, the controller <NUM> may process the accelerations <NUM> and/or the pressure data <NUM> in order to determine a probable location of the elevator car <NUM>, discussed further below. The processor <NUM> 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 <NUM> 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 <NUM> of the sensing apparatus <NUM> is configured to store and supply electrical power to the sensing apparatus <NUM>. The power source <NUM> 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 <NUM> may also generate electrical power for the sensing apparatus <NUM>. The power source <NUM> 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 sensing apparatus <NUM> includes a communication module <NUM> configured to allow the controller <NUM> of the sensing apparatus <NUM> to communicate with the remote device <NUM> and/or controller <NUM> through at least one of short-range wireless protocols <NUM> and long-range wireless protocols <NUM>. The communication module <NUM> may be configured to communicate with the remote device <NUM> using short-range wireless protocols <NUM>, such as, for example, Bluetooth, BLE, Wi-Fi, HaLow (<NUM>. 11ah), Wireless M-Bus, zWave, ZigBee, or other short-range wireless protocol known to one of skill in the art. Using short-range wireless protocols <NUM>, the communication module <NUM> is configured to transmit the sensor data <NUM> to a local gateway device <NUM> and the local gateway device <NUM> is configured to transmit the sensor data <NUM> to a remote device <NUM> through a network <NUM>, as described above. The communication module <NUM> may be configured to communicate with the remote device <NUM> using long-range wireless protocols <NUM>, such as for example, cellular, LTE (NB-IoT, CAT M1), LoRa, Ingenu, SigFox, Satellite, or other long-range wireless protocol known to one of skill in the art. Using long-range wireless protocols <NUM>, the communication module <NUM> is configured to transmit the sensor data <NUM> to a remote device <NUM> through a network <NUM>. In an embodiment, the short-range wireless protocol <NUM> is sub GHz Wireless M-Bus. In another embodiment, the long-range wireless protocol is SigFox. In another embodiment, the long-range wireless protocol is LTE NB-IoT or CAT M1 with <NUM>, <NUM> fallback.

The sensing apparatus <NUM> includes a location determination module <NUM> configured to determine a location (i.e., position) of the elevator car <NUM> within the elevator shaft <NUM>. The location of the elevator car <NUM> (i.e., elevator car location) may be fixed locations along the elevator shaft <NUM>, such as for example, the landings <NUM> of the elevator shaft <NUM>. The elevator car locations may be equidistantly spaced apart along the elevator shaft <NUM> such as, for example, <NUM> meters or any other selected distance. Alternatively, the elevator car locations may be or intermittently spaced apart along the elevator shaft <NUM>.

The location determination module <NUM> may utilize various approaches to determine a location of the elevator car <NUM> (i.e., elevator car location) within the elevator shaft <NUM>. The location determination module <NUM> may be configured to determine a location of the elevator car <NUM> within the elevator shaft <NUM> using at least one of a pressure location determination module <NUM> and an acceleration location determination module <NUM>.

The acceleration location determination module <NUM> is configured to determine a distance traveled of the elevator car <NUM> within the elevator shaft <NUM> in response to the acceleration of the elevator car <NUM> detected along the Y axis. The sensing apparatus <NUM> may detect an acceleration along the Y axis shown at <NUM> and may integrate the acceleration to get a velocity of the elevator car <NUM> at <NUM>. At <NUM>, the sensing apparatus <NUM> may also integrate the velocity of the elevator car <NUM> to determine a distance traveled by the elevator car <NUM> within the elevator shaft <NUM> during the acceleration <NUM> detected at <NUM>. The direction of travel of the elevator car <NUM> may also be determined in response to the acceleration <NUM> detected. The location determination module <NUM> may then determine the location of the elevator car <NUM> within the elevator shaft <NUM> in response to a starting location and a distance traveled away from that starting location. The starting location may be based upon tracking the past operation and/or movement of the elevator car <NUM>.

The pressure location determination module <NUM> is configured to detect an atmospheric air pressure within the elevator shaft <NUM> when the elevator car <NUM> is in motion and/or stationary using the pressure sensor <NUM>. The pressure detected by the pressure sensor <NUM> may be associated with a location (e.g., height, elevation) within the elevator shaft <NUM> 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 elevator car <NUM> may also be determined in response to the change in pressure detected via the pressure data <NUM>. The pressure sensor <NUM> 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 elevator car <NUM> is stationary, or at certain intervals when the elevator car <NUM> is stationary and/or at a known location. The acceleration of the elevator car <NUM> may also need to be detected to know when the elevator car <NUM> is stationary and then when the elevator car <NUM> is stationary the sensing apparatus <NUM> may need to be offset to compensate the sensor drift and environment drift.

In one embodiment, the pressure location determination module <NUM> may be used to verify and/or modify a location of the elevator car <NUM> within the elevator shaft <NUM> determined by the acceleration location determination module <NUM>. In another embodiment, the acceleration location determination module <NUM> may be used to verify and/or modify a location of the elevator car <NUM> within the elevator shaft <NUM> determined by the pressure location determination module <NUM>. In another embodiment, the pressure location determination module <NUM> may be prompted to determine a location of the elevator car <NUM> within the elevator shaft <NUM> in response to an acceleration detected by the IMU sensor <NUM>.

In one embodiment, a health determination module <NUM> may process the sound detected by the microphone <NUM>, the light detected by the light sensor <NUM>, the humidity detected by the humidity sensor <NUM>, the temperature data <NUM> detected by the temperature sensor <NUM>, the accelerations <NUM> detected by the IMU sensor <NUM>, and/or the pressure data <NUM> detected by the pressure sensor <NUM> in order to determine a health level (see <FIG>) of the elevator system <NUM>.

The health determination module <NUM> may be located on the remote device <NUM> or the sensing apparatus <NUM>. In an embodiment, the health determination module <NUM> is located on the remote device <NUM>. In an embodiment, the remote device <NUM> may process the sound detected by the microphone <NUM>, the light detected by the light sensor <NUM>, the humidity detected by the humidity sensor <NUM>, the temperature data <NUM> detected by the temperature sensor <NUM>, the accelerations <NUM> detected by the IMU sensor <NUM>, and/or the pressure data <NUM> detected by the pressure sensor <NUM> in order to determine a health level of the elevator system <NUM>. In an embodiment, the remote device <NUM> may process the temperature data <NUM> detected by the temperature sensor <NUM>, the accelerations <NUM> detected by the IMU sensor <NUM>, and the pressure data <NUM> detected by the pressure sensor <NUM> in order to determine a health level of the elevator system <NUM>.

The health level may be a graded scale indicating the health of the elevator system <NUM> and/or components of the elevator system. In a non-limiting example, the health level may be graded on a scale of one-to-ten with a health level equivalent to one being the lowest health level and a health level equivalent to ten being the highest health level. In another non-limiting example, the health level may be graded on a scale of one-to-one-hundred percent with a health level equivalent to one percent being the lowest health level and a health level equivalent to one-hundred percent being the highest health level. In another non-limiting example, the health level may be graded on a scale of colors with a health level equivalent to red being the lowest health level and a health level equivalent to green being the highest health level. The health level may be determined in response to at least one of the accelerations <NUM>, the pressure data <NUM>, and/or the temperature data <NUM>. For example, accelerations <NUM> 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 health level. In another example, elevated temperature data <NUM> above a threshold temperature for components may be indicative of a low health level.

The remote device <NUM> is configured to assign a determined health level to probable locations (e.g., elevator car locations) along the elevator shaft <NUM> where the health level was determined. The probably that the determined health level is existent at a particular location may be display via a heat map as illustrated in <FIG>. The health level may then be communicated to the computing device <NUM> where it is visible to a user of the computing device <NUM>. The health level of the elevator system <NUM> may be determined at various locations along the elevator shaft <NUM>. In one example, the health level of the elevator system <NUM> may be determined equidistantly along the elevator shaft <NUM>. In another example, the health level of the elevator system <NUM> may be determined at each landing <NUM> along the elevator shaft <NUM>.

Referring now to <FIG>, while referencing components of <FIG>. <FIG> shows a flow chart of a method <NUM> of monitoring motion of a conveyance apparatus within a conveyance system, in accordance with an embodiment of the disclosure. In an embodiment, the conveyance system is an elevator system <NUM> and the conveyance apparatus is an elevator car <NUM>. In an embodiment, the method <NUM> may be performed by at least one of the sensing apparatus <NUM>, the controller <NUM>, and the remote device <NUM>.

At block <NUM>, a first atmospheric air pressure is detected proximate the conveyance apparatus at the first time using a pressure sensor <NUM> located on the conveyance apparatus. At block <NUM>, a second atmospheric air pressure is detected proximate the conveyance apparatus at a second time using the pressure sensor <NUM> located on the conveyance apparatus. At block <NUM>, a change in atmospheric air pressure proximate the conveyance apparatus is determined in response to the first atmospheric air pressure and the second atmospheric air pressure. At block <NUM>, a height change of a conveyance apparatus is determined in response to the change in atmospheric air pressure proximate the conveyance apparatus. As the conveyance apparatus changes in height the air pressure also changes, thus by maintaining table comprising a pressure and associated height for that pressure one may determine the height merely by detecting pressure. The standard table may have been developed through testing and/or a learn run. The height change may be confirmed or disconfirmed using at least one of a rate of change in atmospheric air pressure prior to the first time, an acceleration of the conveyance apparatus, a rate of change in static atmospheric air pressure, a rate of change in temperature, and a rate of change in relative humidity detection.

Weather changes that bring changes in local air pressure may provide false readings to the method <NUM>, thus additional parameters may be used to confirm movement of the conveyance apparatus, such as, for example, local weather parameters, temperature, relative humidity, static atmospheric air pressure, or acceleration. Local weather parameters may change along with pressure, such as, for example, temperature and relative humidity. Static pressure is measured at a static or stationary location off of the conveyance apparatus, which moves. Thereby, a change in static atmospheric air pressure may be solely caused by the weather. Thus, the static pressure detected by the static pressure sensor <NUM> may be compared used to correct or normalize the pressure detected by the pressure sensor <NUM>, which may be performed locally in the controller <NUM> and/or in the remote device.

Acceleration may be used to disconfirm movement of the conveyance apparatus by detecting acceleration first, which prompts the controller <NUM> to then detect the first atmospheric air pressure and the second atmospheric air pressure. In other words, detection of acceleration may prompt the pressure sensor <NUM> to beginning detecting pressure. For example, the method <NUM> may further include that an acceleration of the conveyance apparatus is detected and then detection of the first atmospheric air pressure proximate the conveyance apparatus at the first time using a pressure sensor located on the conveyance apparatus is commanded and detection of the second atmospheric air pressure proximate the conveyance apparatus at a second time using the pressure sensor located on the conveyance apparatus is commanded.

If air pressure on conveyance system is constantly measured using a pressure sensor <NUM> on the conveyance apparatus then rates of change in atmospheric air pressure indicating a conveyance apparatus speed that are lower than a threshold speed indicating motion (e.g. <<NUM>/s equivalent ) may be attributed to weather. If this lower speed is detected just prior to the first time in block <NUM> than this lower speed may be used to offset the actual speed detected while in motion. For example, if just prior to the first time the rate of change in atmospheric air pressure indicates a speed of <NUM>/s, which is lower than a threshold speed indicating motion equivalent to <NUM>/s, then once motion is actually detected at a speed of <NUM>/s then the <NUM>/s may be subtracted from the <NUM>/s, thus resulting in <NUM>/s of actual speed. It is understood that <NUM>/s is an example and the numbers may be higher or lower. Height can then be determined using the rate of speed of <NUM>/s and the time traveled. The method <NUM> may further comprise detecting a rate of change in atmospheric air pressure prior to the first time; determining that the conveyance apparatus was not moving prior to the first time in response to the rate of change in atmospheric air pressure prior to the first time; determining a rate of change in atmospheric air pressure between the first time and the second time; and adjusting the height change in response to a difference between the rate of change in atmospheric air pressure prior to the first time and the rate of change in atmospheric air pressure between the first time and the second time.

Static atmospheric air pressure, detected by the static pressure senor 314A may be used to disconfirm movement of the conveyance apparatus. The method <NUM> may further include that a first static atmospheric air pressure proximate the conveyance apparatus is detected at about the first time using a static pressure sensor 228A located off of the conveyance apparatus and a second static atmospheric air pressure proximate the conveyance apparatus at is detected about the second time using the static pressure sensor 228A located off of the conveyance apparatus. The rate of change in static atmospheric air pressure proximate the conveyance apparatus is determined between the first time and the second time in response to the first static atmospheric air pressure, the second static atmospheric air pressure, the first time, and the second time. It may be determined that the rate of change in static atmospheric air pressure is above a threshold static atmospheric air pressure rate of change, which may mean that that the conveyance apparatus has not moved between the first time and the second time. The height change may be disconfirmed in response to determining that the conveyance apparatus has not moved between the first time and the second time. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be confirmed or disconfirmed by the static pressure sensor 228A located off of the conveyance apparatus. For example, if the static pressure sensor 228A detects a pressure change that may be attributed to a weather change, then the pressure change detected by the pressure sensors <NUM> may be adjusted or disconfirmed. Once disconfirmed, the controller <NUM> may reset floor level detection and learning.

Static atmospheric air pressure, detected by the static pressure senor 314A may be used to adjust the height change determined in block <NUM>. The method <NUM> may further include that a first static atmospheric air pressure proximate the conveyance apparatus is detected at about the first time using a static pressure sensor 228A located off of the conveyance apparatus and a second static atmospheric air pressure proximate the conveyance apparatus at is detected about the second time using the static pressure sensor 228A located off of the conveyance apparatus. The rate of change in static atmospheric air pressure proximate the conveyance apparatus is determined between the first time and the second time in response to the first static atmospheric air pressure, the second static atmospheric air pressure, the first time, and the second time. The height change determined in block <NUM> may be adjusted in response to the rate of change in static atmospheric air pressure. For example, the static atmospheric air pressure may be subtracted from the atmospheric air pressure detected by the pressure sensor <NUM>. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be adjusted by the static pressure sensor 228A located off of the conveyance apparatus. For example, if the static pressure sensor 228A detects a pressure change that may be attributed to a weather change while the conveyance apparatus is moving, then the pressure change detected by the pressure sensors <NUM> may be adjusted to remove the pressure change attributed to the weather change, thus leaving only the pressure change attributed to the movement of the conveyance apparatus.

A temperature change typically accompanies a static atmospheric air pressure change, thus detecting a temperature change may be utilized in place of and/or in addition to detecting a change in static atmospheric air pressure. Temperature detected by the temperature sensor <NUM> may be used to disconfirm movement of the conveyance apparatus. The method <NUM> may include that a first temperature proximate the conveyance apparatus is detected at about the first time and a second temperature proximate the conveyance apparatus is detected at about the second time. The rate of change in temperature proximate the conveyance apparatus between the first time and the second time is determined in response to the first temperature, the second temperature, the first time, and the second time. The rate of change in temperature may be determined to be above a threshold temperature rate of change and it may be determined that the conveyance apparatus has not moved between the first time and the second time in response to determining that the rate of change in temperature is above the threshold temperature rate of change. In a non-limiting example, the threshold temperature rate of change can be five degrees Fahrenheit per hour, but it is understood that the threshold temperature rate of change can be greater than or less than five degrees Fahrenheit per hour. Then the height change may be disconfirmed in response to determining that the conveyance apparatus has not moved between the first time and the second time. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be confirmed or disconfirmed by the temperature sensor <NUM>. For example, if the temperature sensor <NUM> detects a temperature change that may be attributed to a weather change while the conveyance apparatus is moving, then the pressure change detected by the pressure sensors <NUM> may be adjusted or disconfirmed.

Temperature detected by the temperature sensor <NUM> may be used to confirm movement of the conveyance apparatus. The method <NUM> may include that a first temperature proximate the conveyance apparatus is detected at about the first time and a second temperature proximate the conveyance apparatus at about the second time. The rate of change in temperature proximate the conveyance apparatus between the first time and the second time is determined in response to the first temperature, the second temperature, the first time, and the second time. The rate of change in temperature may be determined to be below a threshold temperature rate of change and it may be determined that the conveyance apparatus has moved between the first time and the second time in response to determining that the rate of change in temperature is below the threshold temperature rate of change. Then the height change may be confirmed in response to determining that the conveyance apparatus has moved between the first time and the second time. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be confirmed or disconfirmed by the temperature sensor <NUM>. For example, if the temperature sensor <NUM> does not detect a temperature change that may be attributed to a weather change while the conveyance apparatus is moving, then the pressure change detected by the pressure sensors <NUM> may be confirmed.

A change in the relative humidity typically accompanies a static atmospheric air pressure change, thus detecting a change in relative humidity may be utilized in place of and/or in addition to detecting a change in static atmospheric air pressure. Relative humidity detected by the humidity sensor <NUM> may be used to disconfirm movement of the conveyance apparatus. The method <NUM> may include that a first relative humidity proximate the conveyance apparatus is detected at about the first time and a second relative humidity proximate the conveyance apparatus at about the second time. The rate of change in relative humidity proximate the conveyance apparatus between the first time and the second time is determined in response to the first relative humidity, the second relative humidity, the first time, and the second time. The rate of change in relative humidity may be determined to be above a threshold relative humidity rate of change and it may be determined that the conveyance apparatus has not moved between the first time and the second time in response to determining that the rate of change in relative humidity is above the threshold relative humidity rate of change. Then the height change may be disconfirmed in response to determining that the conveyance apparatus has not moved between the first time and the second time. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be confirmed or disconfirmed by the humidity sensor <NUM>. For example, if the humidity sensors <NUM> detects a change in relative humidity that may be attributed to a weather change while the conveyance apparatus is moving, then the pressure change detected by the pressure sensors <NUM> may be adjusted or disconfirmed.

Relative humidity detected by the humidity sensor <NUM> may be used to confirm movement of the conveyance apparatus. The method <NUM> may include that a first relative humidity proximate the conveyance apparatus is detected at about the first time and a second relative humidity proximate the conveyance apparatus at about the second time. The rate of change in relative humidity proximate the conveyance apparatus between the first time and the second time is determined in response to the first relative humidity, the second relative humidity, the first time, and the second time. The rate of change in relative humidity may be determined to be below a threshold relative humidity rate of change and it may be determined that the conveyance apparatus has moved between the first time and the second time in response to determining that the rate of change in relative humidity is below the threshold relative humidity rate of change. Then the height change may be confirmed in response to determining that the conveyance apparatus has moved between the first time and the second time. In other words, the pressure sensor <NUM> located on the conveyance apparatus may detect a pressure change however that pressure change may be confirmed or disconfirmed by the humidity sensor <NUM>. For example, if the humidity sensor <NUM> does not detect a change in relative humidity that may be attributed to a weather change while the conveyance apparatus is moving, then the pressure change detected by the pressure sensors <NUM> may be confirmed.

The method <NUM> may also include that the pressure sensor <NUM> may be utilized to detect the initiation of movement of the conveyance apparatus and then the double integral of acceleration detected by the IMU sensor <NUM> may be utilized to detect the location of the conveyance apparatus within the conveyance system.

Detection of the elevator car location (i.e., height, location, or position) and landings <NUM> visited using an IMU sensor <NUM> (e.g., an acceleration sensor) as well as with a pressure sensor <NUM> has some limitations. The precise landing <NUM> with an associated critical vibration causing a low health score for the elevator system <NUM> may be uncertain due to external air pressure (i.e., weather) changes while the elevator car <NUM> moving. It is important to know the precise landing so that a mechanic may quickly find and fix the critical vibration causing the lower health score. This may result in the landing table generation within the remote device <NUM> being incorrect. The landing table is then utilized by the remote device <NUM> to determine the current elevator car location (i.e., height, location, or position) and landings <NUM>. One method to exclude external air pressure changes from landing table generation is to use edge computing, which is utilized in method <NUM> and <FIG>.

In a second method (e.g., method <NUM> illustrated in <FIG> and method <NUM> illustrated in <FIG>) the correct landing table could be corrected or re-built in the remote device <NUM> when the landing table was generated without edge processing and includes sporadic variable offsets that were caused by external events, such as, for example, external air pressure changes (i.e., weather changes). Method <NUM> depicted in <FIG> and method <NUM> depicted in <FIG> illustrate this second method.

Referring now to <FIG> and <FIG>, while referencing components of <FIG>, <FIG> shows a flow chart of a method <NUM> of monitoring motion of an elevator car <NUM> within an elevator system <NUM>, in accordance with an embodiment of the disclosure. In an embodiment, the method <NUM> may be performed by at least one of the sensing apparatus <NUM>, the controller <NUM>, and the remote device <NUM>.

At block <NUM>, a sensing apparatus <NUM> detects a plurality of pairs of corresponding data within a selected period of time. The selected period of time may be a <NUM> day period in a non-limiting embodiment, but it is understood that the selected period of time may be more or less than a <NUM> day period. Each pair of corresponding data includes a detected elevator car height and a landing corresponding to the detected elevator car height. The landing may be determined based on the height detected. The sensing apparatus <NUM> may further comprises a pressure sensor <NUM> and the plurality of pairs of corresponding data are detected using the pressure sensor <NUM>. The sensing apparatus <NUM> may further comprises an inertial measurement sensor <NUM> and the plurality of pairs of corresponding data are detected using the inertial measurement sensor <NUM>. Also, the sensing apparatus <NUM> may further comprises a combination of the pressure sensor <NUM> and the inertial measurement sensor <NUM>. The sensing apparatus <NUM> may normalize at least one of the plurality of pairs of corresponding data within the selected period of time. The normalization may occur periodically, such as, for example, once a day. It is understood that the normalization may occur more or less than once per day. The normalization may be performed if the internal memory is limited. Thus, a maximum number of landings <NUM> may be detected (e.g.<NUM>) and if the external drift keeps adding new landings <NUM> than the maximum number of landings <NUM> are reached and no new landings <NUM> can be detected. To avoid the sensor this scenario, the sensor is periodically reset to start the first landing <NUM> at <NUM>. Then lower floors added as minus, higher as positive. Then the overall table may corrected so that the lowest floor is <NUM>.

At block <NUM>, the plurality of pairs of corresponding data are transmitted to a remote device <NUM> (e.g., cloud computing device) for processing. At block <NUM>, the remote device <NUM> determines which of the landings of the plurality of pairs of corresponding data have a number of reoccurrences above a selected threshold. The selected threshold <NUM>% or <NUM> sigma in normal distribution, in a non-limiting embodiment. For example, the selected threshold being <NUM>% means that <NUM>% of the data is below a waterline (i.e., the floors higher than all the other floor hits combining to <NUM>%). Additionally, the selected threshold could be the max. number of landings <NUM> if none from independent other source. For example, information entered into system when the mechanic is on site (e.g. via an APP) or detected from the elevator control system <NUM> (e.g. service tool port) see change in <FIG>. It is under stood that the selected threshold may be more or less than <NUM>% or <NUM> sigma.

As illustrated in chart <NUM> of <FIG>, a number of visits or hits <NUM> within a selected time period (e.g., <NUM> days) is shown plotted for each landing <NUM>. The percentage of the total number of hits for each landing is also shown at <NUM>. The landings that have a number of hits above a selected threshold <NUM> may be determined to be correct landing locations. The landings that have a number of hits below the selected threshold <NUM> may be determined to be incorrect landing locations. For example, as shown in <FIG>, landings <NUM>-<NUM> are below the selected threshold <NUM> and thus may not exist because they may have resulted from external drift, as aforementioned. In the instance that an exact number of landings is known the statistics have a precise threshold. In the instance that the number of landings is unknown then "<NUM> sigma" is good statics threshold, but "<NUM> sigma" can be modified with AI, such as, for example, human in the loop feedback about landing level accuracy of this algorithm can help the model learn a correct threshold criteria.

At block <NUM>, the remote device <NUM> determines that pairs of corresponding data of the plurality of pairs of corresponding data are above the selected threshold. The pairs of corresponding data of the plurality of pairs of corresponding data include a landing with a number of reoccurrences above the selected threshold <NUM> are correct pairs. This is performed to narrow down the detected landings <NUM> to the correct landings <NUM>. The remote device <NUM> may save the correct pairs in a landing table generated and stored on the remote device <NUM>. Additionally, the remote device <NUM> may determine that pairs of corresponding data of the plurality of pairs of corresponding data that do not include a landing with a number of reoccurrences above the selected threshold are incorrect pairs. The remote device <NUM> may remove the incorrect pairs from the landing table generated and stored on the remote device <NUM>.

Once the correct landings <NUM> have been identified, then the system may be able to associated newly detected landings with the previously detected landings <NUM> that have been identified as correct. The method <NUM> may further include that the sensing apparatus detects a first pair of corresponding data at a first time. The first time may occur at a first elevator car location. The first pair of corresponding data including a first detected elevator car height at the first time and a first landing corresponding to the first detected elevator car height at the first time. The sensing apparatus <NUM> then transmits the first pair of corresponding data to the remote device <NUM> for processing and the remote device <NUM> matches the first pair of corresponding data to one of the correct pairs to determine an actual landing of the elevator car at the first time.

At block <NUM>, a sensing apparatus <NUM> detects a plurality of pairs of corresponding data <NUM> within a selected period of time. The selected period of time may be a <NUM> day period in a non-limiting embodiment, but it is understood that the selected period of time may be more or less than a <NUM> day period Each pair of corresponding data <NUM> includes a detected elevator car height and a landing corresponding to the detected elevator car height. The landing may be determined based on the height detected. The sensing apparatus <NUM> may further comprises a pressure sensor <NUM> and the plurality of pairs of corresponding data <NUM> are detected using the pressure sensor <NUM>. The sensing apparatus <NUM> may further comprises an inertial measurement sensor <NUM> and the plurality of pairs of corresponding data <NUM> are detected using the inertial measurement sensor <NUM>. The sensing apparatus <NUM> may normalize at least one of the plurality of pairs of corresponding data <NUM> within the selected period of time. The normalization may occur periodically, such as, for example, once a day.

At block <NUM>, the plurality of pairs of corresponding data <NUM> are transmitted to a remote device <NUM> (e.g., cloud computing device) for processing. At block <NUM>, the remote device <NUM> determines which of the plurality of pairs of corresponding data <NUM> have a greatest number of reoccurrences for each landing. As illustrated in chart <NUM> of <FIG>, a number of visits or hits <NUM> within a selected time period (e.g., <NUM> days) is shown plotted for each height <NUM> and each landing <NUM> determined to be at the height <NUM>. Each shape plotted on the chart represents a pair of corresponding data <NUM> and the pairs of corresponding data <NUM> with the most visits or hits <NUM> for each height is determined to be correct. For example, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period, and at a height of <NUM> landing "<NUM>" received the most visits or hits <NUM> within a selected time period.

At block <NUM>, the remote device <NUM> determines that pairs of corresponding data <NUM> of the plurality of pairs of corresponding data <NUM> that have the greatest number of reoccurrences above the selected threshold are correct pairs.

The remote device <NUM> may save the correct pairs in a landing table generated and stored on the remote device <NUM>. Additionally, the remote device <NUM> may determine that pairs of corresponding data <NUM> of the plurality of pairs of corresponding data <NUM> that do not have a minimum number of hits or visits are incorrect pairs. The remote device <NUM> may remove the incorrect pairs from the landing table generated and stored on the remote device <NUM>.

The method <NUM> may further comprise: that the sensing apparatus detects a first pair of corresponding data <NUM> at a first time. The first time may occur at a first elevator car location. The first pair of corresponding data <NUM> including a first detected elevator car height at the first time and a first landing corresponding to the first detected elevator car height at the first time. The sensing apparatus <NUM> then transmits the first pair of corresponding data <NUM> to the remote device <NUM> for processing and the remote device <NUM> matches the first pair of corresponding data <NUM> to one of the correct pairs to determine an actual landing of the elevator car at the first time.

Referring now to <FIG>, with continued reference to <FIG>. <FIG> shows a flow chart of a method <NUM> of monitoring health of an elevator or escalator system <NUM>, in accordance with an embodiment of the present disclosure. <FIG> illustrates a computing device <NUM> generating a graphical user interface <NUM> via display device <NUM> for viewing and interacting with the application <NUM> illustrated in <FIG>. The computing device <NUM> 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>, the computing device <NUM> is a touchscreen smart phone. The computing device <NUM> includes an input device <NUM>, such as, 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>, since the computing device <NUM> is a touchscreen smart phone, then the display device <NUM> also functions as an input device <NUM>. <FIG> illustrates a graphical user interface <NUM> generated on the display device <NUM> of the computing device <NUM>. A user may interact with the graphical user interface <NUM> through a selection input, such as, for example, a "click", "touch", verbal command, gesture recognition, or any other input to the user interface <NUM>.

At block <NUM>, a sensing apparatus detects sensor data <NUM>, the sensor data <NUM> including at least one of an acceleration <NUM> of the elevator car <NUM>, temperature data <NUM> of the elevator system <NUM>, and pressure data <NUM> proximate the elevator car <NUM>.

At block <NUM>, a health level of the elevator system <NUM> is determined in response to at least one of the acceleration <NUM> of the elevator car <NUM>, the temperature data <NUM> of the elevator system <NUM>, and the pressure data <NUM> proximate the elevator car <NUM>.

At block <NUM>, it is determined whether the health level is greater than a selected threshold. At block <NUM>, it is determined that there is a potential health issue <NUM> if the health level is greater than the selected threshold. In an embodiment, the potential health issue may relate to a landing door issue, as illustrated in <FIG>. In an embodiment, the potential health issue may relate to a guide rail of the elevator shaft, as illustrated in <FIG>.

At block <NUM>, one or more possible locations <NUM> are determined for the health level within an elevator shaft <NUM>. The one or more possible locations <NUM> determined at block <NUM> for the health level within an elevator shaft <NUM> by the method <NUM> or method <NUM>.

At block <NUM>, a probability <NUM> of each of the one or more possible locations within the elevator shaft <NUM> is determined. At block <NUM>, displaying the probability <NUM> of the health level being at a plurality of locations throughout an elevator shaft <NUM> on a display device <NUM> of a computing device <NUM>. In an embodiment, the probability <NUM> of the health level being at a plurality of locations throughout an elevator shaft <NUM> on a display device <NUM> of a computing device <NUM> is displayed via a heat map as illustrated in <FIG>. In the heat map warm colors (e.g., red) may represent higher probabilities and cool colors (e.g., green) may represent lower probabilities. In another embodiment, the probability <NUM> of the health level being at a plurality of locations throughout an elevator shaft <NUM> is displayed on a display device <NUM> of a computing device is displayed via a numerical percentage, as illustrated in <FIG>. In another embodiment, the probability <NUM> of the health level being at a plurality of locations throughout an elevator shaft <NUM> on a display device <NUM> of a computing device <NUM> is displayed via a heat map and a numerical percentage, as illustrated in <FIG>.

Claim 1:
A method of monitoring motion of an elevator car (<NUM>) within an elevator system (<NUM>), the method comprising:
detecting, using a sensing apparatus (<NUM>), a plurality of pairs of corresponding data within a selected period of time, each pair of corresponding data including a detected elevator car height and a landing (<NUM>) corresponding to the detected elevator car height;
transmitting the plurality of pairs of corresponding data to a remote device (<NUM>) for processing;
determining, using the remote device (<NUM>), which of the plurality of pairs of corresponding data have a greatest number of reoccurrences for each landing (<NUM>); and
determining, using the remote device (<NUM>), that pairs of corresponding data of the plurality of pairs of corresponding data that have the greatest number of reoccurrences for each landing (<NUM>) are correct pairs.