US-12626581-B2 - System and technique for controlling cleaning behavior and managing prohibited actions interfering with cleanliness in a cleanroom environment

US12626581B2US 12626581 B2US12626581 B2US 12626581B2US-12626581-B2

Abstract

This disclosure is directed to a system for detecting when an individual performs a prohibited action during a cleaning event. A wearable computing device that is worn by an individual performing cleaning in an environment detects movement associated with the wearable device during a cleaning event. One or more processors determines, based at least in part on the movement associated with the wearable computing device detected during the cleaning event, whether the individual has performed a prohibited action during the cleaning event. Responsive to determining that the individual performed the prohibited action during the cleaning event, the one or more processors may perform an operation.

Inventors

Grant Daniel Lindh
Albert Goldfain
Janice Alina Frias
Helen Gates
Alex Robert Pederson
Christopher Moen Flynn

Assignees

ECOLAB USA INC.

Dates

Publication Date: 20260512
Application Date: 20230330

Claims (20)

1 . A method comprising: detecting, by a wearable computing device that is worn by an individual performing cleaning in an environment, movement associated with the wearable device during a cleaning event, wherein the environment comprises a cleanroom segmented into a plurality of areas, each area having a respective assigned cleaning protocol level, wherein detecting the movement associated with the wearable computing device comprises measuring, by at least one sensor of the wearable computing device, movement data; detecting, by one or more sensors external to the wearable computing device, additional data indicative of one or more states of the individual during the cleaning event, wherein the one or more sensors external to the wearable computing device comprise at least one of a door entry logging system and a door exit logging system configured to identify zone transitions by the individual between the plurality of areas; determining, by one or more processors, based on the movement associated with the wearable computing device detected during the cleaning event and the additional data detected by the one or more sensors, whether the individual has performed a prohibited action during the cleaning event, wherein determining whether the individual has performed the prohibited action during the cleaning event comprises: determining at least one signal feature for the movement data, and comparing the at least one signal feature for the movement data to reference signal feature data associated with the prohibited action, wherein the prohibited action comprises traversing the plurality of areas in an order that violates a predefined zone-transition protocol based on one or more of door entry logging data and door exit logging data; and responsive to determining that the individual performed the prohibited action during the cleaning event, performing, by the one or more processors, an operation comprising issuing a user alert to a computing device separate from the wearable computing device indicating the prohibited action.
2 . The method of claim 1 , wherein performing the operation comprises issuing one of an audible, a tactile, and a visual alert via the wearable computing device.
3 . The method of claim 1 , wherein the environment comprises one or more of a cleanroom and one or more ancillary controlled spaces.
4 . The method of claim 1 , further comprising receiving, by the wearable computing device, an indication that the individual performing cleaning has deviated from a planned cleaning protocol during the cleaning event.
5 . The method of claim 1 , further comprising: determining, by the one or more processors and based on the movement associated with the wearable computing device detected during the cleaning event, a risk score for the cleaning event; and responsive to the risk score exceeding the threshold risk score, outputting, by the one or more processors, a fail indication for the cleaning event.
6 . The method of claim 5 , wherein determining the risk score comprises: determining, by the one or more processors, whether the individual performed one or more non-compliant cleaning movements; and responsive to determining that the individual performed the one or more non-compliant cleaning movements, increasing, by the one or more processors, the risk score based on a weighted model and the one or more non-compliant cleaning movements.
7 . The method of claim 6 , wherein the one or more non-compliant cleaning movements comprises one or more of: an improper record of gowning, a non-compliant surface wiping motion, a non-compliant equipment wiping motion, a failure to disinfect during a material transfer, improper hand hygiene, improper wall mopping, improper HEPA vacuuming, an improper paper fold, improper floor mopping, and an improper cleaning spray distribution.
8 . The method of claim 1 wherein the prohibited action comprises one or more of: the individual improperly interacting with their body, the individual improperly contacting a surface in the environment, the individual placing themselves in an improper state, and the individual improperly moving throughout the environment.
9 . The method of claim 1 , wherein the wearable computing device includes the one or more processors.
10 . The method of claim 1 , further comprising: transmitting, by the wearable computing device, movement data to an external computing device in wireless communication with the wearable computing device, wherein the external computing device includes the one or more processors.
11 . The method of claim 1 , further comprising: determining, by the one or more processors, using a model, and based on the movement associated with the wearable computing device and the additional data detected by the one or more sensors, a multi-stream risk score for the individual during the cleaning event.
12 . The method of claim 11 , wherein the model comprises a plurality of weights, each weight corresponding to a potential action detected by one of the wearable computing device or one of the one or more sensors external to the wearable computing device.
13 . The method of claim 1 , wherein the one or more sensors comprise one or more of: a camera system, a pressure sensor system, an audio sensor system, a radio detection and ranging system, a light detection and ranging system, a proximity sensor system, a door entry logging system, a door exit logging system, and a thermal imaging system.
14 . The method of claim 13 , wherein the one or more sensors comprise the camera system, and wherein the additional data comprises one or more of: pose data for the individual during the cleaning event, image data for the individual during the cleaning event, and video data for the individual during the cleaning event.
15 . The method of claim 1 , wherein the additional data is indicative of one or more of: that hair of the individual is exposed, that skin of the individual is exposed, that a position of the individual is improper during the cleaning event, that a form of the individual is improper during the cleaning event, that the individual has touched outside surfaces while gowned, that the individual gowned in an improper order, that a gown worn by the individual is not a correct size, that the gown worn by the individual has an incorrect fit, movement speed, proximity information, occupancy information, and self-sanitation compliance.
16 . The method of claim 1 , wherein the prohibited action comprises one or more of: a movement speed exceeding a threshold movement speed, the individual touching a face while wearing a glove, the individual scratching a body while wearing the glove, the individual bending over, the individual leaning against a wall, the individual placing one or more arms on a countertop, the individual crossing one or more zones in a wrong order, a material transfer without proper sanitation, a cart transfer into a wrong area, a violation of proximity limits, a violation of occupancy limits, entering a space without access permission, and insufficient airlock settling time between instances of a door opening.
17 . The method of claim 1 , further comprising: synchronizing, by the one or more processors, a clock on the wearable device and a clock on the one or more sensors; and interleaving, by the one or more processors, the movement associated with the wearable computing device and the additional data detected by the one or more sensors based on timestamps associated with the movement and timestamps associated with the additional data.
18 . A method comprising: detecting, by a wearable computing device that is worn by an individual performing cleaning in an environment, movement associated with the wearable device during a cleaning event, wherein the environment comprises a cleanroom segmented into a plurality of areas, each area having a respective assigned cleaning protocol level, wherein detecting the movement associated with the wearable computing device comprises measuring, by at least one sensor of the wearable computing device, movement data; detecting, by a camera system external to the wearable computing device, additional data for the individual during the cleaning event, the additional data comprising pose data for the individual during the cleaning event, wherein the camera system external to the wearable computing device comprise at least one of a door entry logging system and a door exit logging system configured to identify zone transitions by the individual between the plurality of areas; determining, by the one or more processors, based on the movement associated with the wearable computing device and the additional data detected by the camera system, whether the individual has performed a prohibited action during the cleaning event, wherein determining whether the individual has performed the prohibited action during the cleaning event comprises: determining at least one signal feature for the movement data, and comparing the at least one signal feature for the movement data to reference signal feature data associated with the prohibited action, wherein the prohibited action comprises traversing the plurality of areas in an order that violates a predefined zone-transition protocol based on one or more of door entry logging data and door exit logging data; and responsive to determining that the individual performed the prohibited action during the cleaning event, performing, by the one or more processors, an operation comprising issuing a user alert to a computing device separate from the wearable computing device indicating the prohibited action.
19 . The method of claim 18 , further comprising: determining, by the one or more processors, using a model, and based on the movement associated with the wearable computing device and the additional data detected by the camera system, a multi-stream risk score for the individual during the cleaning event.
20 . The method of claim 19 , wherein the model comprises a plurality of weights, each weight corresponding to a potential action detected by one of the wearable computing device or the camera system.

Description

RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 63/325,505, filed Mar. 30, 2022, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD This disclosure relates to devices and techniques for managing cleanliness, including monitoring and controlling of cleaning behavior through a wearable computing device and detecting prohibited actions interfering with cleanliness, particularly in a cleanroom environment. BACKGROUND A cleanroom is an engineered space, which maintains a very low concentration of airborne particulates. Cleanrooms are well isolated, well-controlled from contamination, and actively cleansed. Such rooms are commonly needed for scientific research and industrial production, such as for semiconductor manufacturing, pharmaceutical manufacturing, and other highly pure applications. A cleanroom is designed to keep contaminants such as dust, airborne organisms, and vaporized particles outside of the cleanroom environment and away from whatever product is being handled inside the cleanroom. Conversely, a cleanroom can also help keep materials escaping from the cleanroom. For instance, in hazardous biology, nuclear work, pharmaceutics, and virology, cleanroom systems may be utilized to keep hazardous materials contained within the cleanroom. Cleanrooms typically come with a cleanliness level quantified by the number of particles per cubic meter at a predetermined molecule measure. The ambient outdoor air in a typical urban area contains 35,000,000 particles for each cubic meter in the size range 0.5 μm and bigger. By comparison an ISO 14644-1 level 1 certified cleanroom permits no particles in that size range, and just 12 particles for each cubic meter of 0.3 μm and smaller. SUMMARY In general, this disclosure is directed to devices, systems, and techniques for managing hygiene activity by deploying a computing device associated with an individual performing cleaning to track the efficacy of their cleaning actions and detect whether any prohibited actions were performed. The computing device can include one or more sensors that detect and measure cleaning motion associated movement of the computing device caused by movement of the individual, e.g., during a cleaning event. In some examples, the computing device is worn by the individual performing the cleaning, such as at a location between their shoulder and tip of their fingers (e.g., wrist, upper arm). In either case, the computing device can detect movement associated with the individual going about their assigned tasks, which may include movement during cleaning activities as well as interstitial movements between cleaning activities. The movement data generated by the computing device can be analyzed to determine whether the individual performed a prohibited action during the cleaning event. In some configurations, an operation of the computing device is controlled based on the determination of the prohibited action performance. Additionally or alternatively, the efficacy of the cleaning determined can be stored for the cleaning event, providing cleaning validation information for the environment being cleaned. While the devices, systems, and techniques of the disclosure can be implemented in a variety of different environments, in some examples, the technology is utilized in a cleanroom. In general, a cleanroom is an enclosed space that defines a controlled environment where pollutants such as dust, airborne microbes, and aerosol particles are filtered out in order to provide the cleanest area possible. Cleanrooms are typically used for manufacturing products such as electronics, pharmaceutical products, and medical equipment. A cleanroom can be classified into different levels of contamination depending on the amount of particles allowed in the space, per cubic meter. For example, the International Organization for Standardization (ISO) classifies cleanrooms under ISO 14644 with classes ranging from 1 to 9 (class 1, 2, 3, 4, 5, 6, 7, 8, and 9) depending on the number and size of particles permitted in the per volume of air in the cleanroom. Cleanrooms may also control variables like temperature, air flow, and humidity. In practice, the cleanroom and/or equipment in the cleanroom may need to be periodically cleaned to maintain the cleanliness of the room and/or equipment in the room. To do this, one or more individuals may enter the room to perform cleaning. The individual performing cleaning may first put on garments required to enter the cleanroom (e.g., gown, gloves, face mask, booties) before passing through an airlock to enter the cleanroom. The individual may be assigned one more cleaning tasks (e.g., surfaces and/or objects to be cleaned) while inside the cleanroom. While performing those assigned cleaning tasks, the individual may be instructed to avoid certain actions that undermine the cleanliness of the cleanroom. For example, the individual may be instruc