Office Action 2: Notice of Allowance (2025-06-17)

CLAIMS:
LISTING OF THE CLAIMS

SVG {EMBED HERE} 0.3471.677 l 14, 2025

SVG {EMBED HERE} 0.1231.757
1\. (Currently Amended) A laundry treatment appliance defining a vertical direction, a lateral direction, and a transverse direction, the laundry treatment appliance comprising:
a cabinet defining a receiving space;
a wash tub provided within the receiving space;
a wash basket received within the wash tub; and
a controller provided within the cabinet, the controller being configured to direct a laundry operation, the laundry operation comprising:
receiving a plurality of wash requests from a plurality ofexternal devices associated with a plurality of unique users, wherein each wash request of the plurality of wash requests comprises an image of a unique laundry load and one or more wash parameters corresponding to the uniqjue laundry load;
analyzing, by one or more computing devices using a machine learning image recognition model, a first image to evaluate one or more laundry load characteristics of a first unique laundry load;
analyzing, by the one or more computing devices using the machine learning image recognition model, a second image to evaluate one or more laundry load characteristics of a second unique laundry load;
matching a first unique user and a second unique user from the plurality of unique users, the first uniqjue user and the second uniqjue user having a matching laundry load characteristic from the one or more laundry load characteristics; \[\[and\]\] generating a joint washing cycle comprising one or more wash parameters corresponding to the uniqjue laundry load subsequent to matching the first and second unique users based on the matching laundry load characteristics; and
initiating the joint washing cycle at the laundry treatment appliance according to the one or more wash parameters.

2\. (Currently Amended) The laundry treatment appliance of claim 1, wherein the laundry operation further comprises:
receiving the first unique laundry load within the wash basket;
determining a first unique laundry load size of the first unique laundry load;

Office Action Dated April 14, 2025 receiving the second unique laundry load within the wash basket after determining the first unique laundry load size;anddetermining a second unique laundry load size of the second unique laundry load.
3\. (Original) The laundry treatment appliance of claim 2, wherein determining the first and second unique laundry load sizes comprises:
capturing a first laundry load image of the first unique laundry load;
analyzing, by the one or more computing devices using the machine learning image recognition model, the first laundry load image to determine a first occupied space within the wash basket;
capturing a second laundry load image of the first and second unique laundry loads within the wash basket; and
analyzing, by the one or more computing devices using the machine learning image recognition model, the second laundry load image to determine a second occupied space within the wash basket.
4\. (Currently Amended) The laundry treatment appliance of claim 3, wherein the laundry operation further comprises:
determining a total cost for the joint washing cycle in response to determining the second occupied space within the wash basket.
5\. (Currently Amended) The laundry treatment appliance of claim 4, wherein the laundry operation further comprises:
determining a first individual cost for the first unique user and a second individual cost for the second unique user after determining the total cost of the joint washing cycle;
receiving a confirmation from each of the first and second unique users; and
initiating the joint washing cycle in response to receiving the confirmation from each of the first and second unique users.

Office Action Dated April 14, 2025

6\. (Original) The laundry treatment appliance of claim 3, wherein the first and second laundry load images are captured by a remote camera outside of the wash basket.

7\. (Original) The laundry treatment appliance of claim 1, wherein the machine learning image recognition model comprises at least one of a convolution neural network ("CNN"), a region-based convolution neural network ("R-CNN"), a deep belief network ("DBN"), or a deep neural network ("DNN") image recognition process.

8\. (Currently Amended) The laundry treatment appliance of claim 1, wherein the one or more laundry load characteristics comprises a color of the corresponding unique laundry load.

9\. (Currently Amended) The laundry treatment appliance of claim 8, wherein the laundry operation further comprises:
determining, via image analysis on a first unique image, a first unique laundry load is a first color after receiving the plurality of wash requests; and
concealing the first unique laundry load in the first unique image with a first reference image in response to determining the first unique laundry load is the first color.

10\. (Original) The laundry treatment appliance of claim 9, wherein determining the first unique laundry load is the first color comprises:
determining that at least 80% of the first unique laundry load in the first unique image is not white.

11\. (Currently Amended) A method of operating a laundry treatment appliance, the laundry treatment appliance comprising a wash basket for receiving one or more laundry loads, the method comprising:
receiving a plurality of wash requests from a plurality of external devices associated with a plurality of unique users, wherein each of the wash requests of the plurality of wash requests comprises an image of a unique laundry load;

Office Action Dated April 14, 2025 analyzing, by one or more computing devices using a machine learning image recognition model, a first image to evaluate one or more laundry load characteristics of a first unique laundry load;analyzing, by the one or more computing devices using the machine learning image recognition model, a second image to evaluate one or more laundry load characteristics of a second unique laundry load;
matching a first unique user and a second unique user from the plurality ofunique users, the first unique user and the second unique user having a matching laundry load characteristic from the one or more laundry load characteristics;
determining a first unique laundry load size of the first unique user, the first unique laundry load size being determined within the wash basket;
determining a second unique laundry load size of the second unique user, the second unique laundry load size being determined within the wash basket after determining the first unique laundry load size; \[\[and\]\] generating a joint washing cycle comprising one or more wash parameters corresponding to the first unique laundry load and the second unique laundry load subsequent to determining the first and second laundry load sizes, the joint washing cycle being based on the matching laundry load characteristics; and
initiating the joint washing cycle at the laundry treatment appliance according to the one or more wash parameters.

12\. (Original) The method of claim 11, wherein determining the first and second unique laundry load sizes comprises:
receiving the first unique laundry load within the wash basket;
capturing a first laundry load image of the first unique laundry load;
analyzing, by the one or more computing devices using the machine learning image recognition model, the first laundry load image to determine a first occupied space within the wash basket;
receiving the second unique laundry load within the wash basket after determining the first unique laundry load size;

Office Action Dated April 14, 2025 capturing a second laundry load image of the first and second unique laundry loads within the wash basket; andanalyzing, by the one or more computing devices using the machine learning image recognition model, the second laundry load image to determine a second occupied space within the wash basket.

13\. (Currently Amended) The method of claim 12, wherein the laundry operation further comprises:
determining a total cost for the joint washing cycle in response to determining the second occupied space within the wash basket.

14\. (Currently Amended) The method of claim 13, wherein the laundry operation further comprises:
determining a first individual cost for the first unique user and a second individual cost for the second unique user after determining the total cost of the joint washing cycle;
receiving a confirmation from each of the first and second unique users; and
initiating the joint washing cycle in response to receiving the confirmation from each of the first and second unique users.

15\. (Original) The method of claim 12, wherein the first and second laundry load images are captured by a remote camera outside of the wash basket.

16\. (Original) The method of claim 11, wherein the machine learning image recognition model comprises at least one of a convolution neural network ("CNN"), a region- based convolution neural network ("R-CNN"), a deep belief network ("DBN"), or a deep neural network ("DNN") image recognition process.

17\. (Currently Amended) The method of claim 11, wherein the one or more laundry load characteristics comprises a color of the corresponding unique laundry load.

Office Action Dated April 14, 2025

18\. (Currently Amended) The method of claim 17, wherein the laundry operation further comprises:
determining, via image analysis on a first unique image, a first unique laundry load is a first color after receiving the plurality of wash requests; and
concealing the first unique laundry load in the first unique image with a first reference image in response to determining the first unique laundry load is the first color.

19\. (Original) The method of claim 18, wherein determining the first unique laundry load is the first color comprises:
determining that at least 80% of the first unique laundry load in the first unique image is not white.

OFFICE ACTION:
DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant’s response to the Non-final Office Action dated 04/14/2025, filed with the office on 05/20/2025, has been entered and made of record.
Response to Amendment
In light of Applicant’s amendments, Applicant’s remarks presented in Pages 10-11 of its Reply has been found to be persuasive.  Accordingly, the rejection of record of claims under 35 U.S.C. 101 has been withdrawn.
In light of Applicant’s amendment of the claims 4-5, 8-10, 13-14, and 17-19, the rejections of record under 35 U.S.C. 112(b) for the claims including insufficient antecedent basis have been withdrawn.
Allowable Subject Matter
Claims 1-19 are allowed.  As states in the None-final Office Action, the following is the examiner stated reasons for indication of allowable subject matter:
Hombroek et al (Publication No. US 2022/0195652) discloses a laundry washing machine (Paragraph 0036, 0038) using a controller (Paragraph 0058) for analyzing, using a machine learning model, an image of a laundry load to identify a load characteristic (Paragraph 0141). As well as determining the weight of the load.
Beveal et al (US Patent No. 10,466,665) discloses the use of a laundry machine by multiple users and splitting the payment between the multiple users (Col 25 lines 11-21) and ability to alter pricing depending on multiple factors (Col 29 lines 4-10).
Carobene et al (EP 3751454 A1) discloses determining weight and size of laundry loads, as well as determining the color characteristics of the load.
Liz Stinson discloses connecting unique users to do laundry via an app and using the app for user confirmation and payment.
Cha et al (Publication No. US 2021/0062397) discloses the use of different machine learning models for image recognition.
However, when the closest prior art of record is taken in combination, they fail to teach or suggest the invention of claim 1 and 11. At best, the references of record would provide a laundry appliance where the color and weight of individual laundry loads can be determines as well determining the cost of that load. The reference of record would not provide the laundry of two or more unique users within the same wash tub/basket.
Accordingly the references of record do not teach the ordered combination of the limitations of the independent claims: “A laundry treatment appliance defining a vertical direction, a lateral direction, and a transverse direction, the laundry treatment appliance comprising: a cabinet defining a receiving space; a wash tub provided within the receiving space; a wash basket received within the wash tub; and a controller provided within the cabinet, the controller being configured to direct a laundry operation, the laundry operation comprising: receiving a plurality of wash requests from a plurality of external devices associated with a plurality of unique users, wherein each wash request of the plurality of wash requests comprises an image of a unique laundry load and one or more wash parameters corresponding to the unique laundry load; analyzing, by one or more computing devices using a machine learning image recognition model, a first image to evaluate one or more laundry load characteristics of a first unique laundry load; analyzing, by the one or more computing devices using the machine learning image recognition model, a second image to evaluate one or more laundry load characteristics of a second unique laundry load; matching a first unique user and a second unique user from the plurality of unique users, the first unique user and the second unique user having a matching laundry load characteristic from the one or more laundry load characteristics; generating a joint washing cycle comprising one or more wash parameters corresponding to the unique laundry load subsequent to matching the first and second unique users based on the matching laundry load characteristics; and initiating the joint washing cycle at the laundry treatment appliance according to the one or more wash parameters.”
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion

APPLICANT REBUTTAL: REMARKSApplicant respectfully requests reconsideration and allowance in view of this Response.No new matter is introduced by this Response.I.    Statement of the Interview Applicant thanks Examiner Kaur for the courtesies extended during the telephone interview on May 13, 2025. During the interview, Examiner Kaur and Applicant's representative discussed the claimed subject matter, the Office Action, and possible suggestions to further emphasize patent eligible, novel, and non-obvious features of the claimed subject matter.II.   Objections to the Specification The Office Action objected to the specification. Without acquiescing to or otherwise commenting on the merits of the objections, Applicant has amended the specification in the interest of advancing prosecution. Applicant submits that the specification as pending is proper and requests that the objections be withdrawn.III. Rejections under 35 U.S.C. § 112 Without acquiescing to or otherwise commenting on the merits of the rejection, Applicant has amended the claims in the interest of advancing prosecution. Applicant submits that the pending claims satisfy the requirements of § 112 and requests that the rejections under § 112 be withdrawn.IV.   Rejections under 35 U.S.C. § 101 Claims 1-19 were rejected under 35 U.S.C. § 101 for allegedly being directed to a judicial exception without significantly more.Without acquiescing to or otherwise commenting on the merits of the rejection, Applicant has amended the claims in the interest of advancing prosecution. For at least the following reasons, Applicant submits that the pending claims are patent eligible and requests that the rejections under § 101 be withdrawn.A.    Independent Claim 1 Claim 1 recites a laundry treatment appliance including a controller configured to direct a laundry operation, the laundry operation includes, inter alia, receiving a plurality of wash requests from a plurality of external devices associated with a plurality of unique users, wherein each wash request of the plurality of wash requests comprises an image of a unique laundry load and one or more wash parameters corresponding to the unique laundry load; generating a joint washing cycle comprising one or more wash parameters corresponding to the unique laundry loads subsequent to matching the first and second unique users based on the matching laundry load characteristics; and initiating the joint washing cycle at the laundry treatment appliance according to the one or more wash parameters. Even if the independent claim 1 was directed to an abstract idea (which Applicant respectfully submits it is not), Applicant respectfully submits that the limitations presented above integrate any alleged judicial exception into a practical application. For at least this reason, Applicant submits that claim 1 is patent eligible.B.    Independent Claim 11 For at least the reasons discussed above with respect to claim 1, Applicant submits that claim 11 is also patent eligible.C.    Dependent Claims For at least the reasons discussed above with respect to the above independent claims, Applicant submits that the claims respectively dependent thereon are also patent eligible.Applicant also notes that the patentability of the dependent claims certainly does not hinge on the patentability of independent claims. Some or all of these claims may possess features that are independently patentable, regardless of the patentability of the independent claims.V.    Allowable Subject Matter Applicant wishes to thank the Examiner for indicating that claims 1-19 include allowable subject matter.VI.   Conclusion Applicant respectfully submits that the pending claims are patentable for at least the reasons set forth above. As such, it is believed that the present application is in complete condition for allowance. Applicant requests entry of this Response followed by allowance of the application. Examiner Kaur is invited and encouraged to telephone the undersigned, however, if any issues remain after consideration of this Response.Please charge any additional fees required by this Response to the above-captioned Deposit Account.Respectfully submitted, DORITY & MANNING, P.A.May 20, 2025


CITED REFERENCE SUMMARIES: Ref US20220195652: Claims:
1. A laundry washing machine, comprising:
a wash tub disposed within a housing; a color detection sensor positioned to capture color composition data of a load of articles as the load of articles is added to the wash tub; a weight sensor operatively coupled to the wash tub to sense a weight of the load of articles as the load of articles is added to the wash tub; and a controller coupled to the color detection sensor and the weight sensor and configured to initiate a plurality of color composition data captures with the color detection sensor responsive to detected weight changes sensed by the weight sensor as the load of articles is added to the wash tub, the controller configured to initiate each color composition data capture in response at least in part to the weight sensor detecting a stable weight in the wash tub for at least a predetermined duration; wherein the controller is further configured to set one or more operational settings for a wash cycle based upon the plurality of color composition data captures.
2. The laundry washing machine of claim 1, wherein the controller is configured to detect the stable weight for at least the predetermined duration by determining that a weight change sensed by the weight sensor during the predetermined duration is less than a stability weight constant.
3. The laundry washing machine of claim 2, wherein the controller is configured to detect the stable weight for at least the predetermined duration by starting a stability timer when a weight change subsequent to a prior composition data capture is greater than an article addition weight constant.
4. The laundry washing machine of claim 3, wherein the controller is configured to store a stability weight in connection with starting the stability timer and reset the stability timer if and the stability weight if the weight change sensed by the weight sensor during the predetermined duration exceeds the stability weight constant.
5. The laundry washing machine of claim 4, wherein the controller is configured to initiate a color composition data capture in response to the stability timer reaching the predetermined duration.
6. The laundry washing machine of claim 1, wherein the controller is further configured to detect removal of an article from the wash tub using the weight sensor and delete a color composition data capture in response to detecting removal of the article.
7. The laundry washing machine of claim 1, wherein the controller is further configured to initiate each color composition data capture in response at least in part to detection of image stability in the wash tub.
8. The laundry washing machine of claim 1, wherein the controller is configured to initiate the plurality of color composition data captures in response to detecting an open door, and to determine that all articles in the load have been added to the wash tub in response to detecting a closed door.
9. The laundry washing machine of claim 8, wherein the controller is configured to initiate an additional capture of color composition data after detecting the closed door, and to delete the additional capture of color composition data if a weight change sensed by the weight sensor is less than a predetermined constant.
10. The laundry washing machine of claim 8, wherein the controller is further configured to initiate a capture of an additional color composition data capture after detecting the closed door in response to detecting that the door has been reopened and that the weight sensor has detected another article added to the wash tub.
11. The laundry washing machine of claim 8, wherein the controller is configured to start a sleep timer in response to detecting the open door, to reset the sleep timer in connection with each color composition data capture, to put the laundry washing machine in a sleep state in response to expiration of the sleep timer, and to awaken the laundry washing machine and initiate a color composition data capture in response to detection of a weight change by the weight sensor while the laundry washing machine is in the sleep state.
12. The laundry washing machine of claim 1, wherein the color detection sensor comprises an image sensor configured to capture a digital image, and wherein the laundry washing machine further comprises a light positioned to illuminate the wash tub during image capture with the image sensor.
13. The laundry washing machine of claim 1, wherein the controller is further configured to initiate a color decision algorithm to characterize the captured color composition data by assigning each of a plurality of pixels in the captured color composition data to one of a plurality of color categories, and to characterize the load of articles based upon the characterized color compensation data, and to set one or more operational settings for a wash cycle based upon the characterization of the load of articles by the color decision algorithm.
14. A laundry washing machine, comprising:
a wash tub disposed within a housing; a color detection sensor positioned to capture color composition data of a load of articles as the load of articles is added to the wash tub; and a controller coupled to the color detection sensor and configured to initiate the capture of the color composition data with the color detection sensor as the load of articles is added to the wash tub, the controller further configured to initiate a color decision algorithm to characterize the captured color composition data by assigning each of a plurality of pixels in the captured color composition data to one of a plurality of color categories, and to characterize the load of articles based upon the characterized color compensation data; wherein the controller is further configured to set one or more operational settings for a wash cycle based upon the characterization of the load of articles by the color decision algorithm.
15. The laundry washing machine of claim 14, wherein the controller is configured to initiate the color decision algorithm by executing at least a portion of the color decision algorithm.
16. The laundry washing machine of claim 14, wherein the controller is configured to initiate the color decision algorithm by communicating data from the plurality of color composition data captures to a remote device that executes at portion of the color decision algorithm, and wherein the controller is further configured to receive result data associated with the color decision algorithm from the remote device.
17. The laundry washing machine of claim 14, wherein the color decision algorithm is configured to assign each of the plurality of pixels in the captured color composition data to one of the plurality of color categories by comparing color data for each pixel against a plurality of thresholds associated with the plurality of color categories.
18. The laundry washing machine of claim 14, wherein the color decision algorithm is configured to determine a number of pixels in the captured color composition data that are assigned to each of the plurality of color categories, and to characterize the load of articles based upon the determined numbers of pixels.
19. The laundry washing machine of claim 18, wherein the color decision algorithm is configured to characterize the load of articles based upon the determined numbers of pixels by comparing the determined numbers of pixels against thresholds associated with one or more of the plurality of color categories.
20. The laundry washing machine of claim 19, wherein the plurality of color categories to which the pixels are assigned includes a whites color category, a lights color category, and a darks color category, and wherein the color decision algorithm is configured to characterize the load of articles based upon the determined numbers of pixels by:
characterizing the load of articles as a whites load in response to a majority of the determined numbers of pixels being assigned to the whites color category and the determined number of pixels assigned to the whites color category meeting a whites threshold; characterizing the load of articles as a lights load in response to a majority of the determined numbers of pixels being assigned to the lights color category and the determined number of pixels assigned to the lights color category meeting a lights threshold; and characterizing the load of articles as a darks load in response to a majority of the determined numbers of pixels being assigned to the darks color category and the determined number of pixels assigned to the darks color category meeting a darks threshold.
21. The laundry washing machine of claim 20, wherein the plurality of color categories further includes a reds color category, and wherein the color decision algorithm is further configured to characterize the load of articles as a reds load in response to the determined number of pixels assigned to the reds color category meeting a reds threshold.
22. A method of operating a laundry washing machine, the method comprising:
capturing color composition data of a load of articles as the load of articles is added to a wash tub using a color detection sensor; sensing a weight of the load of articles as the load of articles is added to the wash tub using a weight sensor operatively coupled to the wash tub; initiating a plurality of color composition data captures with the color detection sensor responsive to detected weight changes sensed by the weight sensor as the load of articles is added to the wash tub, wherein each color composition data capture is initiated in response to the weight sensor detecting a stable weight in the wash tub for at least a predetermined duration; initiating a color decision algorithm to characterize the captured color composition data by assigning each of a plurality of pixels in the captured color composition data to one of a plurality of color categories, and to characterize the load of articles based upon the characterized color compensation data; and setting one or more operational settings for a wash cycle based upon the plurality of color composition data captures.
Ref US10466665: Claims:
1. A system comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor, the memory storing instructions which, when executed, instruct the at least one processor to perform operations comprising:
receiving a request for use of a laundry machine that is one of multiple laundry machines in a vicinity of a mobile computing device, the request sent by the mobile computing device responsive to a determination that the mobile computing device is in proximity to the laundry machine, wherein a wireless network interface of the mobile computing device receives a beacon signal that is emitted from each of the multiple laundry machines, wherein the determination that the mobile computing device is in proximity to the laundry machine is based on: i) a received signal level of the beacon signal from the laundry machine having at least a strength that corresponds to a threshold distance between the mobile computing device and the laundry machine, and ii) the received signal level of the beacon signal from the laundry machine being stronger than a respective signal level of each of the other beacon signals from the other laundry machines in the vicinity, wherein the beacon signal includes an identifier of the laundry machine that uniquely identifies the laundry machine among the multiple laundry machines, wherein the identifier included in the beacon signal changes periodically, and wherein the identifier is included in the request, sent by the mobile computing device, for use of the laundry machine;
determining a network address of the laundry machine indicated in the request; and
sending a control signal to the network address of the laundry machine, wherein the control signal causes an altering of an operational state of the laundry machine to enable use of the laundry machine during a period of time.
2. The system of claim 1, wherein the threshold distance is previously determined based on a calibration to measure distance versus signal level for a transmitted power of the beacon signal.
3. The system of claim 1, wherein the request includes a code that identifies the laundry machine and that is presented on or in proximity to the laundry machine, and wherein the code is presented in a scannable barcode of at least one dimension.
4. The system of claim 1, the operations further comprising:
receiving an availability request for availability information describing currently available laundry machines, the availability request indicating a location of one or more of a user or the mobile computing device;
in response to the availability request, identifying one or more laundromats within a threshold distance of the location, the one or more laundromats including one or more currently available laundry machines; and
sending, in response to the availability request, the availability information indicating the one or more laundromats that include the one or more currently available laundry machines.
5. The system of claim 4, the operations further comprising:
receiving a reservation request for a reservation of at least one laundry machine at a particular laundromat of the one or more laundromats, the reservation request sent in response to a selection of the particular laundromat from the one or more laundromats, the selection made through a user interface (UI);
updating status information to indicate the at least one laundry machine as reserved;
sending at least one control signal to cause at least one status indicator of the at least one laundry machine to indicate a reserved status; and
sending a response to the mobile computing device indicating the reservation of the at least one laundry machine at the particular laundromat.
6. The system of claim 5, the operations further comprising:
selecting the at least one laundry machine from the one or more currently available laundry machines at the particular laundromat, based at least in part on an analysis of usage history of the one or more currently available laundry machines.
7. The system of claim 1, wherein:
the laundry machine is a washing machine; and
the period of time corresponds to at least one wash cycle of the washing machine.
8. The system of claim 1, wherein:
the laundry machine is a dryer; and
the period of time corresponds to one or more increments of drying time associated with the dryer.
9. A computer-implemented method performed by at least one processor, the method comprising:
receiving, by the at least one processor, a request for use of a laundry machine that is one of multiple laundry machines in a vicinity of a mobile computing device, the request sent by the mobile computing device responsive to a determination that the mobile computing device is in proximity to the laundry machine, wherein a wireless network interface of the mobile computing device receives a beacon signal that is emitted from each of the multiple laundry machines, and wherein the determination that the mobile computing device is in proximity to the laundry machine is based on: i) a received signal level of the beacon signal from the laundry machine having at least a strength that corresponds to a threshold distance between the mobile computing device and the laundry machine, and ii) the received signal level of the beacon signal from the laundry machine being stronger than a respective signal level of each of the other beacon signals from the other laundry machines in the vicinity, wherein the beacon signal includes an identifier of the laundry machine that uniquely identifies the laundry machine among the multiple laundry machines, wherein the identifier included in the beacon signal changes periodically, and wherein the identifier is included in the request, sent by the mobile computing device, for use of the laundry machine;
determining, by the at least one processor, a network address of the laundry machine indicated in the request; and
sending, by the at least one processor, a control signal to the network address of the laundry machine, wherein the control signal causes an altering of an operational state of the laundry machine to enable use of the laundry machine during a period of time.
10. The method of claim 9, wherein the threshold distance is previously determined based on a calibration to measure distance versus signal level for a transmitted power of the beacon signal.
11. The method of claim 9, wherein the request includes a code that identifies the laundry machine and that is presented on or in proximity to the laundry machine.
12. The method of claim 9, further comprising:
receiving, by the at least one processor, an availability request for availability information describing currently available laundry machines, the availability request indicating a location of one or more of a user or the mobile computing device;
in response to the availability request, identifying, by the at least one processor, one or more laundromats within a threshold distance of the location, the one or more laundromats including one or more currently available laundry machines; and
sending, by the at least one processor, in response to the availability request, the availability information indicating the one or more laundromats that include the one or more currently available laundry machines.
13. The method of claim 12, further comprising:
receiving, by the at least one processor, a reservation request for a reservation of at least one laundry machine at a particular laundromat of the one or more laundromats, the reservation request sent in response to a selection of the particular laundromat from the one or more laundromats, the selection made through a user interface (UI);
updating, by the at least one processor, status information to indicate the at least one laundry machine as reserved;
sending, by the at least one processor, at least one control signal to cause at least one status indicator of the at least one laundry machine to indicate a reserved status; and
sending, by the at least one processor, a response to the mobile computing device indicating the reservation of the at least one laundry machine at the particular laundromat.
14. One or more computer-readable storage media storing instructions which, when executed by at least one processor, instruct the at least one processor to perform operations comprising:
receiving a request for use of a laundry machine that is one of multiple laundry machines in a vicinity of a mobile computing device, the request sent by the mobile computing device responsive to a determination that the mobile computing device is in proximity to the laundry machine, wherein a wireless network interface of the mobile computing device receives a beacon signal that is emitted from each of the multiple laundry machines, and wherein the determination that the mobile computing device is in proximity to the laundry machine is based on: i) a received signal level of the beacon signal from the laundry machine having at least a strength that corresponds to a threshold distance between the mobile computing device and the laundry machine, and ii) the received signal level of the beacon signal from the laundry machine being stronger than a respective signal level of each of the other beacon signals from the other laundry machines in the vicinity, wherein the beacon signal includes an identifier of the laundry machine that uniquely identifies the laundry machine among the multiple laundry machines, wherein the identifier included in the beacon signal changes periodically, and wherein the identifier is included in the request, sent by the mobile computing device, for use of the laundry machine;
determining a network address of the laundry machine indicated in the request; and
sending a control signal to the network address of the laundry machine,
[Truncated to input limit]