Self-calibrating odor sensing system with user feedback

Abstract

The present invention pertains to a self-calibrating odor sensing system that harnesses human feedback to continuously adapt and recalibrate itself. This system employs an electronic odor sensor connected to an microcontroller for monitoring air quality, with a particular application in multi-floor gravity chute buildings. Users are engaged through a user interface, which prompts them to rate their olfactory experience as "happy" for pleasant or "sad" for unpleasant. These user ratings are transmitted to a central Master Panel for data collection and processing. Over time, the system computes a baseline odor rating reflecting the typical odor experience. Utilizing this baseline and additional parameters such as a "span," the system dynamically establishes an odor threshold level. This threshold acts as a trigger for system responses when air quality is deemed unacceptable. Furthermore, the system continuously adapts to changing conditions by adjusting the baseline and threshold based on ongoing user feedback.

Description

Self-Calibrating Odor Sensing System with User FeedbackBackgroundField:

[0001] The present inventions relates to the field of environmental monitoring systems and, more specifically, to a self-calibrating odor sensing system that leverages user feedback to continuously adapts and recalibrate itself. This technology finds particular utility in the context of gravity chute buildings and other environments where air quality management is critical. The feedback information can be used for triggering automatic cleaning and sanitizing procedures through a network and to the gravity chute's cleaning hardware.Description of Related Art:

[0002] Odor sensors, which are designed to detect and measure the concentration of Volatile Organic Compounds (VOCs) in the air, are essential for maintaining indoor air quality in various settings. However, traditional odor sensors often exhibit significant limitations. They tend to deteriorate over time, requiring frequent maintenance and calibration to remain accurate. Moreover, their precision is seldom comparable to the discerning capabilities of the human olfactory system.

[0003] The lack of odor sensors that can mimic the acuity of human senses has presented a challenge in multiple industries, including sanitation, where the control of unpleasant odors is crucial. Existing solutions involve periodic calibration and maintenance, making them labor- intensive and costly, while still falling short of addressing the dynamic nature of odor perception.Summary:

[0004] The present invention introduces a groundbreaking self-calibrating odor sensing system that overcomes these inherent shortcomings. By combining odor sensor for VOC measurements and a microcontroller for data processing, this system not only provides real-time monitoring of air quality but also harnesses human participation to create a dynamic and self- adjusting calibration process.

[0005] In practice, the system is deployed in multi-floor gravity chute buildings, where users are prompted to rate their olfactory experience through a user interface after waste disposal transactions. This rating, ranging from "happy" for pleasant to "sad" for unpleasant, is transmitted to a central Master Panel responsible for data aggregation and analysis. Over time, the system computes a baseline odor rating for the gravity chute, serving as a reference for typical odor experiences.

[0006] Crucially, the system establishes an odor threshold based on this baseline and additional parameters, such as a "span." This threshold acts as a triggerfor the system to respond when air quality is considered unacceptable, enabling timely interventions to address odor issues. Furthermore, the system continually adapts its baseline and threshold levels based on evolving user feedback, ensuring it remains highly sensitive to changing odor conditions.

[0007] In essence, the present invention eliminates the need for constant maintenance and calibration, as it relies on user input to autonomously determine baseline levels and recalibrate thresholds. This novel technology has the potential to revolutionize the management of indoor air quality in gravity chute buildings and other settings, offering a cost-effective, responsive, and user-centric solution to odor control.

[0008] This background section provides context for the invention, emphasizing the challenges and limitations of existing odor sensing systems and introducing the innovative approach of the self-calibrating odor sensing system.Brief Description of Drawings:

[0009] Figure 1 is a Unsanitary to Sanitary evaluation diagram

[0010] Figure 2 is a Schematic diagram of an odor sensor connected to a MCU

[0011] Figure 3 is a graph showing days vs particles per million with gradient span boxes

[0012] Figure 4 is a user input flow diagram showing data flow from user to network to odor sensor to wash controller.Detailed Descriptions of Example Embodiments:

[0013] Figure 1 is a Unsanitary to Sanitary evaluation diagram where the lower scores 1- 2 can lower the baseline and reset the span location in the data model and the middle number selection 3 keeps the baseline where it currently is in the data model and the upper number selections increase the baseline to a higher threshold resetting the top of the span range and increasing the baseline. This selection hardware sends via network this data to the building's data model to configure the span in the MCU which is responsible to trigger the event action (Figure 2).

[0014] Figure 2 is a Schematic diagram of an odor sensor connected to a MCU whereby the odor sensor collects parts per million of air particulates to establish a trend of data collected for a data model. An arbitrary value is set in the MCU firmware which sets the baseline, span and threshold values. The output of the sensor connects to an operational amplifier which sends the analog data to the MCU which is forwarded to a network to be stored in a data model and providedata analytics and MCU feedback to alter the span trajectory in the microcontroller. There are three (3) components of a dataset which provide a basis of activity for the event action (figure 2) beginning with the baseline dataset, and a threshold dataset whereby threshold minus baseline equals span and it is this span's threshold which determines when an event action occurs. The said span is determined from the selection data sets provided by the human interface in Figure 1.

[0015] Figure 3 is a graph showing days vs particles per million with gradient span boxes (103, 105) which are on a graph created by a data model stored in a network server for an associated data set provider (building) whereby the graph (101) represents the data collected from the odor sensor circuit (Figure 2) and the boxes (103, 105) show the span range. While the user feedback is between 5 - 3, there is no trigger event however when the span model range allows the graph to enter the 1-2 range, a trigger event occurs which begins directives associated with improving the air quality. This can include wash and air flow adjustments.

[0016] The graph shows span (103) showing an existing reading span from day 5 to day 12 from 45 ppm and reaching 68ppm where the user input determined was the threshold for span (103). This caused a trigger event turning on the air quality improvement initiatives and causing the user feedback between day 12 to day 23 to be within tolerable range. However the odor sensor span threshold now has reset to a new level causing the baseline to increase to 70 ppm whereas the users determined this was a sanitary level and when the threshold is met at 110 ppm, this triggers a new air quality improvement initiative and resetting the baseline again. This will be a constant change in user input verses actual odor sensory input constantly keeping a calibration to user preferences.

[0017] Figure 4 is a user input flow diagram showing data flow from user to network to odor sensor to wash controller whereby a hopper door is located on each floor of a multi-story building. The user utilizes the system to discard waste and when the transaction is completed, the user may make a selection rating the sanitary condition of the gravity chute. This selection may range from 1-5 in the sanitary to unsanitary selection hardware interface which relays the selection data to a network to a master controller which is further relayed to the internet. The internet is in constant update with the odor sensor or may feedback data aggregation back to the master for the computational process. This said computational process may occur on either the Master Controller or the Internet server and the said Master Controller may directly load the user selection values serially via network to the Odor Sensor. The said user selection values alter the current threshold constantly adjusting the span between the baseline and the threshold up or down on the data reading from the odor sensor element. Once threshold is met, this triggers an event such as a wash controller which cleans the chute autonomously improving air quality and awaiting user feedback to begin the cycle again.Methods of Preferred Embodiments:

[0018] The following description outlines preferred embodiments of the methods employed by the self-calibrating odor sensing system, illustrating its operational processes and the utilization of human feedback for continuous recalibration. It should be noted that while the following embodiments describe specific steps, alternative configurations and variations are possible and are considered within the scope of this invention.Hardware Setup:

[0019] The system is initially configured by equipping each floor of a gravity chute building with an MQ135 sensor, which is capable of measuring a wide range of Volatile Organic Compounds (VOCs) in the ambient air.

[0020] Each MQ135 sensor is connected to an ESP32 microcontroller, which facilitates data collection, processing, and communication with a central system, often referred to as the Master Panel. A code example is provided below which shows how to achieve score based calibration of the MQ135 sensor using a microcontroller;

[0021] The Code: / / Define variables for baseline, threshold, and span float baseline - 45.0; / / Initial baseline ... This can be adjusted float threshold = 100.0; / / Initial threshold... When an action takes place float span = threshold - baseline; / / Define a function to recalibrate the system void recalibrate(float userRating) { / / Calculate the new baseline based on user rating if (userRating == 5.0) { baseline += 15.0; / / Increase baseline by 15 ppm} else if (userRating >= 2.5 && userRating < 5.0) { baseline -= userRating * 10.0; / / Decrease baseline based on rating} / / Update the span and threshold threshold = baseline + span;} void setup() { / / Initialize the Microcontroller and MQ135 sensor / / Set up communication with the central system (Master Panel)} void loop() { / / Read user rating from the user interface float userRating = 3.0; / / Example user rating, replace with actual input / / Recalibrate the system based on user rating recalibrate(userRating); / / Continuously monitor air quality with the MQ135 sensor float currentReading = readMQ135Sensor(); / / Replace with actual reading / / Check if the current reading exceeds the threshold if (currentReading > threshold) { / / Implement a response (e.g., activate ventilation, send alerts) takeActionTolmproveAirQuality();} / / Continue monitoring and recalibrating as needed delay(lOOO); / / Adjust the delay as needed} float readMQ135Sensor() { / / Replace this function with actual code to read the MQ135 sensor / / Return the VOC concentration value} void takeActionToImproveAirQualityO { / / Implement wash cycle to improve air quality / / activate ventilation or send alerts }

[0022] Code Explanation:

[0023] Initialization:

[0024] The code begins with the initialization of variables for the baseline, threshold, and span, which are used to define the system's initial calibration settings.

[0025] Recalibration:

[0026] The recalibrate() function is defined to adjust the baseline based on the user's odor rating. If the user rates the odor as "5" (optimum), the baseline increases by 15 ppm. If the rating is between "2.5" and "5," the baseline decreases based on the rating multiplied by 10.

[0027] Setup:

[0028] In the setup() section, the ESP32 and MQ135 sensor are initialized, and any necessary communication with the central system (Master Panel) is set up.

[0029] Main Loop:

[0030] The loop() function is where the main execution occurs:

[0031] The user rating is simulated with the variable userRating. In practice, you would replace this with actual input from the user interface.

[0032] The system recalibrates based on the user's rating using the recalibrate() function.

[0033] The code continuously monitors air quality by reading the MQ135 sensor's data(simulated with readMQ135Sensor(); replace with actual sensor reading).

[0034] If the current reading exceeds the recalibrated threshold, the system can take actions to improve air quality (simulated with takeActionTolmproveAirQuality(); replace with actual response logic).

[0035] Sensor Readings:

[0036] The readMQ135Sensor() function is a placeholder for reading the actual VOC concentration from the MQ135 sensor.

[0037] Air Quality Improvement:

[0038] The takeActionTolmproveAirQuality() function represents a placeholder for implementing actions to improve air quality when the threshold is exceeded. These actions could include activating wash cycles and ventilation systems, sending alerts, or any other necessary responses.

[0039]

[0040] Data Collection:

[0041] The MQ135 sensors continuously sample the air quality and record data related to the concentration of VOCs present in the environment. These data points are collected at regular intervals.

[0042] User Interface and Rating Feedback:

[0043] A user interface is deployed on every floor, accessible after individuals perform waste disposal transactions within the gravity chute building.

[0044] Users are prompted to rate their olfactory experience on a simple scale, typically ranging from "happy" for a pleasant odor to "sad" for an unpleasant odor. User ratings are recorded immediately after the transaction.

[0045] Transmission to Master Panel:

[0046] The user's ratings, along with corresponding floor and timestamp information, are transmitted to the Master Panel. This central system is responsible for data aggregation, analysis, and subsequent recalibration processes.

[0047] Baseline Calculation:

[0048] Over time, as user ratings accumulate, the system computes an average or baseline odor rating specific to each floor. The baseline serves as a reference for the typical odor experience on that floor.

[0049] Threshold Adjustment:

[0050] Utilizing the baseline rating and other adjustable parameters, such as a "span," the system establishes an odor threshold level. This threshold indicates the point at which the air quality is considered unacceptable.

[0051] Continuous Adaptation:

[0052] As the system collects additional user ratings and real-time data from the MQ135 sensors, it continuously adjusts the baseline and threshold levels. This dynamic adaptation ensures the system remains highly responsive to changing odor conditions within the building.

[0053] System Responses:

[0054] When the system detects that the odor exceeds the threshold, it triggers predefined responses to rectify the issue. Such responses may include activating ventilation systems, alerting maintenance personnel, or implementing other actions aimed at improving air quality.

[0055] These preferred embodiments describe the operational sequence and methods of the self-calibrating odor sensing system. It highlights the system's ability to leverage user feedback for continuous recalibration, thus addressing the challenges associated with conventional odor sensors and offering a responsive and user-centric solution for maintaining indoor air quality.

Claims

We Claim:Claim 1: A self-calibrating odor sensing system comprising: an odor sensor capable of measuring Volatile Organic Compounds (VOCs) in the air; an MCU (Microcontroller Unit) for data processing and communication; a user interface for collecting odor ratings from users; and a Master Panel for data aggregation and recalibration based on user ratings.Claim 2: The system of Claim 1, wherein the system recalibrates the baseline and threshold levels based on user ratings, wherein: user ratings of "5" lead to an increase in the baseline by a predefined value. user ratings between "2.5" and "5" result in a decrease in the baseline based on the rating multiplied by a predefined factor.Claim 3: The system of Claim 1, wherein the baseline rating is continuously computed for each floor based on accumulated user ratings.Claim 4: The system of Claim 1, wherein the threshold level is set based on the baseline and a predefined span, and when the threshold is exceeded, the system triggers responses to improve air quality.Claim 5: The system of Claim 1, which continuously adapts the baseline and threshold levels based on evolving user feedback and real-time sensor data, ensuring the system remains highly responsive to changing odor conditions.Claim 6: A method for self-calibrating odor sensing comprising: collecting user ratings for odor perception after waste disposal transactions; recalibrating the baseline and threshold levels based on user ratings;continuously monitoring air quality with an odor sensor; and triggering responses to improve air quality when the current reading exceeds the recalibrated threshold.Claim 7: The method of Claim 6, wherein recalibration of the baseline is performed by increasing the baseline by a predefined value for user ratings of "5," and decreasing the baseline for user ratings between "2.5" and "5" based on the rating multiplied by a predefined factor.Claim 8: The method of Claim 6, further comprising continuously computing and updating the baseline rating for each floor based on accumulated user ratings.Claim 9: The method of Claim 6, further comprising setting the threshold level based on the recalibrated baseline and a predefined span, and triggering actions to improve air quality when the current reading from the odor sensor exceeds the recalibrated threshold.Claim 10: The method of Claim 6, which includes continuously adapting the baseline and threshold levels based on evolving user feedback and real-time sensor data, maintaining the system's automated responsiveness to changing odor conditions.

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