An indoor air quality sensing system and method of analysing indoor air quality using the system thereof

Abstract

The present invention relates to an indoor air quality sensing system (100). The indoor air quality sensing system (100) comprises an enclosure comprising at least one inlet (2) configured to allow indoor air to flow into the enclosure; a plurality of sensors (6) located within the enclosure for sensing indoor air quality parameters; a computing device configured to process the indoor air quality parameters and produce indoor air quality results; characterized by a display connectable to the computing device and configured to show the indoor air quality results; wherein the sensors (6) comprise at least one graphene-based sensor configured to detect bioaerosols. Further, a method of analysing indoor air quality using the indoor air quality sensing system (100) is also disclosed.

Description

[0001] AN INDOOR AIR QUALITY SENSING SYSTEM AND METHOD OF ANALYSING INDOOR AIR QUALITY USING THE SYSTEM THEREOF

[0002] TECHNICAL FIELD

[0003] This invention relates generally to the field of sensing systems. More particularly, the present invention pertains to an indoor air quality sensing system.

[0004] BACKGROUND ART

[0005] The level of invisible airborne organic chemical and odour contaminates, as well as ozone and other oxidant related contaminates, in indoor air is generally higher than the levels found outdoors. Potentially harmful contaminates known as volatile organic compounds (VOCs) are a large group of carbon-based chemicals that easily evaporate at room temperature. While most people can smell high levels of some volatile organic compounds, other volatile organic compounds have no odour. Odour does not indicate the level of risk from inhalation of this group of chemicals. There are thousands of different volatile organic compounds produced and used in daily lives. Volatile organic compounds are often released from products such as building materials, carpets, adhesives, upholstery fabrics, vinyl floors, composite wood products, paints, and varnishes.

[0006] The health risks from inhaling any chemical depends on how much of the chemical is in the air, and how long and how often a person inhales the chemical. Breathing low levels of volatile organic compounds for long periods of time may increase the risk of health problems for some people. Several studies suggest that exposure to volatile organic compounds may make symptoms worse in people who have asthma or are particularly sensitive to chemicals. Short-term exposure (acute) to high levels of volatile organic compounds may cause eye, nose and throat irritation, headaches, nausea, vomiting, dizziness or worsening of asthma symptoms. Long-term exposure (chronic) to high levels of volatile organic compounds create an increased risk of cancer, liver damage, kidney damage, and central nervous system damage. In order to better monitor the indoor air quality, some advances and improvements have been made in creating and discovering better indoor air quality management systems. Examples of related references are described below, and the supported teachings of each reference are incorporated by reference herein:

[0007] US5394934A relates to an indoor air quality sensor designed to be utilized in a zone of a building to control the ventilation of the zone and the method of effecting such control. The sensor comprises a first sensor for sensing a selected leading indicator of contamination in the zone and providing an output signal representative thereof and at least one additional sensor for sensing at least one selected secondary indicator of contamination in the zone and providing an output signal representative thereof. A processor, utilized for generating an output signal representative of the indoor air quality in the zone, receives the output signals from the first sensor and the least one additional sensor and generates the output signal representative of the indoor air quality in the zone by influencing the output of the first sensor by an amount that is a function of the output signal of the least one additional sensor.

[0008] US7302313B2 relates to an air monitoring system having an air monitoring unit with at least one sensor for measuring data of an air quality parameter and a computer for storing the air quality parameter data received from the sensor. The air monitoring unit may use an installed or a portable system, or a combination of both, for measuring the air quality parameters of interest. A remote data centre may be provided, and the data may be uploaded to the data centre from the unit by a communications media such as the Internet. Information or instructions may also be downloaded from the data centre to the unit via the communications media for controlling or modifying the function of the unit. An expert system may be provided with the air monitoring system for controlling the unit. The information or instructions downloaded to the unit may be generated by the expert system. AU2021 103962A4 relates to a portable system and a method for real-time monitoring the air quality using the Internet of Things (loT). The system comprises a portable computing device, a self-adhesive transparent flexible strip with an array of multiple sensors, a wireless communication unit, a cloud computing unit to process the signals, a software application and a proximity sensor. The sensors sense the quality of air and send the signals to a wireless communication unit. The wireless communication unit then passes the signal information to the cloud computing unit where these signals are processed by a Machine Learning algorithm and communicates with the computing device. The computing device with the aid of the software application displays the air quality results. The software application activates the proximity sensor to identify the specific location of air pollutants.

[0009] WO2021 130759A1 provides a method and a system to measure and control indoor environment using Internet of Things (loT) and Artificial Intelligence (Al) or Strong Artificial Intelligence (SAI). The method includes the steps of measuring air quality of an indoor environment and / or outdoor environment using respective sensors and / or analyzers, followed by receiving, configuring and controlling the data, by the processor, to maintain the indoor air quality using healthy gas stored in the container(s) and using air conditioned unit to achieve the user desired indoor air quality parameters. Further, the present disclosure also provides a system for measuring and controlling air quality in an indoor environment as desired by the user. The user can even customize the parameters to achieve desired air quality in the indoor environment.

[0010] Nevertheless, the references described above and other existing techniques still suffer from a number of problems of which the objectives and features of the present invention attempt to address. For example, the existing indoor air quality management systems are only capable of detecting limited gases and pollutants present in the indoor air. More particularly, the existing indoor air quality management systems do not take bioaerosols, such as airborne transmissions of pathogens, non-pathogenic organisms, fragments of microbial cells, and by-products of microbial metabolism, into consideration when assessing the indoor air quality. Lack of accurate indoor air quality measurement can lead to a higher risk of indoor health concerns. Therefore, there still remains a need in the art to provide an indoor air quality sensing system that solves the problems described herein.

[0011] SUMMARY OF THE INVENTION

[0012] The following presents a simplified summary of the present invention in order to provide a basic understanding of some aspects of the present invention. This summary is not an extensive overview of the present invention. Its sole purpose is to present some concepts of the present invention in a simplified form as a prelude to a more detailed description that is presented later.

[0013] It is an objective of the present invention to provide an indoor air quality sensing system that is capable of real-time monitoring indoor air quality.

[0014] It is also an objective of the present invention to provide an indoor air quality sensing system that is capable of achieving a comprehensive indoor air quality measurement by detecting a wide range of gases and pollutants present in the indoor air.

[0015] Accordingly, these objectives may be achieved by following the teachings of the present invention. The present invention relates to an indoor air quality sensing system. The indoor air quality sensing system comprises an enclosure comprising at least one inlet configured to allow indoor air to flow into the enclosure; a plurality of sensors located within the enclosure for sensing indoor air quality parameters; a computing device configured to process the indoor air quality parameters and produce indoor air quality results; characterized by a display connectable to the computing device and configured to show the indoor air quality results; wherein the sensors comprise at least one graphene-based sensor configured to detect bioaerosols. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order for the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may have been referred by embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and is therefore not to be considered limiting of its scope. The invention may admit to other equally effective embodiments.

[0017] These and other features, benefits, and advantages of the present invention will become apparent by reference to the following figures, with like reference numbers referring to like structures across the views, wherein:

[0018] Figure 1 illustrates a front view of an indoor air quality sensing system in accordance with an embodiment of the present invention;

[0019] Figure 2 illustrates a flowchart of the artificial intelligence model training and testing to produce a best-fit model for the detection of air quality in accordance with an embodiment of the present invention;

[0020] Figure 3 illustrates a flowchart of the artificial intelligence model flow for the detection of air quality in accordance with an embodiment of the present invention; and

[0021] Figure 4 illustrates a flowchart of the artificial intelligence model flow to obtain a baseline value in accordance with an embodiment of the present invention.

[0022] DETAILED DESCRIPTION OF THE INVENTION

[0023] As required, detailed embodiments of the present invention are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the invention, which may be embodied in various forms. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting but merely as a basis for claims. It should be understood that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents and alternatives falling within the scope of the present invention as defined by the appended claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words "include," "including," and "includes" mean including, but not limited to. Further, the words "a" or "an" mean "at least one” and the word "plurality" means one or more, unless otherwise mentioned. Where the abbreviations or technical terms are used, these indicate the commonly accepted meanings as known in the technical field.

[0024] The present invention is described hereinafter by various embodiments with reference to the accompanying drawings, wherein reference numerals used in the accompanying drawings correspond to the like elements throughout the description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein. Rather, the embodiment is provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art.

[0025] The present invention relates to an indoor air quality sensing system (100). The indoor air quality sensing system (100) comprises an enclosure comprising at least one inlet (2) configured to allow indoor air to flow into the enclosure; a plurality of sensors (6) located within the enclosure for sensing indoor air quality parameters; a computing device configured to process the indoor air quality parameters and produce indoor air quality results; characterized by a display connectable to the computing device and configured to show the indoor air quality results; wherein the sensors (6) comprise at least one graphene-based sensor configured to detect bioaerosols.

[0026] Referring to the drawings as shown in Figures 1 -3, the present invention will now be described in more detail.

[0027] Figure 1 illustrates a front view of an indoor air quality sensing system (100) in accordance with an embodiment of the present invention. An inlet (2) can be located at the top of an enclosure for receiving indoor air while two outlets (8) can be located at respective sides proximate to the lower section of the enclosure. A plurality of sensors (6) can be located within the enclosure and a fan (4) can be disposed above the sensors (6) so as to direct the indoor air received from the inlet (2) to flow through the sensors (6). Subsequently, the indoor air can flow out of the enclosure through the two outlets (8). The enclosure can be portable such that the indoor air quality sensing system (100) can be moved to a desired place to measure the indoor air quality thereof.

[0028] When the indoor air flows through the sensors (6), the sensors (6) can detect indoor air quality parameters such as, but not limited to, types of gases and pollutants present in the indoor air. Thereafter, a computing device such as, but not limited to, a processor can process the indoor air quality parameters and produce indoor air quality results such as, but not limited to, an indoor air quality index. The indoor air quality index can be a weighted combination of the indoor air quality parameters. Subsequently, a display such as, but not limited to, a screen connectable to the computing device can show or exhibit the produced indoor air quality results for real-time monitoring. The indoor air quality results can be displayed in the form of a dashboard or a graphical user interface including various types of visual data. For example, the visual data may include the detected types of gases and pollutants present in the indoor air as well as the amount or concentration thereof. Further, the display will give an alert message when the indoor air quality index exceeds a predetermined safe exposure level. For example, the display may advise a user to open a window or a door for better ventilation when the indoor air quality goes beyond the pollution threshold.

[0029] In accordance with an embodiment of the present invention, the sensors (6) include, but not limited to, carbon monoxide sensors, carbon dioxide sensors, volatile organic compound sensors, nitric oxide sensors, nitrogen dioxide sensors, and ammonia sensors. The sensors (6) also comprise at least one graphene-based sensor configured to detect bioaerosols. As such, the indoor air quality sensing system (100) is capable of detecting harmful gases and simultaneously sensing the bioaerosols including bacteria, fungi, viruses, microbial toxins, pollen, and plant fibres so as to encompass all relevant air pollutants at every feasible time frame. The indoor air quality sensing system (100) may further comprise a temperature sensor and a humidity sensor to aid the determination of the indoor air quality index.

[0030] Graphene oxide (GO) and metal oxide dissolved in ethanol can first be reduced to reduced graphene oxide using acid under vigorous stirring and sonication. Then, the solution can be annealed at high temperature for a period of time. The cooled precipitate from the process can be centrifuged, washed and dried. The resulting material that is less than 10 nm in size is called nanomaterial which can be then deposited onto an interdigitated electrode (IDE) by way of a solvent to ensure uniform spread.

[0031] For the polymer, the synthesis process and chemical usage may differ depending on the type of polymer. Generally, the synthesis proses for the polymer involves dissolving the polymer in deionized water with ultrasonication for an hour and the resultant can then be washed thoroughly with deionized water and dried in an oven / room temperature depending on the type of the polymer. After the synthesis process, the drop casting method can be used to bind the sensing material on the die. Polymer cellulose can be used as the binder. Once the sensing material is bound to the die, it can be used for the testing of the bioaerosol detection.

[0032] In accordance with an embodiment of the present invention, the graphene-based sensor can be customized. The customization of the graphene-based sensor aims to increase the specificity of the bioaerosol detection towards certain gases. The graphene-based sensor can be customized for different gas concentration ranges and fabricated by first preparing the sensing materials. The examples of the sensing material customization include, but not limited to, tin oxide (SnO2) / reduced graphene oxide (RGO) / gold nanoparticles (AuNPs), zinc oxide (ZnO) / reduced graphene oxide (RGO) / gold nanoparticles (AuNPs), nickel oxide (NiO2) / reduced graphene oxide (RGO) / gold nanoparticles (AuNPs), reduced carboxyl-graphene oxide (RGO-COOH), reduced graphene oxide (RGO) / poly(3,4-ethylene dioxythiophene) polystyrene sulphonate (PEDOT:PSS), and graphene (GP) / polyaniline (PANI). The sensing materials can be obtained through the synthesis process. The synthesis process for the metal oxide may differ from that of the polymer.

[0033] In accordance with an embodiment of the present invention, the sensors (6) also comprise at least one metal oxide sensor for detecting the bioaerosols. The metal oxide can be doped with noble metals such as, but not limited to, gold nanoparticles. The examples of the metal oxide include, but not limited to, tin oxide, nickel oxide, and zinc oxide.

[0034] In accordance with an embodiment of the present invention, the indoor air quality sensing system (100) further comprises a wireless communication unit for wirelessly communicating with a cloud computing unit. The indoor air quality parameters received from the sensors (6) and the indoor air quality results produced by the computing device can be delivered to the cloud computing unit for storage through the wireless communication unit using communication protocols such as, but not limited to, Wi-Fi, Bluetooth, and, ZigBee. The wireless communication unit and the cloud computing unit jointly form an Internet of Things (loT) network for real-time monitoring the indoor air quality.

[0035] The present invention also discloses a method of analysing indoor air quality using an indoor air quality sensing system (100), wherein the method comprising the steps of, sampling the indoor air, and producing the indoor air quality results through a display connectable to a computing device, wherein the indoor air quality parameters received by a plurality of sensors (6) are processed using an artificial intelligence incorporated in the computing device. The sampling of indoor air is conducted every 1 minute to capture baselines and the sensors (6) responses to contamination within the 1 minute as well. Besides, sensor (6) responses take 1-5 seconds when exposed to contaminants due to sensing material characteristics and the physical movement of the contaminants. The changes in air quality are rarely abrupt and occur slowly. Even during testing, 1 minute produced the best accuracy. The artificial intelligence model can use the measured indoor air quality parameters to learn in the creation of more accurate indoor air quality results. The artificial intelligence better learns the pattern, resulting in the indoor air quality results becoming more accurate and predictive.

[0036] In accordance with an embodiment of the present invention, the indoor air quality parameters are processed using the artificial intelligence by the steps of, aggregating the sensor data, pre-processing the sensor data, predicting model, analysing the result obtained from the model, storing the result in a cloud database; and displaying the result on the computing device as shown in Figure 2 and Figure 3. Further, the models developed to determine the indoor air quality condition. This model can be implemented in the multiple sequence prediction method where the first layer is the input layer that takes in n number of input data, LSTM / GRU Layer 1 , LSTM / GRU Layer 2, LSTM / GRU Layer 3, Dense Layer, and Output Layer. The output layer can be the AQI or the air quality index at that point in time.

[0037] In accordance with an embodiment of the present invention, the indoor air quality baseline parameters are processed using the artificial intelligence by the steps of aggregating the sensor data, pre-processing the sensor data, predicting model, analysing the result obtained from the model, storing the result in a cloud database; and displaying the result on the computing device, as shown in Figure 4. Further, the models were developed to serve as baselines to compare indoor air quality.

[0038] Accordingly, the indoor air quality sensing system (100) of the present invention is capable of real-time monitoring indoor air quality. Moreover, the indoor air quality sensing system (100) of the present invention is capable of achieving a comprehensive indoor air quality measurement by detecting a wide range of gases and pollutants present in the indoor air. A wide variety of further uses and advantages of the present invention will become apparent to one skilled in the art.

[0039] The exemplary implementation described above is illustrated with specific characteristics, but the scope of the invention includes various other characteristics.

[0040] Various modifications to these embodiments are apparent to those skilled in the art from the description and the accompanying drawings. The principles associated with the various embodiments described herein may be applied to other embodiments. Therefore, the description is not intended to be limited to the embodiments shown along with the accompanying drawings but is to be providing the broadest scope consistent with the principles and the novel and inventive features disclosed or suggested herein. Accordingly, the invention is anticipated to hold on to all other such alternatives, modifications, and variations that fall within the scope of the present invention and appended claims.

[0041] It is to be understood that any prior art publication referred to herein does not constitute an admission that the publication forms part of the common general knowledge in the art.

[0042] In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as “comprises” or “comprising” is used in an inclusive sense, i.e., to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.

Claims

CLAIMS:1 . An indoor air quality sensing system (100), comprising: an enclosure comprising at least one inlet (2) configured to allow indoor air to flow into the enclosure; a plurality of sensors located within the enclosure for sensing indoor air quality parameters; a computing device configured to process the indoor air quality parameters and produce indoor air quality results; characterized by a display connectable to the computing device and configured to show the indoor air quality results; wherein the sensors (6) comprise at least one graphene-based sensor configured to detect bioaerosols.

2. The indoor air quality sensing system (100) as claimed in claim 1 , further comprising a fan (4) located within the enclosure and configured to direct the indoor air to flow through the sensors (6).

3. The indoor air quality sensing system (100) as claimed in claim 1 , wherein the enclosure further comprises at least one outlet (8) configured to allow the indoor air to flow out of the enclosure.

4. The indoor air quality sensing system (100) as claimed in claim 1 , wherein the indoor air quality parameters comprise types of gases and pollutants present in the indoor air.

5. The indoor air quality sensing system (100) as claimed in claim 1 , wherein the indoor air quality results comprise an indoor air quality index.

6. The indoor air quality sensing system (100) as claimed in claim 1 , wherein the sensors (6) further comprise carbon monoxide sensors, carbon dioxidesensors, volatile organic compound sensors, nitric oxide sensors, nitrogen dioxide sensors, and ammonia sensors.

7. The indoor air quality sensing system (100) as claimed in claim 1 , further comprising a wireless communication unit for wirelessly communicating with a cloud computing unit.

8. A method of analysing indoor air quality using an indoor air quality sensing system (100) as claimed in claim 1 , wherein the method comprising the steps of: sampling the indoor air; and producing the indoor air quality results through a display connectable to a computing device; wherein the indoor air quality parameters received by a plurality of sensors are processed using an artificial intelligence incorporated in the computing device.

9. The method as claimed in claim 8, wherein the indoor air quality parameters are processed using the artificial intelligence by the steps of: aggregating the sensor data; pre-processing the sensor data; predicting model; analysing the result obtained from the model; storing the result in a cloud database; and displaying the result on the computing device.

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