Sensor system

Abstract

To provide a sensor system which enables data acquisition in consideration of a data trend and the degree of combined impact of environmental factors on disease.SOLUTION: A sensor system is provided, comprising storage means 2 for storing the degree of impact of environmental factors on each disease, sensing means 3 for measuring multiple sets of environmental factor data, and identification means 5 for selectively identifying at least one of the multiple sets of environmental factor data measured by the sensing means 3 on the basis of the degree of impact.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a sensor system for measuring physical quantities of environmental factors in indoor environments such as residential environments (for example, homes, offices, schools, hospitals, hotels, stores, etc.). [Background technology]

[0002] There is a wide range of research being conducted on the optimization of indoor environments, including residential environments, by analyzing various environmental factor data obtained by comprehensively measuring the physical quantities of environmental factors in indoor environments such as residential environments.

[0003] For example, the sensor system in Patent Document 1 uses multiple environmental sensors to measure environmental factors such as temperature and humidity, and based on that data, a computer system connected to a server or the like analyzes degree information indicating the degree to which the indoor environment is suitable for a specified life purpose (e.g., sleep, washing and drying, work, etc.), and provides support for living a comfortable life by reporting the suitability or unsuitability of the indoor environment. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-13221 A (Page 5, Figure 1) [Non-patent literature]

[0005] [Non-Patent Document 1] Nakayama, Y., Nakaoka, H., Suzuki, N. et al. Prevalence and risk factors of pre-sick building syndrome: characteristics of indoor environmental and individual factors. Environ Health Prev Med 24, 77 (2019). [Non-Patent Document 2] Nakayama Y, Suzuki N, Nakaoka H, ​​Tsumura K, Takaguchi K, Takaya K, Hanazato M, Todaka E, Mori C. Assessment of Personal Relaxation in Indoor-Air Environments: Study in Real Full-Scale Laboratory Houses. Int J Environ Res Public Health. (2021). Summary of the Invention [Problem to be solved by the invention]

[0006] It has long been known that indoor environments have a significant impact on human health, but the inventors' research has revealed that, for example, sick house symptoms are caused by a complex combination of factors, including not only the physical quantities of chemical substances such as volatile organic compounds (VOCs), which are one of the environmental factors in the indoor environment, but also other environmental factors such as CO2 concentration and fine particulate matter (PM) concentration, as well as personal attributes of the people living there, such as their gender, age, and disease history, and their lifestyles, such as cleaning frequency and ventilation frequency (see non-patent documents 1 and 2).

[0007] In Patent Document 1, trend data of various environmental factors measured by multiple environmental sensors is uploaded to a server and used as part of big data to evaluate the impact on health management, etc. In this case, while highly accurate analysis is possible, there is a problem that the trend of the data is lost before the evaluation is performed. In addition, in order to take the data trend into consideration, it is necessary to select environmental factor data that are complexly related to the onset of disease based on preventive medical knowledge by experts, which is inefficient.

[0008] The present invention has been made with attention to these problems, and aims to provide a sensor system that enables data acquisition that takes into account data trends and the degree of the complex influence of environmental factors on disease. [Means for solving the problem]

[0009] In order to solve the above problems, the sensor system of the present invention comprises: A storage means for storing an influence level, which is the degree of influence of an environmental factor on a disease, for each disease; A sensing means for measuring a plurality of environmental factor data; The device is characterized by comprising a discrimination means for selectively discriminating at least one of the plurality of environmental factor data measured by the sensing means based on the degree of influence. According to this feature, the environmental factor data to be acquired can be determined from the large amount of environmental factor data measured by the sensing means based on the degree of influence of the environmental factor on the disease quantified by the discrimination means, thereby providing a sensor system that enables data acquisition that takes into account the data trend and influence degree.

[0010] The determining means performs the determination based on personal attributes, lifestyle conditions, and the degree of influence. This feature makes it possible to obtain data that takes into account personal attributes and lifestyle conditions in addition to the degree of impact.

[0011] a first storage means for storing the environmental factor data measured by the sensing means; The apparatus further comprises a second storage means for storing environmental factor organizing data including the environmental factor data selectively determined by the determination means. According to this feature, even if the impact level stored in the storage means is updated or a disease is added, it is possible to generate environmental factor sorting data including environmental factor data newly discriminated by the discrimination means from the environmental factor data stored in the first storage means.

[0012] The environmental factor summary data is characterized in that it contains the environmental factor data selectively determined for each of the diseases. According to this feature, it is easy to analyze the relationship between diseases and environmental factors based on the environmental factor organized data.

[0013] The environmental factor sorting data is characterized in that it contains the environmental factor data ranked for each of the diseases. According to this feature, it is easy to analyze important environmental factors for a disease based on the environmental factor organized data. [Brief description of the drawings]

[0014] [Figure 1] 1 is a diagram showing the appearance of an environmental sensor device to which a sensor system of the present invention is applied; [Diagram 2] FIG. 1 is a block diagram showing a configuration of a sensor system in an embodiment. [Diagram 3] FIG. 13 is a diagram showing a sheet on which environmental factor data of rank A for sick house symptoms is compiled, with regard to the environmental factor summary data stored in the second data storage unit. [Figure 4] FIG. 13 is a diagram showing a sheet on which environmental factor data of rank B for sick house symptoms is compiled, with regard to the environmental factor summary data stored in the second data storage unit. [Diagram 5] FIG. 13 is a diagram showing a sheet summarizing environmental factor data of rank A for sleep disorders, with respect to the environmental factor organization data stored in the second data storage unit. [Figure 6] FIG. 13 is a diagram showing a sheet in which temperatures are summarized as environmental factor data for each disease, with regard to the environmental factor organized data stored in the second data storage unit. [Figure 7] FIG. 13 is a diagram showing a sheet summarizing the results of ranking environmental factor data for each disease, for the environmental factor organized data stored in the second data storage unit. [Figure 8] FIG. 13 is a schematic diagram showing an example of output data of environmental factor organization data. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A sensor system according to an embodiment of the present invention will be described below with reference to the accompanying drawings. EXAMPLES

[0016] The sensor system in this embodiment is applied to an environmental sensor device 1 as shown in Fig. 1. The environmental sensor device 1 in this embodiment is housed in a roughly cubic housing measuring 6 cm on each side, and includes a plurality of sensors, a CPU, a memory, a hard disk (storage), and the like that constitute a computer system described below. The environmental sensor device 1 is installed, for example, on the floor or on a shelf in each room of a living space or workplace, and continuously measures and records the fluctuations in the physical quantities of various environmental factors in the indoor environment.

[0017] The sensor system of this embodiment that is applied to the environment sensor device 1 will be described in detail with reference to FIG.

[0018] As shown in Figure 2, the sensor system is mainly composed of a measurement unit 3 (sensing means) consisting of multiple sensors, and a computer system equipped with a data (impact level) storage unit 2 (storage means), a condition setting unit 4, a discrimination unit 5 (discrimination means), and a data storage unit 6.

[0019] In detail, the measurement unit 3 includes a temperature sensor, a humidity sensor, a CO2 sensor, a volatile organic compound (VOC) sensor, a particulate matter (PM) sensor, an air pressure sensor, and an illuminance sensor. The sensors in the measurement unit 3 may be freely added or removed depending on the environmental factors to be measured.

[0020] In this embodiment, the measurement unit 3 is described as measuring the physical quantities of various environmental factors using each sensor at 5-second intervals, but the measurement interval is not limited to this and may be any measurement interval that provides sufficient environmental factor data necessary for analyzing the association between disease and environmental factors.

[0021] The data (impact) storage unit 2 stores, for each disease, the impact level, which is the degree of the complex impact of environmental factors on the disease. In detail, the data storage unit 2 stores, for each disease, the impact level that has been analyzed and analysed based on the research data and preventive medical knowledge accumulated while the inventors are conducting empirical research on the causal relationship between diseases and various environmental factors in the indoor environment, while also taking into account their complex correlation. The data storage unit 2 is capable of updating the impact level, adding diseases, etc.

[0022] Here, the "degree of influence" in this embodiment is a quantification of the degree of influence of an environmental factor on a disease by performing path analysis or regression analysis using dedicated analysis software. For example, the degree of influence on sick house symptoms is calculated for each environmental factor by the function y = f(a) + f(b) + f(c) + f(d) + f(e) + ··· f(x) + ε. Here, ε is an error term. In addition, the variables a, b, c, d, e, ···, x are adjusted odds ratios (ratios between the probability of disease occurrence and the probability of disease non-occurrence) in logistic regression analysis of each environmental factor (e.g., a is temperature, b is humidity, c is CO2 concentration, d is VOC concentration, and e is PM concentration) on the onset of sick house symptoms. In addition, the variables a, b, c, d, e, ···, x may be calculated by various analysis methods and analytical methods, not limited to logistic regression analysis. In addition, it goes without saying that the degree of influence of an environmental factor on various diseases can be calculated by changing the function according to the target disease.

[0023] In addition, in this embodiment, the degree of influence stored in the data storage unit 2 is calculated in advance externally, but the present invention is not limited to this. For example, the data storage unit 2 may be configured to incorporate dedicated analysis software and to add the latest research data so that the degree of influence can be calculated in the data storage unit 2. Also, the data storage unit 2 may be configured so that functions and variables for calculating the degree of influence can be added or updated by adding the latest research data.

[0024] The condition setting unit 4 can set factors other than environmental factors such as personal attributes (gender, age, disease history, etc.) and lifestyle (cleaning frequency, ventilation frequency, etc.) of people living in the indoor environment where the environmental sensor device 1 is installed as conditions. Furthermore, the condition setting unit 4 of this embodiment is configured to obtain odds ratios in logistic regression analysis for each disease and each environmental factor based on the input personal attributes and lifestyle conditions. This odds ratio is used as a coefficient for discriminating environmental factor data in the discrimination unit 5. Note that the personal attributes and lifestyle factors in the condition setting unit 4 may be freely added, deleted, etc. depending on the people who use the room where the environmental sensor device 1 is installed. Furthermore, it goes without saying that the conditions may be only one of personal attributes and lifestyle.

[0025] The condition setting unit 4 may obtain the odds ratio in the following manner, different from the above. In detail, the condition setting unit 4 stores in advance the contribution degree for each disease, which is analyzed and analyzed based on the research data and preventive medical knowledge accumulated by the inventors while conducting empirical research on the causal relationship between a disease and various conditions, while taking into consideration the complex correlation between them. The condition setting unit 4 is capable of updating the contribution degree and adding diseases, etc. The condition setting unit 4 may also obtain the odds ratio in the logistic regression analysis for each disease and each environmental factor, based on the previously set contribution degree and the inputted personal attributes and lifestyle conditions.

[0026] The discrimination unit 5 is provided with a discrimination algorithm generated by learning (deep and transfer learning) in advance, and selectively discriminates at least one of the multiple environmental factor data measured by the measurement unit 3 based on the influence of the environmental factor for each disease stored in the data storage unit 2 and a coefficient (odds ratio) obtained from the personal attributes and lifestyle conditions set in the condition setting unit 4, and determines the frequency of use of the environmental factor data to be acquired. In detail, for example, the discrimination unit 5 compares a value (hereinafter also referred to as a "rank discrimination value") obtained by multiplying the value of the influence stored in the data storage unit 2 by a coefficient obtained based on the conditions in the condition setting unit 4 with a threshold value previously set for ranking the environmental factor data for various diseases, and determines the type of environmental factor data to be acquired and the frequency of use of the data based on the determined rank. Here, the rank indicates the priority order of data that requires observation based on preventive medical knowledge for the onset of diseases estimated to be caused by various environmental factors, based on the inventor's extensive research to date. In other words, the rank is an index that represents the environmental factors that are important for health outcomes based on preventive medical knowledge that takes into account the complex correlation with the onset of various diseases, and is determined by the discrimination unit 5 based on the conditions set by the condition setting unit 4, with the order of importance being A, B, C, etc.

[0027] The "data usage frequency" refers to the sampling rate of environmental factor data acquired for each disease by the discrimination unit 5. For example, in this embodiment, the environmental factor data stored at 5-second intervals in the data storage unit 6 (first data storage unit 60) is sampled at a predetermined extraction frequency (e.g., 1-hour intervals) according to the rank of the disease. Regarding the data usage frequency, it is preferable to set a high sampling rate for environmental factors whose environmental factor data fluctuates greatly.

[0028] Here, for example, even if people live in the same indoor environment, the required health varies depending on their personal attributes, i.e., children are required to be healthy against sick house symptoms and allergies, elderly people against heart disease and heat stroke, and middle-aged people against sleep disorders and mental health, and the association between diseases and environmental factors may change depending on lifestyle. Therefore, in this embodiment, the discrimination unit 5 uses rank discrimination values ​​that take into account the influence of environmental factors on each disease as well as personal attributes and lifestyle conditions to rank the environmental factor data.

[0029] The discrimination unit 5 is not limited to one that ranks the environmental factor data using the rank discrimination value, but may be one that ranks the environmental factor data using only the value of the influence degree of the environmental factor for each disease.

[0030] The data storage unit 6 is composed of a first data storage unit 60 (first storage means) in which all environmental factor data measured by the measurement unit 3 is stored, and a second data storage unit 61 (second storage means) in which environmental factor sorting data generated from the environmental factor data acquired (discriminated) from the first data storage unit 60 based on the rank discrimination value in the discrimination unit 5 is stored.

[0031] In the first data storage unit 60, all the environmental factor data measured by the measurement unit 3 at five second intervals is stored in chronological order.

[0032] The second data storage unit 61 stores environmental factor organized data obtained by the discrimination unit 5 based on the rank discrimination value for each disease from all environmental factor data stored in the first data storage unit 60. In this embodiment, the environmental factor organized data is stored in the second data storage unit 61 as a worksheet file that can be used with spreadsheet software (see Figs. 3 to 7).

[0033] The worksheet files stored in the second data storage unit 61 are composed of sheets in which environmental factor data is acquired from the first data storage unit 60 for each disease and for each rank, i.e., sheets in which environmental factor data is ranked and acquired from the first data storage unit 60 for each disease (see Figures 3 to 5), a sheet in which environmental factor data is acquired from the first data storage unit 60 for each disease (see Figure 6), and a sheet summarizing the ranking results of the environmental factor data for each disease (see Figure 7).

[0034] More specifically, as shown in Figure 3, environmental factor data is collected for each disease and for each rank, and the sheet for rank A for sick house symptoms summarizes the environmental factor data for CO2 concentration, VOC concentration, and PM concentration. The frequency of data usage is 1 hour for VOC concentration, and 3 hours for CO2 concentration and PM concentration.

[0035] As shown in Fig. 4, the sheet for rank B for sick house symptoms summarizes environmental factor data on temperature and humidity. The data usage frequency is 3 hours for temperature and 12 hours for humidity. Although not shown for the sake of convenience, the sheet for rank C for sick house symptoms summarizes environmental factor data on air pressure, and the sheet for rank D for sick house symptoms summarizes environmental factor data on illuminance.

[0036] In this way, even for the same disease, the discrimination unit 5 generates sheets in which the types of environmental factor data selected for each rank and the frequency of data use are different.

[0037] The worksheet file also includes sheets for sick house symptoms, as well as sheets for allergies and sleep disorders, each with ranks A to D, as sheets on which environmental factor data is acquired for each disease and each rank.

[0038] 3 and 5, the types of environmental factor data to be acquired and the frequency of data use differ for different illnesses, for example, sick house symptoms and sleep disorders, even if the sheets are of the same rank A. As described above, the discrimination unit 5 ranks the environmental factor data for each illness, and the types of environmental factor data to be acquired and the frequency of data use are determined based on the determined rank.

[0039] As shown in Fig. 6, the sheet on which temperature is acquired as environmental factor data for each disease summarizes the environmental factor data for temperature for sick house symptoms, allergies, and sleep disorders. The data usage frequency for temperature is 3 hours for sick house symptoms, 6 hours for allergies, and 1 hour for sleep disorders. In this way, the sheet on which environmental factor data is acquired for each disease reflects the rank assigned to each disease by the discrimination unit 5 as the data usage frequency. Although not shown for the sake of convenience, the worksheet file also has sheets for humidity, VOC concentration, CO2 concentration, PM concentration, air pressure, and illuminance in addition to temperature as sheets summarizing environmental factor data for each disease.

[0040] In addition, as shown in Figure 7, there is a sheet that summarizes the ranking results of the environmental factor data for each disease. By using this sheet, it is easy to understand the environmental factors that are most important for multiple diseases.

[0041] Furthermore, in this embodiment, when the number of people for which the condition setting unit 4 sets conditions is multiple, i.e., when multiple personal attributes are set, the coefficient multiplied by the influence value changes depending on the personal attributes, resulting in different ranking results. Therefore, the discrimination unit 5 generates worksheet files with different data acquisition contents for the number of personal attributes and stores them in the second data storage unit 61. That is, environmental factor organization data customized according to the health required for multiple people with different personal attributes living in the same indoor environment is stored in the second data storage unit 61. At this time, it is preferable that the multiple worksheet files stored in the second data storage unit 61 are labeled with personal attributes.

[0042] Furthermore, the discrimination unit 5 acquires data from the first data storage unit 60 at the timing when a predetermined operation is performed by the user of the environmental sensor device 1 or at a predetermined preset timing, and the generated worksheet file is stored in the second data storage unit 61. All of the worksheet files stored in the second data storage unit 61 are stored in chronological order, and those that are no longer necessary can be deleted.

[0043] Furthermore, by incorporating a communication module, the environmental sensor device 1 may be configured so that all environmental factor data measured by the measurement unit 3 and the environmental factor sorting data generated by the discrimination unit 5 can be stored not only in the data storage unit 6 (first data storage unit 60, second data storage unit 61) but also in an external network such as the cloud.

[0044] As described above, in this embodiment, the discrimination unit 5 determines the type of environmental factor data, the range of data use, and the like based on the degree of influence on a disease and the conditions of personal attributes and lifestyle from the vast amount of environmental factor data stored in the first data storage unit 60, and generates a worksheet file (environmental factor organized data) having a sheet on which environmental factor data is acquired for each disease and for each rank, which can be stored in the second data storage unit 61 provided separately from the first data storage unit 60. This makes it possible to output the worksheet file from the data storage unit 6 and use it for analyzing the relationship between a disease and environmental factor data.

[0045] As a method of using the various data stored in the data storage unit 6, for example, when a user of the environmental sensor device 1 develops a disease, the user takes the environmental sensor device 1 to a hospital, outputs the worksheet file stored in the second data storage unit 61, and a doctor checks the contents of the sheets (see Figs. 3 to 5) in which environmental factor data is acquired for each disease and for each rank, and the sheets (see Fig. 6) in which environmental factor data is acquired for each disease, and the like, and can easily analyze the cause of the disease. In addition, since the environmental factor data ranked by the discrimination unit 5 is data that includes preventive medical knowledge, etc., not only doctors but also non-medical users, engineers, researchers, etc. can easily grasp and analyze the relationship between the disease and the environmental factors by checking the contents of each sheet of the worksheet file.

[0046] As described above, the environmental sensor device 1 can output the environmental factor sorting data in the form of a worksheet file, but it may also analyze the environmental factor sorting data stored in the second data storage unit 61 in cooperation with an application outside the sensor system, and create data individually classified by disease and rank (see FIG. 8). This eliminates the need for data analysts, such as doctors and researchers at hospitals, to prepare analytical equipment, making analysis easier even for those with little knowledge of preventive medicine. In addition, by converting the relationship between diseases and environmental factors from the environmental factor sorting data into an easy-to-understand form and visualizing it, it can also contribute to disease prevention and health promotion through awareness.

[0047] As described above, the sensor system of the present invention can select environmental factor data to be acquired for each rank from the large amount of environmental factor data measured by the measurement unit 3 based on the degree of influence of the environmental factor on a disease quantified by the discrimination unit 5, making it possible to acquire data that takes into account the trend and influence of the data. In other words, it becomes possible to selectively acquire data on environmental factors that are in a complex relationship with multiple health outcomes from a large amount of trend data (environmental factors), and this can be used for highly accurate analysis.

[0048] Furthermore, the discrimination unit 5 can acquire personalized environmental factor data and generate environmental factor organization data by making a discrimination for each rank based on conditions such as personal attributes and lifestyles and the degree of influence. That is, a single environmental sensor device 1 can generate environmental factor organization data in which the types of acquired environmental factor data and the frequency of data use are customized according to the health required for multiple people (e.g., adults and children) with different personal attributes living in the same indoor environment.

[0049] Furthermore, the sensor system of the present invention is equipped with a first data storage unit 60 that stores environmental factor data measured by the measurement unit 3, and a second data storage unit 61 that stores environmental factor organized data selectively acquired from the first data storage unit 60 by the discrimination unit 5. Therefore, even if the impact level stored in the data storage unit 2 is updated or a disease is added, etc., environmental factor organized data can be generated in which newly discriminated environmental factor data is acquired by the discrimination unit 5 from all environmental factor data stored in the first data storage unit 60.

[0050] Furthermore, for example, by installing the environmental sensor device 1 in an evacuation shelter during a disaster, the environmental factor sorting data selectively determined and acquired by the determination unit 5 based on the degree of influence on illnesses such as heat stroke, sleep disorders, and mental health stored in the second data storage unit 61 can be output and used for analysis to meet the urgent requirement of maintaining an appropriate indoor environment, and after the emergency is no longer an issue due to the closure of the evacuation shelter, it is also possible to verify the appropriateness of the emergency response by reanalyzing all the environmental factor data stored in the first data storage unit 60. Furthermore, by uploading all the environmental factor data stored in the first data storage unit 60 to an external network such as the cloud, it can be used as part of big data for medical elucidation and technology development.

[0051] In addition, since the environmental factor summary data includes environmental factor data that is selectively determined for each disease, it is easy to analyze the relationship between diseases and environmental factors based on the environmental factor summary data.

[0052] Furthermore, since the environmental factor summary data includes environmental factor data ranked for each disease, it is easy to analyze the environmental factors that have a large impact on a disease based on the environmental factor summary data.

[0053] Furthermore, since the ranking is performed by the discrimination unit 5, various relationships between the disease and the environmental factor data can be obtained based on the ranking, not limited to the examples of ranking in Figures 3 to 5. Although an example of storing data in the form of a sheet in the second data storage unit 61 as shown in Figures 3 to 7 has been shown, data may be stored in a form other than a sheet.

[0054] Although the embodiments of the present invention have been described above with reference to the drawings, the specific configuration is not limited to these embodiments, and the present invention also includes modifications and additions that do not deviate from the gist of the present invention.

[0055] For example, in the above embodiment, the environmental sensor device 1 is described as having a built-in computer system equipped with a data storage unit 2, a discrimination unit 5, etc., but this is not limited to the above. By connecting the environmental sensor device to an external network such as the cloud and having it perform learning, etc. using edge computing technology, it is also possible to selectively discriminate environmental factor data including potential effects that are complexly related to various diseases, etc. from a larger amount of research data and environmental factor data, and acquire the data.

[0056] In addition, in the above embodiment, an example was described in which one second data storage unit 61 is provided to store environmental factor sorting data, but this is not limited to the above. For example, multiple second data storage units may be provided so that environmental factor sorting data can be allocated and stored for each personal attribute set in the condition setting unit 4.

[0057] In addition, the environmental sensor device 1 can be used by a doctor to diagnose a patient in combination with information on personal attributes such as body temperature, heart rate, blood pressure, facial expression, voice, and behavior measured by other biosensors, making it possible to make diagnosis through digital interviews more efficient. [Explanation of symbols]

[0058] 1. Environmental sensor device 2 Data storage unit (storage means) 3. Measurement unit (sensing means) 4 Condition setting section 5 Discrimination unit (discrimination means) 6 Data Storage Section 60 First data storage unit (first storage means) 61 Second data storage unit (second storage means)

Claims

1. A storage means for storing an influence level, which is the degree of influence of an environmental factor on a disease, for each disease; A sensing means for measuring a plurality of environmental factor data; and a discrimination means for selectively discriminating at least one of the plurality of environmental factor data measured by the sensing means based on the degree of influence.

2. 2. The sensor system according to claim 1, wherein the determining means performs the determination based on personal attributes and lifestyle conditions and the degree of influence.

3. a first storage means for storing the environmental factor data measured by the sensing means; 3. The sensor system according to claim 1, further comprising: a second storage means for storing environmental factor sorting data including the environmental factor data selectively determined by the determination means.

4. The sensor system according to claim 3 , wherein the environmental factor summary data includes the environmental factor data selectively determined for each of the diseases.

5. The sensor system according to claim 3 , wherein the environmental factor organized data includes the environmental factor data ranked for each of the diseases.

Images