Prediction and mitigation of the impacts of environmental conditions

Abstract

This invention provides a system and method for predicting and mitigating the impact of environmental conditions. [Solution] The system includes a user device, the user device includes a processor and memory, the processor and memory perform the following steps: 2202 to identify environmental conditions at a location in the environment; 204 to analyze the environmental conditions in light of individual-specific criteria; 206 to determine the predicted impact on an individual at that location while the identified environmental conditions are present; and 208 to generate a mitigation response based on the predicted impact.

Description

Technical Field

[0001] The present disclosure generally relates to systems and methods for mitigating the effects of environmental conditions.

Background Art

[0002] Exposure to environmental conditions can have harmful effects on humans, plants, animals, and equipment. For example, humans or animals exposed to heat and humidity can exhibit heat stress symptoms or other biological symptoms, especially while engaged in activities such as walking, running, etc. Heat stress and exhaustion typically cause physical symptoms such as sweating, weakness, dizziness, fainting, nausea, muscle cramps, headache, rapid heartbeat, etc. Similarly, plants can wilt, become stunted, and are more likely to become diseased or even die. Equipment can overheat and malfunction.

[0003] Current systems and methods for managing environmental exposure are inadequate in various respects. For example, as a current method, it may be possible to issue a general heat advisory to a wide area or the entire population, but this assumes that one approach is sufficient. Furthermore, existing systems also issue warnings about the effects of environmental condition exposure after the fact of the environmental conditions, which is too late to avoid the effects.

Summary of the Invention

Means for Solving the Problems

[0004] In one embodiment, a method for predicting the effects of environmental exposure includes receiving, by a processor, environmental data of environmental conditions; predicting, by the processor, the biological effects of the environmental conditions on a user; and generating a notification regarding the predicted biological effects.

[0005] Optionally, in some embodiments, the method further includes receiving, by the processor, an activity plan of a user exposed to the environmental conditions.

[0006] Optionally, in some embodiments, the method further includes the step of adjusting the activity plan in the processor to prevent biological effects.

[0007] In some embodiments, optionally, the prediction is based on at least one of the user's biological characteristics and / or the user's activity schedule.

[0008] Optionally, in some embodiments, the processor is located onboard the mobile device.

[0009] In some embodiments, the environmental data may optionally include at least one of current environmental conditions or predictions of future environmental conditions.

[0010] Optionally, in some embodiments, the method further includes the step of the processor receiving the user's tolerance to environmental conditions.

[0011] Optionally, in some embodiments, the method further includes the step of the processor generating a user alert indicating the imminent impact of exposure to environmental conditions.

[0012] Optionally, in some embodiments, the method further includes the steps of: sending a coordinated activity plan to a user device using a processor; and displaying the coordinated activity plan on the user device's display.

[0013] Optionally, in some embodiments, the method further includes the step of the processor receiving user health data from the user device.

[0014] Optionally, in some embodiments, the user device includes a wearable device.

[0015] In some optional embodiments, the processor is associated with a user device, and the activity plan is stored in the user device's memory.

[0016] Optionally, in some embodiments, the environmental data includes one or more of the following: temperature, thermal exposure index, solar radiation, wind speed, wind direction, cloud cover, atmospheric pressure, precipitation, wind-induced cooling, dew point, humidity, atmospheric electric field, wind shear, cumulative radiation dose, or levels of pollutants.

[0017] Optionally, in some embodiments, the contaminant is one or more of particulate matter, nitrogen and oxygen compounds, sulfur compounds, ozone, hydrocarbons, carbon dioxide, or carbon monoxide.

[0018] In one embodiment, a method for predicting the effects of environmental exposure includes the steps of: identifying environmental conditions at a location within the environment; analyzing the environmental conditions against individual-specific criteria to determine the predicted effects on an individual at that location while the identified environmental conditions are present; and generating a mitigation response based on the predicted effects.

[0019] Optionally, in some embodiments, the method further includes the step of outputting a relaxation response to a display associated with a user device accessible from the individual.

[0020] Optionally, in some embodiments, the individual is a human, an animal, or a plant.

[0021] Optionally, in some embodiments, the individual-specific criteria include activity or the path taken through that location.

[0022] Optionally, in some embodiments, individual-specific criteria include biological characteristics associated with the individual.

[0023] In one embodiment, it is a system that predicts and mitigates the impact of environmental conditions. This system includes a user device, the user device includes a processor and a memory, and the processor and the memory are configured to perform the steps of identifying the environmental conditions at a location within an environment, analyzing the environmental conditions in light of individual-specific criteria to determine the predicted impact on an individual within that location while the identified environmental conditions exist, and generating a mitigation response based on the predicted impact.

[0024] Optionally, in some embodiments, the processor and the memory are further configured to perform the step of outputting the mitigation response to a display associated with the user device accessible by the individual.

[0025] Optionally, in some embodiments, the individual is any one of a human, an animal, or a plant.

[0026] Optionally, in some embodiments, the individual-specific criteria include an activity or a route through the location.

[0027] Optionally, in some embodiments, the individual-specific criteria include biological characteristics associated with the individual.

Brief Description of the Drawings

[0028] [Figure 1] A simplified schematic diagram of a system for predicting and mitigating the impact of environmental conditions according to the embodiments described herein is shown. [Figure 2] An example of a method for predicting and mitigating the impact of environmental conditions implemented by the system of FIG. 1 according to the embodiments described herein is shown. [Figure 3] An example of the method of FIG. 2 according to the embodiments described herein is shown, where the system may analyze environmental data and, optionally, further analyze one or more user characteristics. [Figure 4A] An example of the method of FIG. 2 for generating treatment and / or mitigation options is shown. [Figure 4B] Figure 2 shows an example of a method for generating treatment and / or palliative options. [Figure 5] Figure 2 shows an example of the method according to the embodiments described herein, in which the system can notify the user when the exposure threshold is approaching. [Figure 6] Figure 1 shows a simplified block diagram of the components of the computing system for predicting and mitigating the effects of environmental conditions, according to embodiments described herein. [Modes for carrying out the invention]

[0029] Embodiments disclosed herein enable the prediction of environmental exposure to humans, animals, equipment, infrastructure, and / or plants, and the activation of options to mitigate such environmental exposure. Since prediction and mitigation can be performed on an individual basis, accuracy and responsiveness can be improved. Examples of environmental conditions used for prediction include temperature, humidity, ultraviolet (UV) exposure, air pollution (e.g., smoke, allergens), wind, altitude, ozone exposure, wind speed, water activity velocity or wave height, topography, cloud cover, precipitation, elevation, and season (e.g., summer, winter, dry season, or rainy season). Environmental conditions are analyzed based on the actual or predicted location of humans (or other individuals) (e.g., location detection, user input, etc.). The method is configured to analyze various types of data from changing or non-static environments (typically outdoors), including both terrestrial and aquatic environments. These data, along with optional, user- or individual-specific data, are used to predict exposure thresholds (e.g., when heat stress is likely to begin, maximum exposure time, time of exhaustion). User- or individual-specific data may include activity itineraries (e.g., work schedules, travel information, training plans, race trajectories, etc.) and / or biological information (e.g., heart rate, blood glucose, respiratory rate, prior exposure, medical history (i.e., tolerance information), recent meals, etc.). In some examples, optional user- or individual-specific data may include further user-specific information regarding biological and / or psychological thresholds, such as tolerance to noise, tolerance to very crowded places, tolerance to flashlight, and / or tolerance to exposure to new stimuli in the environment. Predictions may be determined before the activity begins (for example, to allow for changes to a particular itinerary before the scheduled time (e.g., to allow for scheduling additional breaks or indoor activities)) and / or in real time to allow for notifications to prevent entering an undesirable biological state.

[0030] Furthermore, in some cases, the effects of exposure to environmental conditions may be reset or reduced, where a biological system (e.g., the human body) has the opportunity to recover from a particular impact. For example, if a person interrupts their running activity and rests in the shade with a fan or in an air-conditioned room, or if their heart rate decreases, they may be able to continue running in the sun for a longer period or distance than if they had not rested. Various examples incorporate such changing factors into the impact, both when making predictions about a particular journey or schedule and when providing real-time feedback.

[0031] The systems and methods described herein predict environmental conditions, including the effects of those conditions (particularly cumulative effects). By predicting the effects of exposure to environmental conditions, the systems can adjust action plans to help avoid or mitigate those effects. The systems can also generate notifications of impending exposure limits, enabling individuals to take protective action before they face a problem.

[0032] Various embodiments help identify and prevent excessive exposure in specific environments, enabling a variety of activities to be carried out more comfortably and with less harm. This can allow construction workers, athletes, travelers, and others to maintain their desired activity schedules more efficiently, enjoyably, and productively, even under harsh environmental conditions such as hot and humid summer days.

[0033] While many examples are described in relation to humans, it should be noted that these are equally applicable to other living systems (including animals, plants, and others) that face similar physiological problems when faced with specific environmental conditions (e.g., plants wilting in heat). Similarly, certain foods, equipment, and inanimate objects may have thresholds of effects that can be predicted and mitigated using these embodiments. Therefore, any description of a specific example should be considered illustrative only.

[0034] Referring to the drawing, Figure 1 shows a simplified schematic diagram of System 100, which predicts the effects of environmental conditions and, optionally, enables the mitigation of those effects. System 100 analyzes environmental conditions to predict and mitigate the effects of prolonged exposure of an individual (e.g., a user) to various environmental conditions. System 100 predicts exposure thresholds or time periods. For example, it predicts when heat stress is likely to begin, when exhaustion may occur, or when aerobic performance may decline. The prediction may be made before the activity begins (this is to allow, for example, to change a particular itinerary before a set time (e.g., to schedule additional breaks or indoor activities)) and / or can provide real-time notifications to prevent entering undesirable biological states while the activity is taking place (for example, it is possible to generate an alert that taking a break may be beneficial in reducing heat stress).

[0035] System 100 includes a server 102 and a user device 106 (for example, a computing device that a user 108 can interact with, such as a telephone, tablet, smartwatch, head-mounted display, or other wearable device, laptop, or desktop computer), a network 104, and one or more environmental characteristics databases or sensors, the environmental characteristics databases or sensors being, for example, local environmental sensors 110 (for example, temperature sensors, humidity sensors, etc.) and weather data 112 (including forecasts 114 and regional environmental data 116).

[0036] In some examples, network 104 receives environmental conditions or characteristics, which are, for example, weather data 112 for a place where user 108 is going, or where user 108 is currently active, or where user 108 is currently located, and which include current and / or future weather information (e.g., forecast 114 and local environmental data 116). Weather data 112 may include, for example, current temperature, predicted future temperature and temperature change throughout the day, current and / or predicted future precipitation, current and / or predicted future ultraviolet (UV) index, humidity, atmospheric pressure, solar radiation, wind speed, wind direction, cloud cover, atmospheric pressure, precipitation, wind temperature, dew point, humidity, atmospheric electric field, wind shear, cumulative dose, pollution level, air quality, smoke index, altitude, and air pollution or contamination (e.g., amounts of particulate matter, nitrogen and oxygen compounds, sulfur compounds, ozone, hydrocarbons, carbon dioxide, or carbon monoxide). Naturally, this is not an exhaustive list, and weather data112 may include various types of relevant environmental data for the present and / or predicted future.

[0037] Furthermore, the network 104 may receive local environmental conditions from the local weather sensor 110. The local environmental conditions received from the local weather sensor 110 can be more detailed for a specific location than the weather data 112, which may apply to a wider area. For example, at a place where user 108 will be active or is currently located (e.g., a workplace, an outdoor sports facility, a garden, an outdoor shopping center), there may be local weather instruments such as a barometer, anemometer, thermometer, hygrometer, rain gauge, or radar that can provide detailed environmental conditions or characteristics for the specific location where user 108 is located.

[0038] Optionally, in some examples, the user device 106 may include user or individual-specific data (e.g., activity itinerary (e.g., work schedule, travel information, etc.) and / or biological information (e.g., heart rate, respiratory rate, prior exposure or tolerance information, medical history, etc.)). In some examples, the user or individual-specific data may be received from, for example, onboard sensors, third-party databases (e.g., work schedule, travel agency, doctor), and / or from input received from user 108. The system 100 can use its optional user or individual-specific data to predict and mitigate the effects of environmental conditions and / or environmental characteristics.

[0039] System 100 can make predictions regarding exposure thresholds (for example, when heat stress is likely to begin) based on received weather data 112, local environmental conditions from local weather sensors 110, and / or optional user or individual-specific data. System 100 may make such predictions onboard or offboard the user device 106.

[0040] In some cases, system 100 can also generate therapeutic and / or mitigation options to help the user never exceed an exposure threshold. These generated therapeutic and / or mitigation options can help reset the biological effects caused by exposure to environmental conditions and / or environmental characteristics, thereby reducing the effects of those conditions and / or characteristics. For example, these therapeutic and / or mitigation options may take the form of predictive alerts or plans to help extend exposure time (e.g., sitting under a tree for 10 minutes when approaching the sun exposure threshold reduces biological exertion, heart rate, etc.).

[0041] System 100 may output a prediction that the user is approaching an exposure threshold, and in some examples, it may output the generated treatment and / or mitigation options to user 108 via user device 106. For example, user device 106 may receive information from system 100 (e.g., from a device via network 104) that the user is expected to exceed the sun / heat exposure threshold if exposure to sunlight / heat lasts for a certain duration, and notify user 108. In some examples, user 108 may be advised via user device 106 to seek shade to avoid sunlight or to wear protective gear against sunlight / heat. In another example, user 108 may be advised to move to a quieter location or to wear hearing protection when exposure to noise may be approaching the noise exposure threshold due to exposure for a certain duration. In yet another example, user 108 may be provided with optional pre-scheduled itinerary changes / updates via user device 106 to avoid approaching predicted exposure thresholds that the user might encounter if the original itinerary were carried out without modification / updates. In some examples, some of the optional itinerary changes may be approved / accepted by user 108, while other parts of the optional itinerary changes may be rejected by user 108.

[0042] System 100 may also send predictions regarding the exposure threshold to Server 102 for storage. Similarly, System 100 may send treatment and / or mitigation options to Server 102 for storage if they are generated. In some examples, previously stored predictions may be transferred to Network 104 or User Device 106 for use in future exposure threshold predictions in order to predict more accurately when User 108 may exceed the exposure threshold. Similarly, stored mitigation options may be transferred to Network 104 or User Device 106 for use in future mitigation option generation. As a result, predictions of approaching the exposure threshold and generated mitigation options may be optimized based on previous predictions and generated mitigation options.

[0043] Furthermore, in some examples, the prediction and mitigation options stored in server 102 may be used to include and / or exclude environmental features. For example, if the prediction and mitigation options stored in server 102 indicate that system 100 has made numerous predictions that user 108 is likely to approach the heat exposure threshold in a particular location and / or environment, then it may be beneficial to add mitigation features (e.g., shade, water dispensers, misting systems, benches, indoor enclosures, rest areas) to prevent future user 108 from approaching the heat exposure threshold in the aforementioned location.

[0044] While the examples described so far detail a user 108 interacting with user device 106, this disclosure is also applicable to any other entities that may be exposed to environmental conditions and characteristics and that may result in biological effects as a result of exceeding an exposure threshold, such as plants, animals, transport infrastructure, and any other entities. Various functions may be performed by one or more devices within the system; for example, user device 106 or server 102 may receive user information and weather information to make predictions, and any description of any particular device performing a particular operation is illustrative only.

[0045] Figure 2 shows an example of a method 200 for predicting and mitigating the effects of environmental conditions, as implemented by System 100 according to embodiments described herein. While Method Example 200 shows a specific sequence of operations, this sequence is modifiable without departing from the scope of the disclosure. For example, some of the operations described may be performed in parallel or in a different sequence that does not substantially affect the functionality of Method 200. In some examples, Method 200 may be performed by a single device, and in other examples, Method 200 may be distributed across multiple different devices (e.g., Server 102, User Device 106, and / or Network 104), each of which implements some or all of Method 200. In some examples, Method 200 may be performed by multiple different components of an exemplary device of System 100 implementing Method 200. In some examples, each operation of Method 200 may be performed approximately simultaneously or in a specific sequence.

[0046] Method 200 may be initiated by the system 100 identifying environmental data in operation 202. For example, in operation 202, the network 104 may receive weather data 112 and / or local weather information from the local weather sensor 110 to identify environmental data and / or environmental conditions for the place where the user is about to be located or will be active.

[0047] Method 200 may proceed to operation 204, in which the system 100 may analyze environmental data and, optionally, analyze one or more user characteristics. For example, in operation 204, the network 104 may analyze weather data 112, local weather information from local weather sensors 110, and optionally, user or individual-specific information to identify environmental conditions and / or environmental characteristics that user 108 may encounter.

[0048] Method 200 may proceed to operation 206, in which system 100 may predict one or more biological effects of environmental conditions and / or environmental characteristics on user 108. For example, in operation 206, system 100 may predict an exposure threshold for user 108 based on environmental conditions and / or environmental characteristics, and exceeding the exposure threshold may lead to a biological effect for user 108 (e.g., heatstroke when the heat exposure threshold is reached).

[0049] Method 200 may proceed to Operation 208, in which System 100 may generate treatment and / or mitigation options to prevent exceeding exposure thresholds corresponding to the biological effects of environmental characteristics. For example, in Operation 208, System 100 may generate treatment and / or mitigation options to prevent exceeding predicted exposure thresholds. In some examples, treatment and / or mitigation options may take the form of recommending to the user to wear sun protection or seek shade when approaching a sun and / or heat exposure threshold, to wear noise-reducing headphones when approaching a noise exposure threshold, or to rearrange the order of the itinerary or rearrange the events of the itinerary so that they occur earlier in the day if System 100 determines that continuing the itinerary as is may bring the user closer to some exposure threshold.

[0050] Method 200 may proceed to Operation 210, in which the system 100 may notify user 108 that it is approaching an exposure threshold. In some examples, the system 100 may notify user 108 via user device 106 of generated treatment and / or mitigation options to prevent exceeding the approaching exposure threshold. For example, in Operation 210, the system 100 may notify user 108 via user device 106 that it is approaching an exposure threshold and, in some examples, of possible treatment and / or mitigation options. In some examples, user 108 may refuse the optional treatment and / or mitigation options. In some such examples, even if user 108 refuses the optional treatment and / or mitigation step, the system 100 may, in some cases, notify user 108 that it is approaching an exposure threshold. In some other examples, user 108 may only be notified that it is approaching an exposure threshold, and no treatment and / or mitigation step is recommended. In another example, the prediction may be provided to the user device, or the data for generating the prediction and the user device may be used (for example, through a health or activity application on the device) to generate alerts and notifications, as well as recommended actions. In these examples, the user device may also include historical data (e.g., biological information, heart rate, etc.), which can be used to generate more accurate, user-specific predictions and recommendations.

[0051] In some examples, method 200 may revert to operation 202, where system 100 may repeat method 200 by re-identifying environmental data for the user's location. For example, system 100 may perform method 200 continuously to notify user 108 whenever it is approaching an exposure threshold, because environmental conditions can change throughout the day (e.g., temperature changes, humidity changes, UV index changes, air pollution changes). In some other examples, the biological effects of exposure may be reset when user 108 adopts one or more of the various treatment or mitigation options, or implements its own treatment or mitigation options not provided by system 100, and system 100 may again predict whether user 108 is approaching or will approach any exposure threshold.

[0052] Figure 3 shows an example of method 200 according to an embodiment described herein, in which system 100 may analyze environmental data and optionally analyze one or more user characteristics.

[0053] In some examples of Method 200, System 100 may analyze environmental data on User Device 106 and, optionally, analyze user or individual-specific information. For example, User Device 106 may include user tolerance 302 to various environmental conditions and / or environmental characteristics (e.g., from onboard sensors of User Device 106, from third-party databases (e.g., work schedules, travel agencies, doctors), and / or from inputs received from User 108). Naturally, User 108 may express that they do not want to provide any user or individual-specific information.

[0054] As shown in Figure 3, the system 100 may optionally be provided with user- or individual-specific information that includes the user's tolerance to various environmental conditions and / or environmental characteristics used in predicting exposure thresholds. For example, the system 100 may be provided with user- or individual-specific information indicating that the user may have high tolerance to heat exposure 304, high tolerance to humidity exposure 306, moderate tolerance to noise, low tolerance to air pollution exposure 310, and high tolerance to sunlight exposure 312. Based to some extent on tolerance, the system 100 may predict that user 108 may approach the air pollution exposure 310 threshold sooner than the heat exposure 304 threshold, humidity exposure 306 threshold, noise exposure 308 threshold, and sunlight exposure 312 threshold (if exposed to such environmental conditions). Furthermore, in some examples, if the system 100 has received user- or individual-specific information that user 108 may have a lower tolerance to air pollution exposure 310, it may generate and provide treatment and / or mitigation options to reduce air pollution exposure 310.

[0055] Figure 4A shows an example of the method in Figure 2 for generating treatment and / or palliative options.

[0056] Consider an example where user 108 plants flowers in a garden. System 100 may be given an initial activity plan 402 that user 108 can perform, which is set on user device 106. This plan includes digging a hole at 10am 404, planting at 11am 406, taking a break at noon 408, and cleaning up at 1pm 410. According to embodiments described herein, system 100 may predict that if user 108 performs activity plan 402 in its current form, it may exceed the sun exposure threshold and the heat exposure threshold. This is because user 108 may be digging a hole 404, planting 406, and cleaning up 410 when the sun exposure is strong and user 108 may be exposed to high / rising temperatures.

[0057] Figure 4B shows an example of the method of Figure 2 for generating treatment and / or mitigation options. In some embodiments, system 100 may generate an updated activity plan 412 that mitigates heat / sun exposure. System 100 may notify user 108 via user device 106 that the exposure threshold may be approached if the original activity plan 402 is carried out, and in some examples, the updated activity plan 412 may be provided to user 108 via user device 106. It is optional for user 108 to accept and carry out the updated activity plan 412 (or accept only a part of it). The updated activity plan 412 may include digging a hole at 7am 414, planting at 8am 416, cleaning up at 9am 418, and resting at 10am 420. As a result, the updated activity plan 412 can limit the user's exposure to sunlight and heat. This is because the updated activity plan 412 is implemented early in the day while temperatures are still low and sunlight exposure is still weak. The updated activity plan 412 can reduce the likelihood of exceeding the heat exposure threshold and / or sunlight exposure threshold, thereby reducing the likelihood of causing the biological effects of exceeding the exposure threshold.

[0058] In some cases, user 108 may reject the updated activity plan 412 and carry out activity plan 402 as originally set out. Even in such cases, user 108 may be notified while carrying out activity plan 402 that they may soon approach a predicted exposure threshold (e.g., sun exposure and / or heat exposure) and that treatment and / or mitigation steps should be taken to prevent exceeding the exposure threshold.

[0059] Figure 5 shows an example of operation 210 of method 200 according to an embodiment described herein, in which system 100 can notify user 108 that it is approaching an exposure threshold.

[0060] In some embodiments, the system 100 can predict that user 108 may be approaching an exposure threshold and can generate treatment and / or mitigation options to mitigate approaching the exposure threshold. The system 100 can also notify the user (502) of the predicted exposure threshold and the generated treatment and / or mitigation options. For example, user 108 may be notified (502) via user device 106 with "You are approaching your exposure limit" and "Find some shade and cool down." In some examples, the user may ignore the notification and refuse to implement the treatment and / or mitigation options.

[0061] Some specific examples of the methods and systems described herein consider a scenario in which a user works outdoors in a workplace. First, the user may optionally input their tolerance to various environmental conditions (e.g., sunlight exposure, humidity, heat, etc.) into a user device. Next, embodiments described herein can predict that, due to predicted increased sunlight and heat exposure (e.g., based on local environmental conditions, forecasts, and optional user data), the user may approach a heat exposure threshold at a specific time (e.g., 1 p.m.). Various mitigation options may be generated to prevent the user from exceeding the heat exposure threshold. For example, the user may be advised to reduce work intensity, take a break, drink water, and / or work in a shaded area of ​​the workplace. The user may then be notified that they are approaching the exposure threshold and to offer mitigation options. In some examples, the user may choose to implement the mitigation options or refuse to implement them, but may still be reminded that they are approaching the exposure threshold if they refuse. Optionally, the prediction that an exposure threshold is approaching and recommendations for mitigation options may be communicated to the user's supervisor or workplace manager, who may recommend that the user take a break and schedule another user to cover their workplace during the user's break, in order to ensure a high level of work efficiency and results while ensuring worker safety (i.e., preventing the user from suffering biological effects by exceeding the exposure threshold).

[0062] Consider an example where plants grow under the supervision of a farmer in a location with unstable weather. According to the embodiments described herein, based on local weather data indicating an unexpected rise in sunlight and / or heat, it may be predicted that plants may approach the heat exposure threshold in the afternoon, and as a result, may wilt and / or die. Mitigation options may be generated, such as covering the plants or watering them. Farmers may be notified that the plants are approaching the heat exposure threshold and of the generated mitigation options in order to prevent the plants from wilting and dying.

[0063] Consider an example where a user goes to an amusement park. Initially, the user may create an itinerary that includes the order in which rides are taken, as well as the timing of meals and / or breaks, or optionally, may be given such an itinerary. According to embodiments described herein, it may be predicted that by following the initially set / provided itinerary, the user may approach, and even exceed, an air pollution exposure threshold (e.g., due to smoke from a nearby wildfire). The user may be notified of the possibility of exceeding the air pollution exposure threshold and may be recommended an updated itinerary that mitigates the air pollution exposure threshold (e.g., an itinerary that includes taking breaks and enjoying indoor rides). The user may accept or reject the updated itinerary (or accept or reject parts of the updated itinerary). Optionally, the user may provide user data (e.g., tolerance to specific exposures) so that a better-fitting updated itinerary that avoids approaching any exposure threshold is recommended.

[0064] Consider an example where frozen food is transported nationwide by trailer truck. According to embodiments described herein, frozen food being transported by trailer truck may be at risk of thawing because it may approach the melting threshold if the trailer truck's current navigation causes it to become stuck in traffic in hot weather. Mitigation options may be generated for the trailer truck driver (or the trailer truck driver's dispatcher), which may include, for example, choosing a less congested route, a cooler or more shaded route, or unloading the frozen food at a nearby facility and waiting until the unfavorable conditions have passed. The trailer truck driver (or the trailer truck driver's dispatcher) may be notified of the prediction that the melting threshold is approaching and the recommended mitigation options. The trailer truck driver may implement one or more of these mitigation options, or may reject them (if rejected, they will still be notified that the melting threshold is approaching).

[0065] Consider the example of athletes conducting preseason training in the summer. According to the embodiments described herein, a particular group of athletes may be predicted to approach their sun and / or heat exposure thresholds if they have a lower tolerance to heat and sun exposure (compared to other athletes). As a result, a coach, medical supervisor, or the athlete themselves may be notified that the athlete is approaching their sun / heat exposure threshold at a particular time of day. For example, the athlete may be advised to reduce the training intensity to allow them to complete the training session, take breaks to drink water, or train in a climate-controlled environment while environmental exposure is at a high level. Advantageously, this makes it possible to mitigate any biological effects that may occur during training while approaching the heat and sun exposure thresholds (e.g., fainting and / or heat stress).

[0066] Figure 6 is a simplified block diagram of the components of the computing system 600 of system 100 (e.g., server 102, local weather sensor 110, user device 106, etc.). For example, the processing element 602 and the memory component 608 may be present in one or more computing systems 600. This disclosure assumes any appropriate number of such computing systems 600. For example, server 102 may be a desktop computing system, a mainframe, a blade, a mesh of computing systems 600, a laptop or notebook computing system 600, a tablet computing system 600, an embedded computing system 600, a system-on-a-chip, a single-board computing system 600, or a combination of two or more of these. The computing system 600 may, as necessary, include one or more computing systems 600, may be standalone or distributed, may span multiple locations, may span multiple machines, may span multiple data centers, or may be in a cloud which may include one or more cloud components in one or more networks. The computing system 600 may include one or more processing elements 602, an input / output (I / O) interface 604, one or more external devices 612, one or more memory components 608, and a network interface 610. Each of the various components may communicate with one or more buses or communication networks (e.g., wired or wireless networks) (e.g., network 104). The components in Figure 6 are for illustrative purposes only. In various examples, the computing system 600 may include further components and / or functionalities not shown in Figure 6.

[0067] The processing element 602 may be any type of electronic device capable of processing, receiving, and / or transmitting instructions. For example, the processing element 602 may be a central processing unit, a microprocessor, a processor, or a microcontroller. Furthermore, it should be noted that some components of the computing system 600 may be controlled by the first processing element 602, and some other components may be controlled by the second processing element 602, and the first and second processing elements may or may not communicate with each other.

[0068] The I / O interface 604 allows the user to input data into the computing system 600 and further enables the input and output of the computing system 600 to communicate with other devices or services. The I / O interface 604 may include one or more input buttons, a touchpad, a touchscreen, or the like.

[0069] The external device 612 is one or more devices that can be used to provide various inputs to the computing system 600, such as a mouse, microphone, keyboard, trackpad, or sensing element (e.g., a thermistor, humidity sensor, photodetector, etc.). The external device 612 may be located locally or remotely and may vary as needed. In some examples, the external device 612 may include one or more additional sensors.

[0070] The memory component 608 is used by the computing system 600 to store instructions for the processing element 602, and to store data (for example, weather data 112 including forecast 114 and local environmental data 116). The memory component 608 may be, for example, magneto-optical storage, read-only memory, random-access memory, erasable programmable memory, flash memory, or a combination of one or more types of memory components.

[0071] The network interface 610 enables communication to and from the computing system 600. The network interface 610 includes one or more communication protocols, such as, but not limited to, Wi-Fi, Ethernet, and Bluetooth. The network interface 610 may also include one or more wired components, such as a Universal Serial Bus (USB) cable. The configuration of the network interface 610 may be modified to communicate using Wi-Fi, Bluetooth, etc., depending on the desired type of communication.

[0072] The display 606 provides the visual output of the computing system 600 and may vary as required by the device. The display 606 may be configured to provide visual feedback to the user 108 and may include a liquid crystal display screen, a light-emitting diode screen, a plasma screen, etc. In some examples, the display 606 may be configured to act as an input element for the user 108, such as through touch feedback.

[0073] All descriptions of specific components that are part of a particular embodiment are intended to be illustrative only and should not be interpreted as requiring their use in conjunction with that particular embodiment or as requiring other elements shown in the illustrated embodiment.

[0074] All relative and directional references (top, bottom, side, front, rear, etc.) are provided as examples to aid the reader in understanding the examples described herein. They should not be interpreted as requirements or limitations, particularly with respect to position, orientation, or use, unless otherwise specifically stated in the claims. References of connection (e.g., attached, joined, connected, joined, etc.) should be interpreted broadly, and there may be intervening members between connections between elements and between relative movements of elements. Thus, references of connection do not necessarily imply that two elements are directly connected and in a fixed relationship with one another, unless otherwise specifically stated in the claims.

[0075] The teachings in this disclosure are illustrative and not limiting. Accordingly, matters included in the above description or shown in the accompanying drawings should be construed as illustrative, not limiting. The following claims are intended to encompass all the comprehensive and specific features described herein, as well as all statements regarding the scope of the methods and systems of the present invention, and, in terms of wording, may fall somewhere between them.

Claims

1. A method for predicting the effects of environmental exposure, The processor receives environmental data of environmental conditions, The processor includes the steps of predicting the biological effects of the environmental conditions on the user, The steps include generating a notification regarding the predicted biological effects, A method that includes this.

2. The method according to claim 1, further comprising the step of the processor receiving a user activity plan to be exposed to the environmental conditions.

3. The method according to claim 2, further comprising the step of adjusting the activity plan in the processor to prevent the biological effects.

4. The method according to claim 1, wherein the prediction is based on at least one of the user's biological characteristics and / or the user's activity schedule.

5. The method according to claim 1, wherein the environmental data includes at least one of current environmental conditions or predictions of future environmental conditions.

6. The processor receives the user’s tolerance to the environmental conditions. The method according to claim 1, further comprising:

7. The processor generates a user alert indicating the imminent impact of exposure to the environmental conditions. The method according to claim 1, further comprising:

8. The processor performs the steps of sending the adjusted activity plan to the user device, The steps include displaying the adjusted activity plan on the user device's display, The method according to claim 1, further comprising:

9. The processor then performs the step of receiving user health data from the user device. The method according to claim 1, further comprising:

10. The method according to claim 9, wherein the processor is associated with a user device and an activity plan is stored in the memory of the user device.

11. The data for the aforementioned environment is Temperature, thermal exposure index, solar radiation, wind speed, wind direction, cloud cover, atmospheric pressure, precipitation, wind-induced cooling, dew point, humidity, atmospheric electric field, wind shear, cumulative radiation dose, or level of pollutants. The method according to claim 1, comprising one or more of the following.

12. The method according to claim 11, wherein the pollutant is one or more of particulate matter, nitrogen and oxygen compounds, sulfur compounds, ozone, hydrocarbons, carbon dioxide, or carbon monoxide.

13. A method for predicting the effects of environmental exposure, Steps include identifying the environmental conditions of a specific location within the environment, A step of analyzing the environmental conditions in light of individual-specific criteria and determining the predicted impact on the individual within the location while the identified environmental conditions are present, The steps include generating a mitigation response based on the predicted impact, A method that includes this.

14. The method according to claim 13, further comprising the step of outputting the relaxation response to a display associated with a user device accessible from the individual.

15. The method according to claim 13, wherein the individual is a human, an animal, or a plant.

16. The method according to claim 13, wherein the individual-specific criteria include activity or a path through the location.

17. A system that predicts and mitigates the impact of environmental conditions, A user device including a processor and memory, wherein the processor and memory are A step of identifying the environmental conditions at a certain location within the environment, A step of analyzing the environmental conditions in light of individual-specific criteria and determining the predicted impact on the individual within the location while the identified environmental conditions are present, The steps include generating a mitigation response based on the predicted impact, The user device is configured to perform the following actions: A system that includes this.

18. The system according to claim 17, wherein the processor and the memory are further configured to perform the step of outputting the relaxation response to a display associated with a user device accessible from the individual.

19. The system according to claim 17, wherein the individual is a human, an animal, or a plant.

20. The system according to claim 17, wherein the individual-specific criteria include biological characteristics associated with the individual.

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