Patent Application
20160070273
This invention relates to disease prevention, and more particularly to integrated systems for preventing diseases using artificial soil.
Recent scientific developments indicate that the increased incidence of allergic diseases among children in current generation is a consequence of the increased cleanliness of their environment as babies. For example, the hygiene hypothesis states that the increased prevalence of autoimmunity and allergic diseases in affluent, industrialized countries may be attributed to decreased exposure to dirt and infectious agents.
Accordingly, one example aspect of the present invention is a method for determining soil composition for preventing allergic diseases. The method includes providing a computer network that communicates with health sensors and environmental sensors. The method includes providing environmental sensors in a first geographic region to measure environmental conditions of the first geographic region. The method also includes providing health sensors for a sample human population in the first geographic region to measure health conditions of the sample human population. The method also includes computing a soil model that prevents allergic diseases based on the environmental conditions and the health conditions, and synthesizing artificial soil that replicates the computed soil model.
Another example aspect of the present invention is a system for determining soil composition for preventing allergic diseases. The system includes a computer network and a plurality of environmental sensors in a first geographic region to measure environmental conditions of the first geographic region. The environmental sensors are in communication with the computer network. A plurality of health sensors for a sample human population in the first geographic region measure health conditions of the sample human population. The health sensors are also in communication with the computer network. A computer processor computes a soil model that prevents allergic diseases based, on the environmental conditions and the health conditions. The computer processor is in communication with the computer network. The system further includes artificial soil that replicates the computed soil model.
Yet another example aspect of the present invention is an artificial soil spray system for prevention of allergic diseases. The system includes a pressurized container, a propellant in the pressurized container for sustaining pressure in the pressurized container, and artificial soil mixture in the pressurized container. The artificial soil mixture including minerals, water, and organic material.
The subject matter which is regarded, as the invention is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the invention are apparent from the following detailed description taken in conjunction with the accompanying drawings in which:
The present invention is described with reference to embodiments of the invention. Throughout the description of the invention reference is made to
After the network provision step 102, the method proceeds to the environmental sensor provision step 104, as shown in
After the environmental sensor provision step 104, the method proceeds to the health sensor provision step 106, as shown in
After the health sensor provision step 106, the method 100 proceeds to the soil model computation step 108, as shown in
As shown in
Returning to
After the inverse representation of data step 116, the method proceeds to the artificial soil synthesis step 118, as shown in
After the artificial soil synthesis step 118, the method 100 proceeds to the artificial soil exposure step 120, as shown in
After the artificial soil exposure step 120, the method proceeds to the allergic response step 122, as shown in
After the allergic response step 122, the method proceeds to the artificial soil adjustment step 124, as shown in
The environmental sensors 204 are located in a first geographic region 206. The environmental sensors 204 measure environmental conditions 208 of the first geographic region 206. The environmental sensors 204 are in communication with the computer network 202. The environmental sensors 204 may include soil sensors 228 to measure native soil composition 230 of the first geographic region 206.
The health sensors 206 measure the health conditions 210 of a sample human population 212 in the first geographic region 206. The health sensors 206 are also in communication with the computer network 202. The health sensors 206 may include allergy sensors 232 to measure allergic responses by the sample human population 212.
The computer processor 208 computes a soil model 216 that prevents diseases, including allergies, based on environmental sensors 208 and health sensors 210. The computer processor 208 is also communication with the computer network 202.
The artificial soil 218 replicates the computed soil model 216. The artificial soil 218 may include a mixture of minerals, water, gases, and organic material. The minerals may also be 45% the mixture by weight. Water may be 25% of the mixture by weight. The gases may be 25% of the mixture by weight. The organic material may be 5% of the mixture by weight. The minerals in the artificial soil 218 may be selected from a group consisting of sand, silt, clay, quartz, silicon dioxide and limestone. The organic material in the artificial soil 218 may be selected from the group consisting of hydrocarbons or plant residues.
According to one embodiment of the invention, the system 200 may include an artificial soil spray 222 for exposing human patients to the artificial soil 218 in a second geographic region 220. The artificial soil spray 222 may include a pressurized container 224 and a propellant 226 in the pressurized container 224. The pressurized container 224 may enclose the artificial soil 218. The propellant 226 may sustain pressure in the pressurized container 224.
According to another embodiment of the invention, the system 200 may include clothing that carries the artificial soil 218.
In a particular embodiment, the artificial soil 300 includes a mixture of minerals, water, gases, and organic material. The minerals may be 45% of the mixture by weight. Water may be 25% of the mixture by weight. The gases may be 25% of the mixture by weight. Organic material may be 5% of the mixture by weight.
The minerals of the artificial soil 300 may be selected from a group consisting of sand, silt, clay, quartz, silicon dioxide and limestone. The organic material may be selected from a group consisting of hydrocarbons or plant residues.
The propellent 404 is contained in the pressurized container 402 and sustains pressure in the pressurized container 402. The artificial soil mixture 406 is also contained in the pressurized container 402 and includes minerals, water, and organic material. The minerals may be 45% of the mixture by volume. Water may be 25% of the mixture by volume. Organic material may be 5% of the mixture by volume. The minerals of the artificial soil 406 may be selected from a group consisting of sand, silt, clay, quartz, silicon, dioxide and limestone. The organic material may be selected from a group consisting of hydrocarbons or plant residues.
Environmental health cognition 506 may involve preprocessing data into a more representative form. Preprocessing of data may utilize hierarchical learning or sparse representations. Environmental health cognition 506 may take place over an extended period of time, for example, monitoring and collecting data over many years.
As shown in
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As shown in
Cognition processing of data 705, for example, processes data generated from environmental health cognition 506. Cognition processing of data 705 may be performed via a neural network. The processed data may then be passed to a classification engine 701. The classification engine 701 may sort and classify the human, health, and environmental data into classes such as, for example, soil type, the presence or absence of allergens, the type of allergen present, and the individual's age.
Correlation analysis 702 identifies correlations, if any, between health data and either behavioral or environmental data.
The health change detector 703 assesses the strength of the correlation between environmental data and health data.
The cause detector 704 identifies the presence or absence of a causal relationship between strongly correlated environmental data and health data. The cause detector 704 also determines the presence or absence of a causal relationship between strongly correlated behavioral data and health data.
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As shown in
Existing soil component data 801 refers to information regarding the components of the ground in a target geographic area. The ground may include sand, dirt, soil, gravel, and other surface matter.
Beneficial soil component data 805 refers information on soil components that may have positive effects on human health. A positive effect on human health may include improving childhood immunity against disease.
The matching engine 802 may compare beneficial soil component data 805 against existing soil component data 801 and compile recommended soil supplement data 803, which are components beneficial to human health that are lacking in the environment of the target geographic area.
An environment replication process 804 then uses the recommended soil supplement data 803 to create environments intended to improve human health. The environment replication process 804 may include adding beneficial organic material (animal or plant) to native soil. The environment replication process may also include synthesizing artificial soil. According to an embodiment or the invention, the artificial soil may be dispensed using a spray.
Returning to
Patient centric care begins with providing information to the patient 905. Providing information involves giving patients information on the effects of the embedded environment on human health.
After providing information to the patient 905, the method proceeds to scheduling and planning step 901. At the scheduling and planning step 901, patients are scheduled for a regimen of visits to the embedded environment.
According to an embodiment of the invention, the scheduling and planning step 901 may also be preceded by a dosage optimization step 902. The dosage optimization step 902 involves determining an optimized regimen of exposure to the embedded environment and may include a determination of the frequency of exposures and length of each exposure.
After the scheduling and planning step 901, the method proceeds to a participation monitoring step 903. At the participation monitoring step 903, the patient's participation is monitored. The patient's participation may also be compared to the prescribed regimen of exposure.
After the participation monitoring step 903, the method proceeds to a health monitoring step 904. At the health monitoring step, the state of the patient's health in reaction to exposure to the embedded environment is assessed. Participation monitoring 904 may also involve informing parents of changes in their child's health after exposure to the embedded environment. According to an embodiment of the invention, participation monitoring may also include providing the local community with general information on the effects of exposure to the embedded environment.
The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, the present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media, (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection, may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
