Method, computer program, system and computer-readable recording medium for power generation

Abstract

To provide a method for supplying power to a device, a computer program, a system, and a computer readable recording medium.SOLUTION: An exemplary embodiment includes generating power from movement of one or more metal coils relative to one or more pieces of cloth containing one or more electronic threads (step 210) and transferring the generated power to a device (step 212).SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to power generation, and more particularly to the use of electrical textiles for power generation. [Background technology]

[0002] Many people wear smart wearable devices that monitor the wearer. Smart wearable devices require power to monitor the wearer and often need to be removed from the wearer's body to charge their batteries. This causes inconvenience to the wearer and results in times when the smart wearable device cannot monitor the wearer. Many people would like a power source for their smart wearable device that does not require the smart wearable device to be removed from the wearer's body. For example, people who wear smart wearable devices that monitor cardiac activity would like their smart wearable device to have a power source that allows it to be charged without the need to remove the smart wearable device from their body. Summary of the Invention [Problem to be solved by the invention]

[0003] The present invention aims to provide a system for generating electricity using electrical fabrics. [Means for solving the problem]

[0004] Exemplary embodiments disclose a method, a computer program product, a system, and a computer-readable medium for providing power to a device, including generating power from the movement of one or more metal coils relative to one or more pieces of fabric including one or more electrical yarns, and transmitting the generated power to the device.

[0005] The following detailed description is provided by way of example and is not intended to limit the exemplary embodiments thereto only and will be best understood in conjunction with the accompanying drawings, in which: [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a schematic diagram of an electrical textile system 100 according to an exemplary embodiment. [Figure 2] FIG. 2 is a flow chart illustrating the operation of the electrical fabric analyzer 144 of the electrical fabric system 100 powering the smart wearable device 120, according to an exemplary embodiment of the present invention. [Figure 3] FIG. 3 is a schematic diagram of a power generation system 110 of an electric textile system 100 generating power to power a smart wearable device 120, according to an exemplary embodiment of the present invention. [Figure 4] FIG. 4 is an exemplary block diagram illustrating hardware components of the electrical textile system 100 of FIG. 1 according to an exemplary embodiment. [Figure 5] FIG. 5 illustrates a cloud computing environment in accordance with an exemplary embodiment. [Figure 6] FIG. 6 illustrates abstract model layers in accordance with an exemplary embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0007] The drawings are not necessarily to scale. The drawings are merely schematic representations and are not intended to depict specific parameters of example embodiments. The drawings are intended to depict typical example embodiments only. In the drawings, like numbers represent like elements.

[0008] Although detailed embodiments of the claimed structures and methods are disclosed herein, it is understood that the detailed embodiments are merely exemplary of the claimed structures and methods, which may be embodied in various forms. The exemplary embodiments are merely illustrative and may be embodied in many different forms, and should not be construed as limitations to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make this disclosure comprehensive and complete, and to fully convey the scope of protection afforded by the exemplary embodiments to those skilled in the art. In this specification, details of well-known features and techniques are omitted to avoid unnecessarily obscuring the present embodiments.

[0009] References in the specification to "one embodiment," "an embodiment," "an exemplary embodiment," etc., indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment may necessarily include that particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in the context of an embodiment, it is within the knowledge of one of ordinary skill in the art to implement such feature, structure, or characteristic in other embodiments, whether or not explicitly described.

[0010] In the following description, some process steps or operations known in the art may be combined with each other for presentation and illustration purposes, and in some instances may not be described in detail, so as not to interfere with the presentation of exemplary embodiments. In other instances, some process steps or operations known in the art may not be described at all. It should be understood that the following description focuses on features or elements according to various exemplary embodiments.

[0011] Many people wear smart wearable devices that monitor the wearer. Smart wearable devices require power to monitor the wearer and often need to be removed from the wearer's body to charge their batteries. This causes inconvenience to the wearer and results in times when the smart wearable device cannot monitor the wearer. Many people would desire a power source for their smart wearable device that does not require the smart wearable device to be removed from the wearer's body. For example, people with smart wearable devices that monitor their cardiac activity would desire the smart wearable device to have a power source that does not require the smart wearable device to be removed from their body to charge.

[0012] Exemplary embodiments are described for computer-implemented methods, computer programs, computer systems, and computer-readable media for providing power to a device. In various embodiments, device refers to a smart wearable device 120 or any smart device that is in contact with or near a user's body, and can include wearable devices such as smart watches, smart necklaces, smart rings, and implanted devices such as electrical tattoos. Power is provided to one or more smart wearable devices 120 for various purposes, such as heart rate monitoring, blood oxygen level monitoring, brainwave monitoring, convenient control of smart devices (e.g., remote controls for computers, televisions, smartphones, etc.), and the like. In general, it will be understood that embodiments herein may relate to providing power to any type of device in any environment and for any purpose.

[0013] 1 illustrates an electric textile system 100 according to an exemplary embodiment. The electric textile system 100 according to an exemplary embodiment can include one or more power generation systems 110, one or more smart wearable devices 120, a smart device 130, and an electric textile server 140, all of which can be interconnected via a network 108. Programs and data of the exemplary embodiments can be stored and accessed across several servers via the network 108; programs and data of the exemplary embodiments can alternatively or additionally be stored locally on just one computing device or on other computing devices than those shown.

[0014] In an exemplary embodiment, the network 108 may be a communications channel capable of transferring data between connected devices. Accordingly, the components of the electric textile system 100 may represent network components or devices interconnected via the network 108. In an exemplary embodiment, the network 108 may be the Internet, represented as a worldwide collection of networks and gateways that facilitate communication between Internet-connected devices. Furthermore, the network 108 may utilize various types of connections, such as wired, wireless, or fiber optic, which may be implemented as an intranet network, a local area network (LAN), a wide area network (WAN), or a combination thereof. In a further embodiment, the network 108 may be a Bluetooth® network, a Wi-Fi network, or a combination thereof. In yet a further embodiment, the network 108 may be a telecommunications network used to enable telephone calls between two or more parties, including a wired telephone network, a wireless network, a closed network, a satellite network, or a combination thereof. In general, network 108 can refer to any combination of connections and protocols that support communication between connected devices.

[0015] In the exemplary embodiment, the power generation system 110 includes one or more power generating coils 112 and one or more pieces of electric fabric 114. While the power generation system 110 is shown as a single device, other embodiments may use multiple power generation systems 110, each including one or more separate cooperating coils 112 and one or more pieces of electric fabric 114. The power generation system 110 may generate power and provide the generated power to one or more smart wearable devices 120. The power generation system 110 is described in more detail as a hardware implementation with reference to FIG. 4, as a cloud implementation with reference to FIG. 5, and using functional abstraction layers for processing with reference to FIG. 6, or a combination thereof.

[0016] In exemplary embodiments, the power generating coil 112 may be one or more types of coils located within the user's body, on or under the user's skin. In some embodiments, the coil 112 may be a copper coil 112. In some embodiments, the coil 112 may be embedded in the user's electrical tattoo, placed directly beneath the user's skin. In other embodiments, the coil 112 may be affixed to the outer surface of the user's skin, for example, with one or more adhesives.

[0017] In exemplary embodiments, electric textile 114 can be one or more pieces of textile woven or sewn with one or more magnetic yarns capable of generating a magnetic field. In some embodiments, electric textile 114 is worn by a user such that one or more pieces of electric textile 114 are positioned near coil 112, and coil 112 and electric textile 114 can collectively generate electricity. In some embodiments, electric textile 114 can be sewn onto an object not directly worn by the user, such as a bed sheet, cover, curtain, or cloth.

[0018] In an exemplary embodiment, smart wearable device 120 may include one or more sensors 122 and may be one or more smart watches, smart necklaces, smart rings, smart speakers, smart assistants, enterprise servers, laptop computers, notebook computers, tablet computers, netbook computers, personal computers (PCs), desktop computers, servers, personal digital assistants (PDAs), rotary dial phones, touch-tone phones, smartphones, mobile phones, virtual devices, thin clients, virtual reality devices, augmented reality devices, or any other electronic device or computing system capable of sending and receiving data to and from other computing devices. While each smart wearable device 120 is illustrated as a single device, in other embodiments, each smart wearable device 120 may include a cluster or multiple computing devices operating together or independently, such as in a cohesive fashion. The smart wearable device 120 is described in more detail as a hardware implementation with reference to FIG. 4, as a cloud implementation with reference to FIG. 5, and using functional abstraction layers for processing with reference to FIG. 6, or a combination thereof.

[0019] In an exemplary embodiment, the sensors 122 may include cameras, microphones, light sensors, infrared sensors, motion detection sensors, pressure detection sensors, speedometers, accelerometers, gyroscopes, Global Positioning System (GPS) sensors, thermometers, or other perceptual hardware devices. Furthermore, the smart wearable device 120 may include one or more sensors 122 such that the sensors 122 can acquire information in multiple directions, at different times / intervals, through different media / frequencies, etc. For example, the smart wearable device 120 may be a pair of goggles including forward-facing cameras each recording an adjacent 60° field of view spanning a total of 180° in front of the user. Furthermore, data processing techniques may be implemented to obtain directional information for the visual and acoustic data based on the signals received by each of the three sensors 122, such as trilateration and triangulation.

[0020] Although the sensor 122 is described as being integrated into the smart wearable device 120, in various embodiments, the sensor 122 can be incorporated into the environment in which the electric textile system 100 is implemented. For example, the sensor 122 can be one or more microphones built into the spectator stands, cameras built into the equipment, speedometers, accelerometers, spectrometers, pedometers, etc. Furthermore, data processing techniques can be implemented to derive directional information for visual and acoustic data based on signals received by each of the three sensors 122, such as trilateration and triangulation. In other embodiments, the sensor 122 can be integrated into other smart devices, such as smartphones and laptop computers, in the environment in which the electric textile system 100 is implemented. In such embodiments, the sensor 122 can communicate directly with other networks and devices, such as the network 108. The sensor 122 is described in more detail with respect to a hardware implementation with reference to FIG. 4, a cloud implementation with reference to FIG. 5, and using functional abstraction layers for processing with reference to FIG. 6, or a combination thereof.

[0021] In an exemplary embodiment, smart device 130 includes electrical fabric client 132 and may be an enterprise server, a laptop computer, a notebook computer, a tablet computer, a netbook computer, a personal computer (PC), a desktop computer, a server, a personal digital assistant (PDA), a rotary dial phone, a touch-tone phone, a smartphone, a mobile phone, a virtual device, a thin client, an IoT device, or any other electrical device or computing system capable of transmitting and receiving data to and from other computing devices. While smart device 130 is illustrated as a single device, in other embodiments, smart device 130 may include a cluster or multiple computing devices operating cooperatively or independently, such as in an assembled fashion. Smart device 130 is described in more detail as a hardware implementation with reference to FIG. 4, as a cloud implementation with reference to FIG. 5, and using functional abstraction layers for processing with reference to FIG. 6, or a combination thereof.

[0022] The electrical textile client 132 can operate as a client in a client-server relationship. The electrical textile client 132 can also be a software or hardware application, or both, that can communicate with a server, such as the electrical textile server 140, via the network 108 and provide a user interface for a user. Furthermore, in exemplary embodiments, the electrical textile client 132 can transmit data from the smart wearable device 120 and / or the sensor 122 to and from the smart device 130 and / or other devices via the network 108. In various embodiments, the electrical textile client 132 uses various wired and wireless connection protocols for data transmission and exchange, such as Bluetooth, 2.5 GHz and 5 GHz Internet, near field communication, Z-Wave, Zigbee, etc. The electrical textile client 132 is described in more detail in connection with FIG. 2 .

[0023] In an exemplary embodiment, the electrical fabric server 140 can include one or more electrical fabric models 142 and an electrical fabric analyzer 144 and can operate as a server in a client-server relationship with the electrical fabric client 132. The electrical fabric server 140 can be an enterprise server, a laptop computer, a notebook computer, a tablet computer, a netbook computer, a personal computer (PC), a desktop computer, a server, a personal digital assistant (PDA), a rotary phone, a touch-tone phone, a smartphone, a mobile phone, a virtual device, a thin client, an IoT device, or any other electrical device or computing system capable of transmitting and receiving data to and from other computing devices. While the electrical fabric server 140 is illustrated as a single device, in other embodiments, the electrical fabric server 140 can include a cluster or multiple computing devices operating together or independently, such as in a cohesive fashion. The electrical fabric server 140 is described in more detail as a hardware implementation with reference to FIG. 4, as a cloud implementation with reference to FIG. 5, and using functional abstraction layers for processing with reference to FIG. 6, or a combination thereof.

[0024] In an exemplary embodiment, the electrical textile model 142 may be one or more algorithms that model the correlation of one or more features (and / or collected data) with the specifications of the power generation system 110 and / or the specifications of one or more smart wearable devices 120. In an exemplary embodiment, the electrical textile model 142 may be generated using machine learning methods such as neural networks, deep learning, hierarchical learning, Gaussian mixture modeling, hidden Markov modeling, K-Means, K-Medoids, fuzzy C-Means learning, etc., to model the likelihood of one or more features (and / or collected data) being indicative of the power specifications of the power generation system 110 and / or the power specifications of one or more smart wearable devices 120. In embodiments, such features relate to power generation and consumption, including power generation rate, power consumption rate, time of day for power generation and / or consumption, number of days in a week for power generation and / or consumption, etc. The electrical fabric model 142 can weight the features based on the impact they have in determining the power specifications of the power generation system 110 and / or one or more smart wearable devices 120. The electrical fabric model 142 is described in more detail with respect to FIG. 2.

[0025] In an exemplary embodiment, the electrical fabric analyzer 144 can be a software program and / or hardware capable of collecting data, extracting one or more features from the data, and applying one or more models to the extracted features to determine the specifications of the power generation system 110 and / or the specifications of the smart wearable device 120. The electrical fabric analyzer 144 can additionally configure a session, generate electricity via one or more coils 112 and pieces of electrical fabric 114, and power one or more smart wearable devices 120 with the generated power. Furthermore, the electrical fabric analyzer 144 can collect data from one or more smart wearable devices 120 and analyze and / or aggregate the collected data. Furthermore, the electrical fabric analyzer 144 can be configured to report the data to a user according to user preferences. The electrical fabric analyzer 144 is described in more detail in conjunction with FIG. 2.

[0026] FIG. 2 is an exemplary flow chart illustrating the operation of the electrical fabric analyzer 144 in the electrical fabric system 100 to provide power to one or more devices according to this exemplary embodiment.

[0027] The electrical fabric analyzer 144 may collect data from the user (step 204). In embodiments, the electrical fabric analyzer 144 may collect data via user input, such as the type or power consumption of one or more smart wearable devices 120, the number of coils 112, the diameter of the coils 112, the number of yarns in the electrical fabric 114, the thickness of the yarns in the electrical fabric 114, and the type of yarn in the electrical fabric 114. The collected data may additionally include the time interval or period during which the user desires to wear the power generation system 110, the one or more smart wearable devices 120, or both. The collected data may be extracted as features for application to one or more models. For example, the electrical fabric analyzer 144 may collect data from the user specifying that the user intends to wear a heart rate monitor requiring 5 watts of power all the time. Alternatively, the electrical fabric analyzer 144 may collect data specifying that the user intends to wear a heart rate monitor having a power generation system that produces an average of 10 watts of power. The electrical fabric analyzer 144 extracts the collected data as one or more characteristics.

[0028] To further illustrate the operation of the electrical fabric analyzer 144, reference will now be made to an illustrative example in which the electrical fabric analyzer 144 collects data specifying, via user input, that the user intends to wear a smart watch that requires 10 watts for approximately 16 hours per day.

[0029] The electrical fabric analyzer 144 can apply one or more electrical fabric models 142 to the collected data / extracted features to determine one or more specifications for the power generation system 110, the one or more smart wearable devices 120, or both. The one or more specifications for the power generation system 110 can include the number of coils 112 required, the type of coils 112, the area of ​​the electrical fabric 114, the type of electrical fabric 114, etc. As described above, the one or more electrical fabric models 142 can be generated through machine learning techniques such as neural networks. In some embodiments, the one or more electrical fabric models 142 are trained using initialization and a feedback loop for weighting features, and both, to indicate that the indicated features have a greater correlation by determining the specifications to weight one or more specifications for the power generation system 110 and / or one or more specifications for the smart wearable devices 120 more heavily than other features. Based on the extracted features and weightings associated with such extracted features, the electrical fabric analyzer 144 can determine specifications such as the number of one or more required coils 112, the type of coils 112, the required area of ​​the electrical fabric 114, the type of electrical fabric 114, etc. for the power generation system 110 and / or one or more smart wearable devices 120.

[0030] Referring to the previously described example in which the electrical fabric analyzer 144 collects data specifying via user input that the user intends to wear a smart watch requiring 10 watts for approximately 16 hours per day, the electrical fabric analyzer 144 applies the electrical fabric model 142 to determine that the user requires a power generation system 110 consisting of five copper coils 112 and an area of ​​4 square inches to power the smart watch requiring 10 watts for approximately 16 hours per day.

[0031] The electrical fabric analyzer 144 can receive and / or execute the configuration (step 208). The electrical fabric analyzer 144 can receive the user configuration by receiving a user registration and user preferences. The user registration is uploaded by a user, i.e., a person using or wearing the power generation system 110 or smart wearable device 120 of the electrical fabric system 100, or an administrator, i.e., a person overseeing the user's use of the electrical fabric system 100 (such as the user's parent or guardian, the user's employer, etc.), and the configuration is received by the electrical fabric analyzer 144 via the electrical fabric client 132 and the network 108. The received user registration may include a reference to a user profile via user login credentials, Internet Protocol (IP) address, Media Access Control (MAC) address, etc., or name, date of birth, gender, address / locality information, phone number, email address, company name, device serial number, type of smart device 130, type of one or more smart wearable devices 120, type of sensor 122, type / number / location of one or more coils 112 and electrical fabric 114, etc. The received user registration may also include receiving or extracting data from a database, such as user health data, calendar data, etc. Finally, the electrical fabric analyzer 144 may receive configurations, such as whether one or more sensors 122 are fixed to one or more devices (e.g., smart device 130 or one or more smart wearable devices 120) or fixed within the environment in which the electrical fabric system 100 is implemented.

[0032] During configuration, the electrical fabric analyzer 144 can further receive user preferences (step 204, cont.). The user preferences can include whether the electrical fabric analyzer 144 should notify the user of the analyzed or aggregated data, or both. For example, the user preferences can specify that the user be notified of the user's heart rate via audio and video feedback to the user's smart device 130 only if the user's heart rate is faster than 100 beats per minute. In another example, the user can specify that the user's daily heart rate be aggregated for a week, with presentation to the user via visual feedback to the user's smart device 130 every Sunday.

[0033] Referring back to the previously described example in which the electrical fabric analyzer 144 determined that a user requires five copper coils 112 and a power generation system 110 with an area of ​​4 square inches to power a smart watch that requires 10 watts for approximately 16 hours per day, the electrical fabric analyzer 144 receives user registration via user upload, including the user name, the type of smartphone or smart device 130, the type of smart wearable device 120 for heart rate monitoring, and the type of sensor 122, including the heart rate sensor. The electrical fabric analyzer 144 further receives the type, number, and location of coils 112 attached to the user's arm, e.g., embedded in an electrical tattoo, and the specifications (according to the specifications determined in step 206) of the electrical fabric 114 woven into the user's shirt that is positioned to directly cover the electrical tattoo on the user's arm. The electrical fabric analyzer 144 also receives, via user upload, a designation that the electrical fabric analyzer 144 should notify the user via audio and visual feedback to the user's smartphone if the user's heart rate is faster than 100 beats per minute.

[0034] The electrical fabric analyzer 144 can generate power from the one or more coils 112 and the pieces of electrical fabric 114 (step 210). In embodiments, the one or more coils 112 can be copper coils 112 or tattooed coils 112 under the user's skin, and the one or more pieces of electrical fabric 114 can include one or more magnetic threads sewn into the electrical fabric 114. In embodiments, the user's movement causes the one or more coils 112 to move relative to the electrical fabric 114, generating, creating, or changing one or more magnetic fields. In embodiments, the changes in the one or more magnetic fields are stored as power within the one or more coils 112, one or more smart wearable devices 120, or both (i.e., stored in one or more batteries of the one or more smart wearable devices 120). In some embodiments, the power generated by the power generation system 110 can directly power one or more smart wearable devices 120 so that the one or more smart wearable devices 120 can function (i.e., collect data via one or more sensors 122). Power generation via one or more coils 112 and strips of electrical textile 114 is further discussed with reference to FIG.

[0035] Referring back to the example of the electrical fabric analyzer 144 receiving the configuration mentioned earlier, the electrical fabric analyzer 144 generates power via the coil 112 of the user's electrical tattoo and the electrical fabric 114 of the user's shirt.

[0036] The electrical fabric analyzer 144 can power one or more smart wearable devices 120 with the generated power (step 212). As previously described, the one or more magnetic field changes can be stored as power within one or more coils 112, one or more smart wearable devices 120, or both (i.e., stored in one or more batteries of one or more smart wearable devices 120). In some embodiments, the power generated by the power generation system 110 directly powers one or more smart wearable devices 120 so that the one or more smart wearable devices 120 can function (i.e., collect data via one or more sensors 122). In some embodiments, the power generation system 110 is connected to one or more smart wearable devices 120 to facilitate power transfer from the power generation system 110 to the one or more smart wearable devices 120. For example, one or more coils 112 may be connected to a heart rate monitor via copper wire to facilitate transmission of the generated power. In some embodiments, the power generated by the power generation system 110 may be transmitted wirelessly to one or more smart wearable devices 120, for example, via one or more wireless charging methods. In some embodiments, the electrical fabric analyzer 144 may power one or more smart wearable devices 120 with power generated by alternative methods.

[0037] Referring back to the example mentioned earlier where the electrical fabric analyzer 144 generates power through the coil 112 of the user's electrical tattoo and the electrical fabric 114 of the user's shirt, the electrical fabric analyzer 144 provides power to the user's heart rate monitor via copper wires connecting the coil 112 and the heart rate monitor.

[0038] As the one or more smart wearable devices 120 are powered by the power generation system 110, the electrical fabric analyzer 144 can collect data from the one or more smart wearable devices 120 (step 214). In some embodiments, the one or more smart wearable devices 120 can collect biometric data (i.e., heart rate, body temperature, blood oxygen level, calories burned, movement speed, etc.) via one or more sensors 122, which can include one or more heart rate monitors positioned on the user's chest and input devices for controlling other smart devices (i.e., the user's hand movements toward a computer mouse, movement in a video game, etc.). In some embodiments, the electrical fabric analyzer 144 can collect Global Positioning Service (GPS) data. For example, the electrical fabric analyzer 144 may collect GPS data for purposes of locating the user and locating points of interest near the user (nearby clinics, gas stations, restaurants, grocery stores, etc.), determining the user's average level of mobility / mobility, etc. In some embodiments, the electrical fabric analyzer 144 may collect data continuously via one or more sensors 122 as long as the smart wearable device 120 has enough power to function.

[0039] Referring to the previously mentioned example in which the electrical fabric analyzer 144 powers the user's heart rate monitor with generated power via copper wires connecting the coil 112 and the heart rate monitor, the electrical fabric analyzer 144 collects heart rate data from the user's heart rate monitor.

[0040] The electrical fabric analyzer 144 may analyze and / or aggregate the collected data (step 216). In embodiments, the electrical fabric analyzer 144 may analyze and / or aggregate the data using one or more electrical fabric models 142 according to one or more user preferences. In embodiments, the electrical fabric analyzer 144 may analyze and / or aggregate using one or more of an average value, a maximum value, a minimum value, a maximum rate of increase, a minimum rate of increase, etc. according to the user preferences. For example, if during configuration the user specifies that they wish to know their average daily heart rate, the electrical fabric analyzer 144 may average the user's heart rate data for each day. As another example, if during configuration the user specifies that they wish to know their maximum daily heart rate, the electrical fabric analyzer 144 may determine the user's maximum daily heart rate. In embodiments, the electrical fabric analyzer 144 need not analyze and / or aggregate the data. For example, if a user specifies that they want to be consistently provided with real-time heart rate data displayed on their smart device 130, the electrical fabric analyzer 144 need not analyze and / or aggregate the data, but can instead be processed to directly notify the user of the data. In other embodiments, if a user specifies that they want a map of their real-time location displayed on their smart device 130, the electrical fabric analyzer 144 need not analyze and / or aggregate previously collected GPS data, but can instead be processed to directly display a map of the user's location.

[0041] Referring to the previously mentioned example in which the electrical fabric analyzer 144 collects heart rate data from a user's heart rate monitor, the electrical fabric analyzer 144 monitors and analyzes data in real time for instances where the user's heart rate exceeds 100 beats per minute according to user preferences. The electrical fabric analyzer 144 detects a heart rate of 98 beats per minute for two minutes, then suddenly detects a heart rate of 105 beats per minute.

[0042] The electrical fabric analyzer 144 can communicate analyzed and / or aggregated data to the user. In some embodiments, the electrical fabric analyzer 144 can communicate data specified by user preferences to the user. In some embodiments, the electrical fabric analyzer 144 can communicate collected data to the user without the need for analysis and / or aggregation. The electrical fabric analyzer 144 can deliver data to the user in audio, video, text, or any other format via the smart device 130, or one or more smart wearable devices 120, or a combination thereof.

[0043] Referring to the previously mentioned example where the electrical fabric analyzer 144 monitors and analyzes data in real time according to user preferences for when the user's heart rate exceeds 100 beats per minute, if the user's heart rate is 98 beats per minute for two minutes and then suddenly detects 105 beats per minute, the electrical fabric analyzer 144 will notify the user via audio and visual feedback on their smartphone that the heart rate is 105 beats per minute after two minutes.

[0044] 3 shows an exemplary schematic diagram of a power generation system 110 in an electric textile system 100 that generates power to power smart wearable devices 120, according to an exemplary embodiment. In embodiments, the one or more coils 112 can be copper coils 112 or tattooed coils 112 under the user's skin, and one or more pieces of electric textile 114 can include one or more magnetic threads sewn into the electric textile 114. In embodiments, user movement can cause the one or more coils 112 to move relative to the electric textile 114, generating, creating, or changing one or more magnetic fields, or a combination thereof. In embodiments, the changes in the one or more magnetic fields are stored as electromagnetic induction-based power in the one or more coils 112, one or more smart wearable devices 120, or both (i.e., stored in one or more batteries of the one or more smart wearable devices 120). In embodiments, the power generated by the power generation system 110 may directly power one or more smart wearable devices 120 so that the one or more smart wearable devices 120 can function (i.e., collect data from one or more sensors 122). In embodiments, the rate of power production and / or consumption is tracked and can be used to determine the number / type / location of coils 112 and / or pieces of electrical textile 114 needed to power the one or more smart wearable devices 120, or to determine the specifications of the one or more smart wearable devices 120, such as battery storage capacity, or both.

[0045] In embodiments, a washing machine for washing fabrics including one or more pieces of electric fabric 114 can have an array of coils 112 surrounding the washing drum of the washing machine. The one or more pieces of electric fabric 114 and the coils 112 can be waterproof. When a wash cycle is applied to fabrics including one or more pieces of electric fabric 114, the movement of the coils 112 relative to the electric fabric 114 can generate electrical power. The generated electrical power can be stored in the coils 112 for later use by a user to power one or more smart wearable devices 120.

[0046] Figure 4 is a block diagram of an example embodiment of a device in the electric textile system 100 of Figure 1. It should be appreciated that Figure 4 is only intended to illustrate one implementation and is not intended to imply any limitation with respect to the environments in which different embodiments may be implemented. Many modifications to the depicted environments may be possible.

[0047] As used herein, a device may include one or more processors (processing units) 16, one or more computer-readable RAMs 30, one or more computer-readable ROMs, one or more computer-readable recording media (system records 34), device drivers 12, read / write drives or interfaces (I / O interfaces 22), and network adapters or interfaces 20, all interconnected over a communications fabric 18. Communications fabric 18 may be implemented as any architecture designed to pass data and / or control information between processors (such as microprocessors, communications and network processors), system memory, peripheral devices, and any other hardware components in the system.

[0048] One or more operating systems 40 and one or more application programs 42 are stored on one or more computer-readable storage media, such as system memory 34, and executed by one or more processors via one or more respective RAMs 30 (which typically include cache memory 32). In the illustrated embodiment, the computer-readable storage media may each be a magnetic disk storage media with an internal hard drive, a CD-ROM, a DVD, a memory stick, magnetic tape, an optical disk, a semiconductor storage device such as RAM, ROM, EPROM, flash memory, or any other computer-readable tangible storage device capable of storing computer programs and digital information.

[0049] The device usable herein may also include an external device 14, such as a R / W drive, that reads from and writes to one or more portable computer-readable recording media or an interface 22. The application program 42 on the device may be recorded on one or more portable computer-readable recording media, read via the respective external device 14, such as a R / W drive, or an I / O interface 22, and loaded into the respective computer-readable recording media.

[0050] The devices used herein may also include a network adapter or interface 20, such as a TCP / IP adapter card or a wireless communication adapter (e.g., a 4G wireless communication adapter using OFDMA technology). Application programs on the computing device may be downloaded to the computing device from an external computer or external device 14 via a network (e.g., the Internet, a local area network, or other wide area network or wireless network) and the network adapter 20 or I / O interface 22. From the network adapter or interface 20, the program may be loaded into a computer-readable storage medium, such as system memory 34. The network may include copper wire, optical fiber, wireless communication, routers, firewalls, switches, gateway computers, and edge servers, or a combination thereof.

[0051] Devices that can be used herein can also include a display 24, a keyboard or keypad, and a computer mouse or touchpad. I / O interface(s) 22 interface to the display 24 for imaging, a keyboard or keypad, a computer mouse or touchpad, and a display 24 for pressure sensing for alphanumeric character entry and user selection, or a combination thereof. The I / O interface 22, external devices 14 such as a R / W drive, or network adapter or interface 20 can include hardware and software (stored on a computer-readable storage medium and / or ROM).

[0052] The programs described herein are identified based on their application for implementation in one particular example embodiment. However, it should be recognized that any specific program terminology used herein is used merely for convenience, and thus the example embodiments are not limited to use in any particular application identified and / or implied by such terminology.

[0053] Based on the foregoing, a computer system, a method, a computer program product, and a computer-readable recording medium have been disclosed. However, numerous modifications and substitutions may be made without departing from the scope of the exemplary embodiments. Accordingly, the exemplary embodiments are disclosed for purposes of illustration and not limitation.

[0054] Although this disclosure includes detailed descriptions of cloud computing, it is understood that implementation of the teachings cited herein is not limited to cloud computing environments. Rather, exemplary embodiments may be implemented in any other type of computing environment now known or later developed.

[0055] Cloud computing is a service delivery model for on-demand network access that provides convenient access to a shared pool of rapidly provisioned and openly configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) with minimal administrative effort or interaction with the service provider. This cloud model includes at least five characteristics, at least three service models, and at least four deployment models.

[0056] Its features are as follows:

[0057] On-demand self-service: Cloud consumers are automatically provisioned with computing capacity, such as server time and network storage, as they need it, without any human interaction with the service provider.

[0058] Widespread network access: Capabilities are available over the network and accessed through standard mechanisms that facilitate use by different thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

[0059] Resource Sharing: Using a multi-tenant model, a provider's computing resources are shared to serve multiple consumers, with different physical and virtualized resources dynamically allocated and reallocated as needed. A sense of location independence exists, such that consumers generally have no control or knowledge of the exact location (e.g., country, state, or data center) of the resources provided, but can specify location at a higher level of abstraction.

[0060] Rapid Elasticity: Capabilities can be provisioned quickly and elastically, sometimes automatically, to quickly scale out and quickly release and quickly scale in. To the consumer, the capabilities available for provisioning often appear unlimited and can be purchased at any time and in any quantity.

[0061] Metered Services: Cloud systems automatically control and optimize resource usage by leveraging metering capabilities at several levels of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported to provide transparency to both providers and consumers of the services being used.

[0062] The service model is as follows:

[0063] Software as a Service (SaaS): The functionality offered to the consumer is the use of the provider's applications running on a cloud infrastructure. The applications are accessible from a variety of client devices through a thin-client interface such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, storage, or individual application functionality, except for limited user-specific application configuration settings.

[0064] Platform as a Service (PaaS): The capability offered to consumers is to deploy applications they create or acquire, written using programming languages ​​and tools supported by the provider, onto a cloud infrastructure. The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, or storage, but does control the deployed applications and, possibly, the configuration of the application hosting environment.

[0065] Infrastructure as a Service (IaaS): The functionality provided to the consumer is the provision of processing, storage, network, and other basic computing resources on which the consumer can deploy and run any software, which may include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but has control over the operating systems, storage, deployed applications, and possibly limited control over select networking components (e.g., host firewalls).

[0066] The deployment model is as follows:

[0067] Private Cloud: Cloud infrastructure operates solely for one organization. It can be managed by that organization or a third party and can exist on or off-premises.

[0068] Community Cloud: Cloud infrastructure is shared by several organizations to support a specific community with common interests (e.g., mission, security requirements, policy, and compliance considerations). It can be managed by those organizations or a third party and can reside on or off premises.

[0069] Public Cloud: Cloud infrastructure is made available to the public or large industry groups and is owned by organizations that sell cloud services.

[0070] Hybrid Cloud: A cloud infrastructure is a combination of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technologies that allow for data and application portability (e.g., cloud bursting for load balancing between clouds).

[0071] Cloud software is service-oriented, focusing on statelessness, loose coupling, modularity, and semantic interoperability. At the heart of cloud computing is the infrastructure, which comprises multiple interconnected nodes.

[0072] Referring to FIG. 5, an exemplary cloud computing environment 50 is shown. As shown, the cloud computing environment 50 includes one or more cloud computing nodes 10, with which communicate local computing devices used by cloud consumers, such as a personal digital assistant (PDA) or cellular phone 54A, a desktop computer 54B, a laptop computer 54C, or an automobile computer system 54N, or combinations thereof. The cloud computing nodes 10 can communicate with each other. They can be grouped physically or virtually within one or more networks (not shown), such as the private, community, public, or hybrid clouds described above, or combinations thereof. It is understood that the types of computing devices 54A-N shown in FIG. 2 are for illustrative purposes only, and that the computing nodes 10 and the cloud computing environment 50 can communicate with any type of computerized device through any type of network or addressable network connection (e.g., a web browser), or both.

[0073] Referring now to Figure 6, a set of functional abstraction layers provided by cloud computing environment 50 (Figure 5) is shown. It should be understood that the components, layers, and functions shown in Figure 6 are intended to be illustrative only, and that embodiments of the present invention are not limited thereto. As shown, the following layers and corresponding functions are provided:

[0074] The hardware and software layer 60 includes hardware and software components. Examples of hardware components include a mainframe 61, multiple servers based on a RISC (reduced instruction set computer) architecture 62, multiple servers 63, multiple blade servers 64, multiple storage devices 65, and network and networking components 66. In some embodiments, the software components include network application server software 67 and database software 68.

[0075] The visualization layer 70 provides an abstraction layer from which embodiments of virtual entities, described below, are provided: virtual servers 71; virtual storage 72; virtual networks 73, including virtual private networks; virtual applications and operating systems 74; and virtual clients 75.

[0076] In one embodiment, the management layer 80 may provide the following functions: A resource provisioning unit 81 provides dynamic acquisition of computing resources and other resources used to perform tasks within the cloud computing environment. A metering and pricing unit 82 provides cost tracking as resources are used within the cloud computing environment and provides accounting or billing for the consumption of these resources. In one embodiment, these resources may include application software licenses. A security unit provides identification and authentication of cloud consumers and tasks, as well as protection of data and other resources. A user portal unit 83 provides accessibility to the cloud computing environment and system administrators for consumers. A service level management unit 84 provides allocation and management of cloud computing resources to meet required service levels. A service level agreement (SLA) planning and fulfillment unit 85 pre-provisions and acquires cloud computing resources required for future requests according to SLAs.

[0077] The workload layer 90 provides examples of functionality for utilizing a cloud computing environment. Examples of workloads and functionality provided by this layer include mapping and navigation 91, software development and lifetime management 92, virtual classroom instruction delivery 93, data analytics processing 94, transaction processing 95, and power generation 96.

[0078] The present invention can be embodied in any possible level of technical detail integration as a system, a method, a computer-readable recording medium, or a computer program, and combinations thereof. The computer-readable recording medium(s) and the computer program have computer-readable program instructions that cause a processor to perform the features of the present invention.

[0079] A computer-readable storage medium may be any tangible device capable of holding and storing instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electro-magnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples of computer-readable storage media include the following: a portable computer disk, 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 disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a punch card, or a mechanically encoded device having protruding structures within grooves that record instructions, and any suitable combination thereof. As used herein, a computer-readable recording medium is not to be construed as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave such as a wave guide or other communication medium (e.g., light pulses passing through a fiber optic cable), or an electrical signal communicated through a wire.

[0080] The computer programs described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or can be downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, or a wireless network, or a combination thereof. The network can include copper communication cables, fiber optic communication cables, wireless communication routers, firewalls, switches, gateway computers, and edge servers, or a combination thereof. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and transfers the computer-readable program instructions to a computer-readable storage medium within the computing / processing device for storage.

[0081] Computer-readable program instructions for carrying out the operations of the present invention can be either source code or object code written in any combination of programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine language instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or one or more procedural programming languages, such as object-oriented programming languages ​​like Smalltalk®, C++, the "C" programming language, or similar programming languages. The computer-readable program instructions can execute entirely on the user computer, partially on the user computer as a stand-alone software package, partially on the user computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer can be connected to the user computer through any type of network, including a local area network (LAN), a wide area network (WAN), or the connection can be to an external computer (e.g., through an Internet service provider). In some embodiments, computer-readable program instructions can be executed by electrical circuitry, including, for example, programmable logic circuitry, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), using state information from the computer-readable program instructions to personalize the electrical circuitry to perform features of the present invention.

[0082] Aspects of the invention described herein have been described with reference to flowchart instructions and / or block diagrams of methods, apparatus (systems), and computer-readable storage media and computer program products according to embodiments of the invention. It will be understood that any combination of flowchart illustrations and / or block diagrams and / or blocks in flowchart illustrations and / or block diagrams can be implemented by computer-readable program instructions.

[0083] Computer-readable program instructions can be provided to a general-purpose computer, a special-purpose computer, or other processor or other programmable data processing device to create a machine, and execution by the computer's processor or other programmable data processing device creates means for implementing the functions / operations specified in the flowchart and block diagram block or blocks, or combinations thereof. These computer-readable program instructions, which direct a computer, programmable data processing device, or other device, or combinations thereof, to function in a particular manner, can also be stored on a computer-readable recording medium, and the computer-readable recording medium having instructions stored thereon constitutes an article of manufacture containing instructions that implement the functional / operational features specified in the flowchart and block diagram block or blocks, or combinations thereof.

[0084] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device and cause a computer-implemented process to perform a series of operational steps on the computer, other programmable apparatus, or other device to implement the functions / acts identified in a block or blocks of the flowcharts and block diagrams, or a combination thereof, on the computer, other programmable apparatus, or other device.

[0085] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and possible implementations of systems, methods, and computer programs according to various embodiments of the present invention. In this regard, the flowcharts or block diagrams may represent modules, segments, or portions of instructions, which contain one or more executable instructions for implementing a specific logical function(s). In some alternative implementations, the functions described in the blocks may be performed other than as illustrated. For example, two blocks shown in succession may actually be performed as a single step, or may be performed simultaneously, substantially simultaneously, or partially or completely overlapping in time, depending on the functionality involved, or the blocks may sometimes be performed in reverse order. It should also be noted that block diagrams and / or flowchart illustrations, and / or combinations thereof, may be implemented by special-purpose hardware-based systems that perform specific functions or operations or execute specific-purpose hardware and computer instructions. [Explanation of symbols]

[0086] 110: Power generation system 112: Generating coil 112: Copper coil 112: Coil 114: Electrical Fabric 120:Smart Wearable Devices 122: Sensor 130: Device 132: Electrical Fabric Client 140: Electrical Fabric Server 142: Electrical fabric model 144: Electrical Fabric Analyzer

Claims

1. A computer-implemented method for powering a device, comprising: collecting data related to the device and / or the power generation system including one or more metal coils and one or more electrical conductors; determining specifications from the collected data, including the configuration of one or more metal coils and one or more electrical conductors; configuring the power generation system in accordance with the standard; generating electricity with the power generation system from the movement of one or more of the electrical conductors relative to one or more of the metal coils; and transmitting the generated power to the device; A method comprising:

2. further transmitting the collected data of the device and / or the power generation system to a server via a network; extracting one or more features from the collected data; and applying one or more models to the extracted features to determine one or more specifications of one or more of the metal coils, one or more of the conductors, or the device; 10. The method of claim 1, comprising:

3. moreover, extracting one or more features from the collected data; applying one or more models to the extracted features to determine information of interest to a user; and presenting said information of interest to said user; 3. The method of claim 1 or 2, comprising:

4. the one or more metal coils are copper coils and are implanted in or attached to the user's body; the conductor is contained in one or more objects such as clothing, bed sheets, bed covers, or curtains; The device is a smart wearable device. The method according to any one of claims 1 to 3.

5. the one or more specifications of the one or more metal coils are number of coils, coil diameter, and coil type; The one or more specifications of the one or more conductors are number of threads, thread thickness, and thread type; and The one or more specifications of the device include the type of device and the power consumption of the device. The method according to any one of claims 1 to 4.

6. 1. A computer program for powering a device, the computer comprising: collecting data related to the device and / or the power generation system including one or more metal coils and one or more electrical conductors; determining specifications from the collected data, including the configuration of one or more metal coils and one or more electrical conductors; configuring the power generation system in accordance with the standard for generating electricity from the movement of one or more of the electrical conductors relative to one or more of the metal coils; and transmitting the generated power to the device; A computer program that executes

7. further transmitting the collected data of the device and / or the power generation system to a server via a network; extracting one or more features from the collected data; and applying one or more models to the extracted features to determine one or more specifications of one or more of the metal coils, one or more of the conductors, or the device; 7. The computer program of claim 6, comprising:

8. moreover, extracting one or more features from the collected data; applying one or more models to the extracted features to determine information of interest to a user; and presenting said information of interest to said user; 8. A computer program according to claim 6 or 7, comprising:

9. the one or more metal coils are copper coils and are implanted in or attached to the user's body; the conductor is contained in one or more objects such as clothing, bed sheets, bed covers, or curtains; The device is a smart wearable device. A computer program according to any one of claims 6 to 8.

10. the one or more specifications of the one or more metal coils are number of coils, coil diameter, and coil type; The one or more specifications of the one or more conductors are number of threads, thread thickness, and thread type; and The one or more specifications of the device include the type of device and the power consumption of the device. A computer program according to any one of claims 6 to 9.

11. a device; a power generation system including one or more metal coils and one or more conductors, the power generation system generating electricity from the one or more metal coils and the one or more conductors, and connected to the device to supply power to the device; a computing system connected to the device and the power generation system; Including, the computing system, collecting data from the device and / or the power generation system; determining a specification for the power generation system, including the configuration of one or more of the metal coils and one or more of the electrical conductors, from the collected data; configuring the power generation system in accordance with the standard for generating electricity from the movement of one or more of the electrical conductors relative to one or more of the metal coils; and transmitting the generated power to the device; To run the system.

12. The computing system includes a server, the computing system further comprising: transmitting the collected data of the device and / or the power generation system to the server over a network; extracting one or more features from the collected data; and applying one or more models to the extracted features to determine one or more specifications of one or more of the metal coils, one or more of the conductors, or the device; The system of claim 11 , further comprising:

13. moreover, extracting one or more features from the collected data; applying one or more models to the extracted features to determine information of interest to a user; and presenting said information of interest to said user; 13. The system according to claim 11 or 12, comprising:

14. the one or more metal coils are copper coils and are implanted in or attached to the user's body; the conductor is contained in one or more objects, such as clothing, bed sheets, bed covers, or curtains; The device is a smart wearable device. The system according to any one of claims 11 to 13.

15. the one or more specifications of the one or more metal coils are number of coils, coil diameter, and coil type; The one or more specifications of the one or more conductors are number of threads, thread thickness, and thread type; and The one or more specifications of the device include the type of device and the power consumption of the device. The system according to any one of claims 11 to 14.

16. A computer-readable recording medium on which the computer program according to any one of claims 6 to 10 is recorded.

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