Frequency-based detection system for precise identification and assessment of the presence and severity of substances

Abstract

A frequency-based detection system for precisely identifying and evaluating the presence and severity of substances comprises an input mechanism for receiving a sample of the target substance or an image / video of it, and a frequency detector for identifying the intrinsic frequency of each substance. The system integrates a display device that shows live video or images to a volunteer with an electrode device held by the volunteer. The electrode device transmits electromagnetic signals corresponding to the volunteer's observed frequencies, which are affected by their interaction with the displayed content. A processing unit connected to the frequency detector, display device, and electrode device receives data on intrinsic and observed frequencies. The processing unit compares these frequencies to determine an alignment metric. The alignment metric is used to estimate the presence and severity of substances in the environment shown in the live feed or image, based on the degree of agreement between the observed frequency and the intrinsic frequency.

Description

Technical Field

[0001] Embodiments of the present invention generally relate to frequency-based detection systems, and more particularly to frequency-based detection systems that use artificial intelligence techniques to identify biological viruses, bacteria, chemical substances, elements present in the periodic table, and their severities.

Background Art

[0002] Matters mentioned in the background section should not be considered prior art merely for the reason that they are mentioned in that section. Similarly, problems mentioned in the background section and problems related to its subject matter should not be assumed to have been already recognized in the prior art. The matters described in the background section merely show different approaches, and in some cases, they may themselves correspond to embodiments of the claimed technology.

[0003] Procedures and practices in medicine have been greatly affected by the increasing use of technology in this field. Medicine has undergone numerous changes as a result of this integration. The increasing use of wireless networks in hospitals and other biomedical facilities is an example of such technology having an impact. A large number of diseases, such as diabetes, heart disease, cancer, etc., affect many people around the world, and tens of millions of lives are taken every year. Regular monitoring can contribute to the prevention or management of specific diseases and may improve the prognosis of patients. For example, since diabetes is an abnormal blood glucose level over a long period, blood glucose levels and diabetes are closely related conditions. Therefore, continuous blood glucose monitoring is essential for the management of this disease.

[0004] In modern times, there are various tests for identifying bacteria, viruses, chemical substances, and radioactive elements on the periodic table. However, these tests are expensive and not widely spread, so they often do not meet the large demand. As a result, regulations regarding testing have been established in many countries. These guidelines require testing for both people and products, but there are still challenges in ensuring consistent detection accuracy.

[0005] Frequency-based detection systems are an innovative technology that has emerged at the intersection of physics, biology, and engineering. The innovative approach of this invention leverages the principles of frequency analysis and wave propagation to enable the detection and identification of a wide range of substances, including viruses, bacteria, chemical compounds, and elements of the periodic table. The development of this system represents a significant advance in non-invasive and rapid detection methods, with a wide range of applications envisioned, including healthcare and environmental monitoring.

[0006] At the core of frequency-based detection systems lies the concept of frequency analysis, which analyzes the intrinsic response of a substance to a specific frequency. In the context of health monitoring, these systems typically rely on propagating waves through a medium such as the human body. By transmitting precisely designed waveforms, the system can induce responses from substances present in the body, forming the basis for detection and identification. Various implementations of frequency-based detection systems interact with and investigate the internal composition of the human body using electromagnetic waves (e.g., radio frequencies) or acoustic waves (e.g., ultrasound).

[0007] Currently, there are no systems that use artificial intelligence to measure the severity of substances and monitor them on a frequency basis. Therefore, there is a need for a system that can measure the presence of viruses, bacteria, and chemicals in patients using non-invasive methods. This situation highlights the urgent need for testing methods that can accurately and rapidly identify the diverse chemical substances present in the human body.

[0008] Photobiomodulation is characterized by its ability to induce photobiological processes within cells. The relationship between these biological responses and emission wavelengths suggests the presence of photoreceptors. It has been shown that photoreceptors exist at the molecular and cellular levels, and that stimulation of these receptors activates multiple biological responses, including DNA / RNA synthesis, cAMP increase, protein and collagen synthesis, and cell proliferation [7]. Precise action spectra are needed for further research into the identification of photoreceptors and the cellular mechanisms of phototherapy (Azeemi, Raza, Yasinzai, 2009). This study is related to frequency detectors, where receptors receive information through a picture. This provides a biological basis for understanding the concept of wavelength testing. Frequency detectors capture signals from intracellular photoreceptors at the molecular level. When the wavelength of the image matches the wavelength of the substance (1, 2, and 3), the frequency detector measurement (above 70 Hz) increases. When the signal from the image does not match the wavelength of the substance (1, 2, and 3), the result is confirmed to be in the range of 50-55 Hz. [Overview of the Initiative]

[0009] Embodiments of the present invention disclose a frequency-based detection system for the precise identification and assessment of the presence and severity of substances. The system comprises an input mechanism configured to receive samples of one or more target substances, either as raw materials or solutions (the solution being saline solution containing the frequencies of the target substances) or as visual representations in the form of images or videos; a frequency detector configured to identify the intrinsic frequencies of each target substance, or intrinsic frequencies from visual representations; a display device configured to display live video or images to a volunteer; an electrode device configured to transmit electromagnetic signals corresponding to the volunteer's observed frequencies, which are held by the volunteer and influenced by their concentration on the live video or images presented on the display device; and a processing unit capable of communicating with the frequency detector, display device, and electrode device. The processing unit is configured to receive data from the frequency detector indicating the intrinsic frequencies of one or more target substances. It also acquires data indicating observed frequencies from the electrode device while the volunteer is gazing at the live video or images. The intrinsic frequencies are compared with the observed frequencies. An alignment metric between the observed frequencies and the intrinsic frequencies is determined, with a predetermined degree of alignment indicating a malfunction. Furthermore, based on the determined alignment metrics, the presence and potential severity of one or more target substances present in the environment, as shown in live video streaming or still images, are estimated.

[0010] According to one embodiment of the present invention, one or more target substances have known frequency signatures and frequencies pre-stored in a detector. The one or more target substances may be selected from, but are not limited to, viruses, bacteria, chemicals, radioactive elements in the periodic table, or combinations thereof. In one embodiment of the present invention, the system further comprises a digital repository configured to store multiple signal frequencies corresponding to multiple organs and diseases in order to facilitate the selection of therapeutic agents based on specific intrinsic frequencies associated with each state.

[0011] In one embodiment of the present invention, the display device is connected to a camera, a drone, and satellite imagery, and receives a stream of live video from a remote location via transmission technology.

[0012] In one embodiment of the present invention, the electrode device includes a plurality of electrodes, which are configured to form a circuit via the body of a volunteer, thereby improving the accuracy of the observed frequency data.

[0013] In one embodiment of the present invention, the volunteer is a healthy volunteer, and the electromagnetic vibrations of the volunteer are used to detect dissonant regions in a video or image.

[0014] In one embodiment of the present invention, the processing unit includes an integrated spectrum analyzer, which is configured to perform spectral analysis on the natural frequencies received from the sample and the observed frequencies received from volunteers, and to determine the frequency consistency.

[0015] In one embodiment of the present invention, the processing unit further comprises an artificial intelligence module, which is configured to automatically analyze and interpret a comparative analysis between natural frequencies and observed frequencies.

[0016] In one embodiment of the present invention, the artificial intelligence module uses a machine learning algorithm to improve the accuracy of the system over time based on accumulated inspection data.

[0017] In one embodiment of the present invention, the frequency detector is further configured to calibrate the intrinsic frequency of a substance based on a reference database of known substances.

[0018] In one embodiment of the present invention, the system further comprises an output device for displaying an alignment metric between an observed frequency and an intrinsic frequency, the output device including a gauge with a scale indicating normal and abnormal frequency matching ranges.

[0019] In one embodiment of the present invention, if the alignment metric determined by the processing unit and displayed on the output device reaches or exceeds 60 Hz, it indicates the presence of one or more target substances in the environment shown in the live video stream or image.

[0020] In one embodiment of the present invention, the processing unit is further configured to record the results of each inspection procedure and create a log including the date, time, substance identification, and severity assessment.

[0021] In one embodiment of the present invention, comparative analysis for determining alignment metrics is performed in real time, making it possible to immediately determine the presence and potential severity of a substance while a volunteer is involved with the image or video.

[0022] According to one embodiment of the present invention, the system is configured to operate in a variety of environments, including laboratory settings, field work, and remote locations made possible by a portable power supply option.

[0023] According to another aspect of the present invention, the system is further configured to analyze an individual's image to determine their life status and cause of death. Here, the processing unit is configured to acquire data indicating the observed frequency from an electrode device while a volunteer is observing a live video or image of the deceased displayed on a display device. Based on the acquired data from the volunteer, the observed frequency is determined, and the individual's condition is determined as follows: If the observed frequency is less than 20 Hz, the person is determined to be deceased; or If the observed frequency exceeds 60 Hz and is localized to a specific organ, it indicates death due to a disease affecting that organ; or If the observed frequency exceeds 60Hz across all organs, it indicates death due to poisoning. [Brief explanation of the drawing]

[0024] To understand the above features of the present invention in detail, a more specific description of the invention, which briefly summarizes the above content, can be made with reference to the embodiments illustrated in the accompanying drawings. However, the accompanying drawings show only representative embodiments of the present invention and do not limit the scope of the present invention. The present invention may allow other equally effective embodiments. These other features, advantages, and effects of the present invention will become apparent by referring to the following figures. The same reference numbers indicate the same structure in each figure, as follows.

[0025] [Figure 1] FIG. 1 shows a frequency-based detection system for precise identification and evaluation of the presence and severity of substances according to an embodiment of the present invention.

[0026] [Figure 2A] According to an embodiment of the present invention, an information flow of an exemplary implementation of the system of FIG. 1 is shown. <* [Figure 2B] According to an embodiment of the present invention, an information flow of an exemplary implementation of the system of FIG. 1 is shown. [Figure 2C] According to an embodiment of the present invention, an information flow of an exemplary implementation of the system of FIG. 1 is shown. [Figure 3A] [Figure 3B] [Figure 3C]

Mode for Carrying Out the Invention

[0027] While the present invention is described herein with reference to embodiments and illustrated examples, those skilled in the art will understand that the invention is not limited to the drawings or embodiments described herein, nor do they indicate the scale of each component. Furthermore, some components that may constitute the present invention may not be shown in some drawings for the sake of explanation, and such omissions do not limit the described embodiments in any way. The drawings and detailed descriptions thereof are not intended to limit the invention to any particular form disclosed. Moreover, the present invention encompasses all modifications, equivalents, and substitutions that fall within the scope of the invention as defined by the appended claims. The word “may” as used herein is used in an allowable sense (i.e., “possible” rather than an obligatory sense (i.e., “must”). Also, “a” or “an” means “at least one,” and “plurality” means “one or more” unless otherwise specified. Furthermore, the terms and expressions herein are used for the sake of explanation and should not be construed as limiting their scope. Expressions such as “including,” “comprising,” “having,” “containing,” and “involving,” and their variations, are intended to broadly encompass subsequent descriptions, their equivalents, and additional undescribed matters, and do not exclude other additives, components, ingredients, or processes. Furthermore, the term “comprising” is considered synonymous with “including” or “containing” for the applicable legal purposes. Descriptions of documents, actions, materials, apparatus, articles, etc., in this specification are included solely to provide context for the present invention. It is not implied or indicated that any or all of these constitute prior art or were publicly known in the art related to the present invention.

[0028] In this disclosure, where the transition phrase "comprising" precedes a composition, element, or group of elements, it is understood that the invention also covers cases where the transition phrases "consisting of," "consisting," "selected from the group of consisting of," "including," or "is" are used prior to the description of the composition, element, or group of elements, and vice versa.

[0029] The present invention will be described below with reference to various embodiments. Reference numerals in the accompanying drawings refer to the same elements throughout this specification. However, the present invention can be implemented in a variety of forms and should not be construed as being limited to the embodiments described herein. Rather, these embodiments are provided to ensure that this disclosure is sufficient and complete and to fully convey the scope of the invention to those skilled in the art. In the following detailed description, numerical values ​​and ranges are given with respect to each aspect of the embodiments described. These numerical values ​​and ranges are for illustrative purposes only and are not intended to limit the scope of the claims. In addition, several materials applicable to various embodiments are identified. These materials are illustrative and are not intended to limit the scope of the invention.

[0030] In the attached drawings, Figure 1 shows a frequency-based detection system 100 for precise identification and assessment of the presence and severity of a substance. As shown in Figure 1, the system 100 includes an input mechanism, a frequency detector 104, a display device 112, an electrode device 106, and a processing unit 110, all of which play important roles in the function of the present invention.

[0031] The input mechanism is configured to receive a sample of one or more target substances contained in the input cup 102, or a visual representation of them as images or videos. The input cup 102 is a key component designed to hold a sample of one or more target substances for analysis. In this specification, the group of one or more target substances identified in system 100 encompasses a wide range of entities, including but not limited to viruses, bacteria, chemicals, and radioactive elements in the periodic table. Each target substance has its own unique frequency signature, which system 100 is designed to detect and analyze. The versatility of the input cup 102 allows these substances to be contained in various forms, such as raw materials or solutions. If the substance is in the form of a solution, the solution is prepared to have a known frequency signature corresponding to the specific substance to be analyzed. Furthermore, system 100 can also utilize frequencies pre-stored in the detector, enabling rapid and efficient analytical processing.

[0032] From this perspective, the input cup 102 is constructed of a material inert to the substance held inside it and is designed not to interfere with frequency analysis. Its design is compatible with various forms of substances, from raw materials to solutions. The cup is equipped with a secure sealing mechanism to prevent contamination and maintain sample integrity. The inside of the cup may be coated or treated to maintain sample stability during analysis. As an essential component of system 100, the input cup 102 is positioned to allow for easy insertion and removal of samples, and to ensure a reliable connection with the frequency detector 104, enabling accurate frequency transmission and detection.

[0033] Furthermore, the frequency detector 104 functions as the primary sensor for determining the intrinsic frequency of each target substance within the input cup 102. This detector possesses advanced frequency sensing technology capable of detecting high-precision frequencies over a wide range. The detector's design minimizes noise interference while achieving maximum sensitivity to the frequencies emitted by the target substances. The device is directly connected to the input cup 102, enabling immediate and accurate frequency measurement as soon as the sample is placed in the cup. Depending on the properties of the analyte, the frequency detector 104 may include, but is not limited to, various sensors such as electromagnetic sensors, acoustic sensors, and piezoelectric sensors. To address attempts to evade detection by using the reciprocal of the substance's frequency to cancel out the identification signal, the system 100 is newly equipped with dual detectors (A and Ai). Detector A identifies the actual frequency of the substance, i.e., a direct match, and is responsible for identifying substances based on their unique vibrational signature, such as cannabis, certain drugs, and unapproved radioactive materials. On the other hand, the Ai detector is designed to detect the inverse frequency of the target substance, providing an advanced countermeasure against detection evasion using inverse frequencies. This dual detection approach significantly enhances the system's robustness by checking both A (actual frequency) and Ai (inverse frequency), ensuring accurate identification of substances even when evasion techniques are employed. This comprehensive approach results in a more reliable detection process, prevents false negatives, and ensures the system's effectiveness in identifying a wide range of substances under various conditions.

[0034] Furthermore, the display device 112 in system 100 functions as an interactive interface used by volunteers 108, playing a crucial role in facilitating the observational aspects of the detection process. This device is often a high-resolution screen capable of displaying live video or images with extreme clarity and precision. To accommodate diverse sources of visual content, the display device 112 is versatile and designed to support connections to external cameras, drones, and satellite imagery 114. This functionality enables the real-time reception and display of live video streams from remote locations, significantly improving the applicability of system 100 to a variety of applications.

[0035] Common display devices 112 used in this type of system include, but are not limited to, LED, LCD, and OLED screens, and are known for their high-quality image reproduction and energy efficiency. These devices are user-friendly, featuring easy navigation of displayed content and an intuitive selection interface. The ergonomic characteristics of the display device 112 have also been carefully considered, and its placement is optimized to allow volunteers 108 to view comfortably and attentively. Some display devices 112 have touchscreen functionality, providing an interactive experience and facilitating a more engaging and effective interaction with the system 100. The combination of high-resolution display technology and advanced connectivity options makes the display device 112 a critical component of the system 100, directly impacting the observation frequency of volunteers 108 and, consequently, the effectiveness of the detection process.

[0036] In addition, the electrode device 106, a core component of the frequency-based detection system 100, is precisely designed to accurately detect and transmit electromagnetic signals corresponding to the observed frequencies of volunteer 108. This device consists of multiple electrodes, each ergonomically designed for comfortable and secure attachment. The electrodes can be held in the hands of volunteer 108 or, if necessary, attached to specific parts of the body to obtain accurate and clear signal measurements.

[0037] The materials used for the electrodes are carefully selected for their excellent biocompatibility, particularly to minimize the risk of skin irritation and allergic reactions during prolonged use. This consideration is crucial in maintaining the comfort of the volunteers and ensuring their safety when interacting with the system. The electrodes are typically composed of conductive materials with high conductivity and low resistance, such as silver or gold, which facilitates the efficient transmission of electromagnetic signals. Given the diversity of frequencies across organs and their impact on the diagnosis and treatment of various diseases, the system has been enhanced with the ability to capture and digitally store multiple signal frequencies. This improvement allows for precise selection of treatments based on frequencies specific to each organ or disease. For example, the system recognizes detailed frequencies specific to electroencephalography (EEG) and electrocardiogram (ECG) and records these and other important signal frequencies in a comprehensive digital repository. This function ensures that an individualized treatment approach is implemented by matching the resonant frequencies of therapeutic interventions with the characteristic frequencies of the target organ or condition.

[0038] In addition to ergonomic design and biocompatible materials, the electrode device 106 includes a flexible and durable cable system 100 that connects to the processing unit 110. This connection is essential for ensuring uninterrupted transmission of electromagnetic signals from the volunteer 108 to the processing unit 110. The cable needs to be both flexible enough to allow the volunteer 108 to move freely and durable enough to maintain performance even with regular use.

[0039] The functionality of the electrode device 106 is further enhanced by its ability to form circuits through the body of volunteer 108. This function improves the accuracy of the observed frequency data acquired by the device. By forming circuits, the device can more accurately detect the 108 electromagnetic vibrations of the volunteer, which are used by system 100 for comparative analysis with the natural frequencies of the target material group.

[0040] Furthermore, at the core of system 100 is a processing unit 110 consisting of advanced hardware and software designed to process and analyze data received from the frequency detector 104 and electrode device 106. The processing unit 110 includes arithmetic functions such as a storage unit 1102 capable of storing machine-readable instructions. Machine-readable instructions can be loaded into the storage unit 1102 from non-temporary machine-readable media such as CD-ROMs, DVD-ROMs, and flash drives. Machine-readable instructions can also be loaded into the storage unit 1102 in the form of computer software programs. The storage unit 1102 can thus be selected from a group consisting of EPROMs, EEPROMs, and flash memory. The processing module also includes a processor 1104 that is operationally connected to the storage unit 1102.

[0041] The processing unit 110 may further include a spectrum analyzer 1106. As an essential component within the processing unit 110, the spectrum analyzer 1106 serves as a fundamental instrument in the precise identification and assessment of the presence and severity of substances. This advanced electronic device acts as a crucial analytical tool, enabling the system 100 to analyze electromagnetic frequencies with exceptional accuracy.

[0042] The spectrum analyzer 1106 comes in various types, selected according to the specific requirements of the application. Notable classifications include sweep-tuned, real-time, and vector spectrum analyzers 1106. Sweep-tuned analyzers are suitable for measuring continuous waveforms, while real-time analyzers excel at instantaneous signal acquisition. The vector spectrum analyzer 1106 provides both amplitude and phase data, making it ideal for achieving a comprehensive understanding of the frequency domain.

[0043] In the context of this invention, the spectrum analyzer 1106 plays a central role in examining two distinct frequency groups: the intrinsic frequency characterizing the target substance in the input cup 102 and the observed frequency transmitted from the volunteer 108 via the electrode device 106. By performing comparative analysis and matching of these frequencies, the spectrum analyzer 1106 enables the processing unit 110 to identify the presence of the target substance and its potential severity. To enhance the system's detection capabilities, a new advanced comparative analysis framework has been introduced that can interpret data obtained from images and videos in addition to conventional raw material samples. This framework operates on the principle that each data format, such as raw materials, frequencies, or their visual representations, contains individual frequency information. As a result, the system can process data in three different formats: 1) the physical raw material itself, 2) the digitally captured frequency of the raw material, and 3) the visual representation of the raw material, such as an image or video. This tripartite approach allows the system to perform sophisticated comparative analysis, including the identification of resonances between various data formats (when F1=F2), and to detect the presence of high-frequency materials. For example, by comparing and analyzing images of a substance like cannabis with recording frequencies for various forms of that substance, it is possible to detect whether an individual or their belongings have come into contact with or been in close proximity to cannabis.

[0044] Furthermore, the processing unit 110 can implement artificial intelligence and deep learning technologies for data analysis, data integration, and real-time data presentation. To this end, the processing unit 110 can incorporate an artificial intelligence module designed to automate the complex task of analyzing and interpreting comparative data obtained from the intrinsic frequencies of the target substance group and the observed frequencies recorded by volunteers 108. This module functions as a computational framework that improves the efficiency of system 100 by streamlining the analysis process. In addition, by employing machine learning algorithms, system 100 can continuously improve its accuracy through the accumulation of test data. This iterative learning mechanism allows system 100 to adaptively improve its ability to identify the presence and potential severity of target substances in the depicted environment, ultimately contributing to improved accuracy and reliability of system 100 as a whole.

[0045] In one embodiment of the present invention, the system 100 further includes an output device 116, which is designed to visually provide an alignment metric between the observed frequency and the natural frequency. The primary function of the output device 116 is to clearly and intuitively display the degree of agreement or difference between the frequencies under examination.

[0046] In the assumed embodiment of the present invention, the output device 116 is equipped with a gauge, which is a basic element of visual display. This gauge is provided with a scale that divides different ranges, allowing the frequency-matched spectrum to be effectively divided into multiple categories. The scale functions as an indicator of how well the observed frequency matches the natural frequency, enabling quick and easy evaluation of the results.

[0047] The scale of the output device 116 is strategically tuned to include two main frequency matching regions: "normal" and "abnormal." These regions serve as the user's reference points, allowing for evaluation of whether the observed frequency is within the expected acceptable range or deviates significantly from the reference.

[0048] Within the "normal" range, the gauge indicates a high degree of agreement between the observed frequency and the natural frequency, suggesting a high degree of correspondence. For example, in practical applications, the 60 Hz frequency, often associated with standard power supplies, can serve as a representative value within this "normal" range. This matching indicates that system 100 detects minimal or almost no presence of the target material group, thereby signifying a "clean" or "normal" environment.

[0049] On the other hand, the "anomalous" range indicates a significant discrepancy between the observed frequency and the natural frequency on the scale. When the gauge needle points in this region, system 100 visually warns that it has detected a significant mismatch, suggesting the possible presence of a target substance that deviates from the expected frequency signature. This "anomalous" mismatch can serve as an indicator of the severity or concentration of the substance in question in the analyte sample.

[0050] Those skilled in the art will understand that a "normal" frequency matching range corresponds to a predetermined matching threshold, and an "abnormal" frequency matching range indicates a deviation exceeding this predetermined threshold. This aligns with the purpose of the gauge, which, by utilizing the predetermined threshold, provides a clear distinction between normal and abnormal alignment.

[0051] The output device 116, through its gauge and scale design, provides a means for the user to quickly and easily interpret the frequency alignment metric, with 60 Hz frequency serving as a representative example of the "normal" range. This visual feedback allows the user to make appropriate decisions based on the alignment evaluation, such as taking further action, conducting additional inspections, or confirming that there are no abnormalities.

[0052] The configuration of the output device 116 described herein is an example, and it should be noted that specific scale divisions and additional visual elements may be modified according to user preferences and specific application requirements. Nevertheless, the basic function of the output device 116 remains consistent, serving as an essential tool for evaluating the alignment between the observed frequency and the natural frequency, thereby enhancing the system's usefulness in material detection and evaluation.

[0053] The present invention operates as follows:

[0054] Figures 2A-2C show the information flow in an example of the system 100 shown in Figure 1, according to an embodiment of the present invention. As shown in Figure 2A, the method begins with the preparation of a sample containing one or more target substances, which is placed in the input cup 102 of the system 100. The input cup 102 is designed to hold substances such as viruses, bacteria, chemicals, and radioactive elements, and its inertness to these substances enables accurate frequency analysis. Next, a frequency detector 104 connected to the input cup 102 starts the detection process. The frequency detector identifies the intrinsic frequency of each target substance in the cup. This intrinsic frequency is a unique signature for each substance and plays an important role in the subsequent comparison process.

[0055] Simultaneously, volunteer 108 interacts with system 100 and focuses on live video or images displayed on display device 112. In one embodiment of the present invention, healthy volunteer 108 is selected. A healthy volunteer 108 may be someone who has consented to participate in the clinical trial and is in good health. Volunteer 108 does not have any acute or chronic disease and is not receiving any serious drug therapy. This ensures that volunteer 108 is a fair participant in the clinical detection process.

[0056] This involvement is important and leads to the generation of observed frequencies that reflect Volunteer 108's focus and emotional response to the displayed content. For example, an electrode device 106 may be held by Volunteer 108 and configured to interact specifically with Volunteer 108's body. One or more electrodes of the electrode device 106 are placed on the skin of Volunteer 108's hand and connected to an external device. This external device generates gentle electromagnetic impulses that interact with Volunteer 108's body. As a result of this interaction, Volunteer 108's body generates specific frequencies, which manifest as responses to stimuli viewed on the display device 112. These images and their sources (e.g., cameras, drones, satellite imagery 114) significantly influence Volunteer 108's level of involvement. This frequency is referred to as the “observed frequency” and is essentially a manifestation of Volunteer 108’s own vibrations or electromagnetic vibrations. This frequency is influenced by the cognitive and emotional responses Volunteer 108 exhibits to the images.

[0057] These vibrations or electromagnetic vibrations are detected by electrodes and transmitted to the processing unit 110 of the detection system 100. The processing unit 110, which includes a spectrum analyzer 1106 shown in Figure 1 and is equipped with advanced analytical capabilities, uses this observed frequency data for comparative analysis. Notably, the electromagnetic vibrations of volunteers 108 are used by the system 100 to detect disharmonious regions in the environment depicted in live video streaming or still images.

[0058] A gentle impulse transmitted from an external device to the body of volunteer 108 plays a crucial role in this process. This ensures that volunteer 108's own vibrations are accurately captured and transmitted through the electrodes. In this way, system 100 can leverage volunteer 108's physiological response to visual stimuli to achieve effective material detection and evaluation.

[0059] In this way, both the natural frequency from the frequency detector 104 and the observed frequency from the electrode device 106 are transmitted to the processing unit 110. The processing unit 110, equipped with a spectrum analyzer 1106 and artificial intelligence functions, receives and processes these datasets.

[0060] As shown in Figures 2B-2C, upon receiving these frequencies, the processing unit 110 performs a comparative analysis using an advanced algorithm. This analysis is not merely a comparison, but a sophisticated process to determine the degree of correlation or deviation between the two frequencies. The results of this comparison are quantified in the form of an alignment metric.

[0061] In this specification, the alignment metric quantifies the degree of equivalence between observed frequencies and natural frequencies. It is a measurable value that clearly indicates how well the volunteer's 10⁸ frequencies match the frequencies of the target material. This metric is calculated based on several factors, including the amplitude, phase, and waveform characteristics of the frequencies involved.

[0062] A key characteristic of alignment metrics is their ability to indicate a malfunction. A malfunction occurs when there is a significant discrepancy between the observed frequency and the natural frequency. This condition suggests an anomaly or irregularity in the environment or the object being analyzed. For example, a high degree of alignment indicates a normal or baseline state, meaning the absence or minimal presence of the target material group. Conversely, a significant deviation from alignment suggests the presence of the target material group, and may further indicate its type and severity.

[0063] In practical terms, the alignment metric functions as a diagnostic tool within System 100. This allows System 100 to detect the presence of target substances with high accuracy and assess the potential severity of these substances in the given environment. Therefore, this metric is not merely a numerical value, but a crucial indicator of System 100's diagnostic capabilities, directly influencing decision-making processes and subsequent actions.

[0064] After the alignment metric is determined by the processing unit 110, the system 100 estimates the presence and potential severity of the target substance group. At this stage, the AI ​​module effectively enhances the analysis of frequency comparison data in the context of a specific frequency range. As described in the disclosure, the system 100 can detect substances by comparing the frequencies stored in the sample in the input cup 102 with the frequencies emitted by the volunteer 108. For example, as shown in Figure 2B, if the alignment metric shows a frequency deviation of less than 60 Hz, it suggests that the environment being analyzed by the volunteer 108 watching the image or live video is in a "normal" state, meaning that the presence of the target substance group is minimal or not detected. On the other hand, Figure 2C shows that a deviation exceeding 60 Hz indicates an "abnormal" state, which is crucial in identifying the presence of a substance at a specific location. For example, if a drone or satellite is broadcasting live video of a landscape and the alignment metric exceeds 60 Hz, the system 100 determines that a substance is present at the specific location being broadcast.

[0065] The output device 116 of system 100 plays a crucial role in visually displaying these results. Equipped with gauges and scales, the output device 116 effectively displays alignment metrics, enabling an intuitive understanding of the detection results. This visualization is essential for users to quickly determine whether or not a substance is present in the environment under investigation. The scale on the gauges is designed to clearly distinguish between "normal" and "abnormal" areas, directly correlating with the presence or absence of the substance at specific locations under monitoring.

[0066] In one embodiment of the present invention, the processing unit 110 can record these results in real time, including the identification of substances and the assessment of their severity. This real-time analysis function ensures that the detection and evaluation of substances, as well as the determination of their specific location, are performed quickly and accurately.

[0067] Furthermore, the adaptability and improvement over time of System 100 are important aspects. System 100 improves its accuracy by using machine learning algorithms based on accumulated test data via the AI ​​module. This continuous learning and adaptation is particularly important for improving the ability to accurately detect the presence of substances in various locations, ensuring the reliability and effectiveness of System 100 under diverse environmental conditions.

[0068] Essentially, System 100 possesses the capabilities of substance presence estimation, visual display of results, real-time data recording, machine learning-based adaptation, and target substance localization, making it an advanced and comprehensive solution in substance detection and severity assessment.

[0069] According to another aspect of the present invention, A specialized application of this frequency-based detection system 100 is configured to analyze images of individuals to determine their survival status and identify the cause of death. This advanced functionality is based on the ability of the processing unit 110 to acquire and analyze data indicating observed frequencies generated when volunteers 108 view images of deceased individuals.

[0070] When volunteer 108 is exposed to still images or live video streams displayed on the device, their focused gaze generates an observation frequency, which is captured by the electrode device 106. This observation frequency is an important element in subsequent analysis. The processing unit 110 evaluates this frequency and determines the survival status and presumed cause of death of individuals in the images.

[0071] System 100 identifies the state of an individual based on a threshold of a specific observation frequency. For example, if the recorded observation frequency is less than 20 Hz, System 100 determines that the individual is dead. This low frequency threshold indicates a lack of vital signals normally found in living individuals.

[0072] Furthermore, System 100 can also identify the cause of death by analyzing the observed frequencies in more detail. If the observed frequency exceeds 60 Hz and is localized to a specific organ, System 100 estimates that the death was caused by a disease affecting that organ. This conclusion is based on the understanding that specific diseases affect the electromagnetic signature of specific organs, and that this effect is reflected in the observed frequencies.

[0073] If the observed frequencies rise uniformly above 60 Hz across all organs, System 100 identifies poisoning as a likely cause of death. This high frequency range across multiple organs suggests a typical System 100 effect in cases of poisoning.

[0074] The system 100 of this embodiment demonstrates potential usefulness in the fields of forensic medicine and medical diagnosis, providing a novel approach to determining the state of life and identifying the cause of death. By utilizing observation frequency analysis, the system 100 can analyze images non-invasively, rapidly, and with high accuracy, providing important insights into the state of life and cause of death of individuals. experiment:

[0075] The experiment began with volunteers undergoing examinations without viewing any images. The examinations included the brain, thyroid, lungs, heart, stomach, liver, and kidneys. During these examinations, volunteers were not shown any images. This was done solely to confirm the presence or absence of any medical problems within the subjects that the system could detect. This examination was conducted to ensure that volunteers were in perfect health and able to participate in the experiment. These were considered control variables to be compared with the results after image presentation. Confirming that volunteers were healthy was important, as individuals with specific organs (brain, thyroid, lungs, heart, stomach, liver, and kidneys) would yield more accurate results when detecting substances 1, 2, and 3. Furthermore, the room temperature was maintained at 24°C, and no one was allowed to enter the room. This allowed volunteers to focus solely on the images.

[0076] Subsequently, volunteers are shown images of patients containing substance 1, 2, or 3, and undergo the examination again. They are examined through the brain, thyroid, lungs, heart, stomach, liver, and kidneys. The purpose of this examination is to show whether the results change depending on whether the images contain the substance (1, 2, and 3). Table 1 shows the results of this experiment. Due to the regulations regarding drawings in the patent specification, the actual (color) images shown to the volunteers are not provided, but the images shown to the volunteers are as follows. Image 1: Covid-19 patient Image 2: Marijuana Image 3: Uranium-92, a periodic table element Results / Analysis:

[0077] The average value for the initial test (without images) was 54.36, which is considered normal or within the healthy range. However, the average value after presenting images increased to 74.82, showing a significant change from the previous test. This indicates that the device can detect substance 1 using images.

[0078] The average value in the first trial, which did not use images, was 54.3 Hz, which is considered to be within the neutral range. On the other hand, the average value in the second trial, in which patients viewed images, was 78.35 Hz, indicating that the detection method was functioning effectively and detecting substance 2 through the images.

[0079] The average value in the initial test (without images) was 54.25 Hz, which is considered to be within the normal range. When images of substance 3 were presented to the patients, the average value rose to 71.9 Hz, which is considered to be in the high range. This suggests that the device can detect substance 3 via images.

[0080] This invention has several advantages. It reflects its innovative approach and advanced technological integration. • Precise substance detection: A major advantage of this system is its ability to precisely detect a wide range of substances, including viruses, bacteria, chemicals, and radioactive elements. This accuracy is achieved by utilizing the unique inherent frequencies of each substance. • Non-invasive analysis: This method, which detects substances by comparing electromagnetic signals and frequencies, is non-invasive. This characteristic is particularly useful in sensitive environments and situations where conventional invasive methods cannot be performed or are undesirable. • Real-time data processing and analysis: This system can process and analyze data in real time, allowing for immediate determination of the presence and severity of substances, which is extremely important in time-constrained situations. • Advanced AI and machine learning integration: The introduction of AI and machine learning algorithms allows the system to continuously improve its accuracy and adapt to new data, increasing its effectiveness over time. • Versatile applications: This system can be used in a variety of environments, from controlled laboratory settings to field work and remote locations, and is designed to be highly portable and adaptable. • Determination of life status and identification of cause of death: In a special embodiment of this system, it is possible to determine the life status and identify the cause of death through image analysis, which is an extremely useful function in the field of forensic medicine. • User-friendly interface: The system's interface, including the display device and output device with intuitive gauges and scales, is designed with ease of use in mind and is accessible to a wide range of users. • Recording and Documentation: The ability to record the results of each test procedure, including substance identification and severity assessment, is useful for accurate record keeping and research purposes. • Customizable frequency range: The system can be customized to meet specific needs and situations by using pre-saved frequencies or by using a frequency calibration function based on a reference database. • Enhanced safety and environmental monitoring: By detecting substances that can be harmful in various environments, this system can improve safety and environmental monitoring capabilities. • Integration with diverse data sources: By integrating with external cameras, drones, and satellite imagery to acquire live video streams, the system's applicability is expanded and its functionality is enhanced. • Advanced electrode design: The design of the electrode device enables precise and clear signal measurement, contributing to the overall accuracy of the system.

[0081] These advantages highlight the system's innovative approach to substance detection and analysis, providing a comprehensive solution that combines precision, versatility, and convenience.

[0082] Furthermore, it should be understood that a communication network and a data repository (local or cloud-based storage) are also available in this invention. The communication network may be a short-range communication network and / or a long-range communication network. The communication interface may include, but is not limited to, a serial communication interface, a parallel communication interface, or a combination thereof. The communication network enables wireless and remote operation of the device, and the data repository may include pre-stored data of known frequencies of target material groups, trained AI or machine learning models, etc.

[0083] Generally, as used herein, the term “module” refers to logic embodied in hardware or firmware, or a collection of software instructions written in a programming language such as Python, R, C, C#, Java®, or assembly. One or more software instructions within a module may be incorporated into firmware such as an EPROM. It will be apparent to those skilled in the art that a module may include connected logic circuits such as gates and flip-flops, and may also include programmable units such as programmable gate arrays or processors. Each module described herein may be implemented as a software and / or hardware module and stored in any type of computer-readable medium or other computer storage device.

[0084] Furthermore, even if one or more operations are described as being performed or associated with a specific module, device, or entity, such operations may be performed or associated with any module, device, or entity. Therefore, any function or operation described as being performed by a module may be alternatively performed by another server, cloud computing platform, or a combination thereof.

[0085] Various modifications to these embodiments will be apparent to those skilled in the art from the description herein and the accompanying drawings. The principles of the various embodiments described herein can also be applied to other embodiments. Accordingly, this description is not limited to the embodiments shown with the accompanying drawings, but is intended to cover the maximum extent consistent with the principles and novel and inventive features disclosed or suggested herein. Accordingly, it is expected that the present invention will encompass all other alternatives, modifications, and variations included in the present invention and the appended claims.

Claims

1. A frequency-based detection system for precisely identifying and evaluating the presence and severity of a substance, the system comprising: An input mechanism configured to receive either a sample of one or more target substances in the form of raw materials or solutions, or a visual representation thereof as an image or video; A frequency detector configured to determine the intrinsic frequency of each individual target substance, or its visual representation thereof; A display device configured to show live video or images to volunteers; An electrode device, held by a volunteer and configured to transmit an electromagnetic signal corresponding to the volunteer's observation frequency, wherein the observation frequency is influenced by the volunteer's focused engagement with live video or images presented on a display device; A processing unit capable of communicating with a frequency detector, display device, and electrode device; The processing unit is configured to perform the following processes: Receiving data from a frequency detector indicating the intrinsic frequencies of one or more target substances; To acquire data indicating the observed frequency from an electrode device while a volunteer observes live video or images; Comparing the natural frequency with the observed frequency; The alignment metric between the observed frequency and the natural frequency is determined, and a predetermined degree of alignment may indicate a malfunction; To estimate the presence and potential severity of one or more target substances in an environment depicted in live video streaming or still photographs, based on determined alignment metrics.

2. In the system according to claim 1, the one or more target material group has a known frequency signature and a frequency pre-stored in the detector, The aforementioned group of one or more target substances is selected from viruses, bacteria, chemical substances, radioactive elements in the periodic table, or combinations thereof.

3. The system according to claim 1 further comprises a digital repository for storing signal frequencies corresponding to multiple organs and diseases, thereby facilitating the selection of therapeutic methods based on the intrinsic frequencies associated with each condition.

4. The system according to claim 1 is further configured such that the display device is connected to a camera, a drone, and satellite imagery, and receives a stream of live video from a remote location via transmission technology.

5. The system according to claim 1 further includes an electrode device which comprises multiple electrodes configured to form a circuit through the body of a volunteer, thereby improving the accuracy of the observed frequency data.

6. The system according to claim 1 is further configured such that the volunteer is a healthy volunteer and the system uses the electromagnetic vibrations of the volunteer itself to detect discordant regions in the video or image.

7. The system described in claim 1 is further configured such that the processing unit has an integrated spectrum analyzer and can perform spectral analysis of the natural frequencies received from the sample and the observed frequencies received from the volunteers to determine the frequency consistency.

8. The system according to claim 1 further includes an artificial intelligence module configured to automatically analyze and interpret a comparative analysis between natural frequencies and observed frequencies.

9. In the system described in claim 7, the artificial intelligence module utilizes a machine learning algorithm to improve the accuracy of the system over time based on accumulated test data.

10. In the system according to claim 1, the frequency detector is further configured to calibrate the intrinsic frequency of a substance based on a reference database of known substances.

11. The system according to claim 1 further comprises an output device configured to display an alignment metric between an observed frequency and an intrinsic frequency, the output device including a gauge having a scale indicating normal and abnormal frequency alignment ranges.

12. In the system according to claim 10, if the alignment metric determined by the processing unit and displayed on the output device reaches or exceeds 60 Hz, it indicates that one or more target substances are present in the environment shown in the live video stream or image.

13. In the system according to claim 1, the processing unit is further configured to record the results of each inspection procedure and to create a log including the date, time, identification of the substance, and severity assessment.

14. In the system described in claim 1, comparative analysis for determining alignment metrics is performed in real time, and the presence and potential severity of a substance can be immediately determined while the volunteer is involved with the image or video.

15. The system described in claim 1 is configured to operate in a variety of environments, including laboratory environments, field work, and remote locations, which are made possible by a portable power supply option.

16. In the system described in claim 1, the system is further configured to analyze an individual's image to determine their life status and identify the cause of death. Here, the processing unit is configured as follows: While volunteers monitor live video and images, and images of deceased individuals are displayed on the display device, data indicating the observed frequency is acquired from the electrode device. Based on data obtained from volunteers, the observed frequency is determined, and the individual's state is identified as follows: If the observed frequency is less than 20 Hz, the death will be recognized. If the observed frequency exceeds 60 Hz and is localized to a specific organ, the death will be recognized as being due to a disease related to that organ. If the observed frequency exceeds 60Hz in all organs, the death will be classified as being due to poisoning.

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