Patent Publication Number: US-2023152161-A1

Title: Enhanced cooker hood with sensors for remote temperature measurement and presence detection

Description:
BACKGROUND 
     Technical Field 
     Description of the Related Art 
     Cooker hoods come with various features to accommodate the growing needs of customers. The cooker hood includes ventilation systems and alarm systems as well as other features. Additional features can be implemented through various type of sensors (e.g., smoke detectors, infrared sensors, temperature sensors, or the like). 
     However, incorporating various sensors and devices in the cooker hood likely drives up the cost of the cooker hood. Generally the cooker hood is placed over a stove top or burners (electric, gas, induction, etc.). As a result, heat is frequently received or interacts with the sensors and the various devices incorporated in the cooker hood, which may heat up the devices and deteriorate the functionality of the devices. This can decrease the life expectancy of the sensors and devices. 
     BRIEF SUMMARY 
     One or more embodiments of the present disclosure provide a device that includes a sensor and a processor. The sensor collects infrared data and the processor processes the infrared data so that multiple functions are performed including temperature measurement and presence detection. Both functions of remote temperature measurement and presence detection are performed based on the same set of collected infrared data from the sensor. Further, because these functions are performed using the same data, the function of presence detection (e.g., motion sensing) and temperature measurement may be conducted at the same time (simultaneously or concurrently). Having one device that is capable of performing multiple functions can reduce the cost of the device and the cooker hood incorporating the device. 
     One example of the sensor includes a thermal infrared sensor. It may include a wafer-level processed and wafer-level packaged low-cost microelectromechanical system (MEMS) thermal sensor or a sensor based on CMOS-SOI-MEMS technology (also referred to as “TMOS”). The TMOS is a MEMS device based on a suspended, thermally isolated, micro-machined floating transistor, which absorbs infrared radiation. A resulting temperature change is transduced into an electric signal. The TMOS operates at a subthreshold region, therefore requiring low power consumption. Accordingly, the overall power consumption of the device can be reduced. 
     Further, the processor may include an application-specific integrated circuit (ASIC) that has low power consumption. The specific instructions or algorithms for processing the infrared data collected from the sensor to perform the function of temperature measurement and the function of presence detection may be programmed into the ASIC. 
     As such, a device according to one or more embodiments of the present disclosure is capable of performing multiple functions at a low cost and while having low power consumption. Further, the device takes into account various factors including the properties of the objects (e.g., types of material, emissivity of the material) within a field of view of the sensor as well as the temperature rise in the ASIC during operation caused by the heat from the objects within the field of view of the sensor. Field of view is the angle that a sensor can see. Accordingly, the device can also provide a temperature measurement with improved accuracy compared to those thermal sensors commercially available. 
     One embodiment of the present disclosure includes an alternative device having an infrared sensor having a field of view. The device further includes a processor coupled to the infrared sensor. In some embodiments, the processor includes a temperature determination circuit and a first compensation circuit. The first compensation circuit is configured to compensate temperature based on characteristics of one or more objects on and adjacent to a heat generating structure in the field of view. In one embodiment, the characteristics of one or more objects includes a type of a material and emissivity of the material. 
     Another embodiment of the present disclosure includes a system, such as a cooking surface and ventilation or lighting hood system. The system includes a heat generating source (coil, electric smooth, etc.), a support structure (fan or light or other overhead structure), and a sensing device. The support structure is above and aligned with the heat generating source. The support structure has a first surface facing the heat generating source. 
     In some embodiments, the device is on the first surface of the support structure and the sensing device has a field of view of at least parts of the heat generating source. Here, the sensor is configured to collect infrared data of one or more objects within the field of view. In one embodiment, the infrared data is indicative of infrared signals including an intensity of infrared light. 
     The device also includes a temperature determination circuit coupled to the sensor. The temperature determination circuit is configured to determine temperature of the one or more objects within the field of view based on the collected infrared data. The device further includes a first compensation circuit configured to compensate temperature based on emissivity of the one or more objects within the field of view. 
     Another embodiment is directed to a presence detection method. The method includes receiving first infrared data from one or more objects within a field of view of a sensor. The method includes applying a first low pass filter to the first infrared data and applying a second low pass filter to the first infrared data. Here, the second low pass filter is different from the first low pass filter. 
     The method further includes determining presence signals based on a difference between an outcome of applying the first low pass filter to the first infrared data and an outcome of applying the second low pass filter to the first infrared data. The method includes comparing the presence signals with a difference of a presence threshold and a hysteresis threshold; and determining a presence of a subject with the field of view based on comparing the presence signals with a difference of a presence threshold and a hysteresis threshold. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       Reference will now be made by way of example to the accompanying drawings. In the drawings, identical reference numbers identify similar elements or acts. In some drawings, however, different reference numbers may be used to indicate the same or similar elements. The shapes of various elements and angles are not necessarily drawn to scale, and some of these elements may be enlarged and positioned to improve drawing legibility: 
         FIG.  1    is a perspective view of a system according to some embodiments of the present disclosure. 
         FIG.  2    is a side view of a system according to some embodiments of the present disclosure. 
         FIG.  3    is a block diagram of a device according to some embodiments of the present disclosure. 
         FIG.  4    is a side view of a device having a lens according to some embodiments of the present disclosure. 
         FIG.  5 A  is a cross-sectional view of a device according to some embodiments of the present disclosure. 
         FIG.  5 B  is a cross-sectional view of a device having a lens mounted on a sensor according to some embodiments of the present disclosure. 
         FIG.  6 A  is a top view showing a positional relationship between a cooking plate and a sensor. 
         FIG.  6 B  is a side view showing a positional relationship between a cooking plate and a sensor. 
         FIGS.  7  and  8    illustrate a sample experiment to assess the degree of a heat generating source contributing to the rise of temperature of a processor in a device. 
         FIG.  9    is an example experiment conducted to both consider the rise of temperature of the processor due to the heat flow from the heated sources as well as the various objects within the field of view that additionally affect the temperature of an object under detection. 
         FIG.  10    illustrates sample filters used in presence detection according to some embodiments of the present disclosure. 
         FIG.  11    illustrates a presence filter based on the sample filters shown in  FIG.  10   . 
         FIG.  12    illustrates a sample flow of the process of presence detection according to some embodiments of the present disclosure. 
         FIG.  13    is a flow chart according to a temperature compensation method according to some embodiments of the present disclosure. 
         FIG.  14    illustrates a sample flow of the process of a device performing both temperature measurement and presence detection according to some embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     Technical advantages and features of the present disclosure, and implementation methods thereof will be clarified through following example embodiments described with reference to the accompanying drawings. The present disclosure may, however, be embodied in different forms and should not be construed as limited to the example embodiments set forth herein. Rather, these example embodiments are provided so that this disclosure may be sufficiently thorough and complete to assist those skilled in the art to fully understand the scope of the present disclosure. 
     A shape, a size, a ratio, an angle, and a number disclosed in the drawings for describing embodiments of the present disclosure are merely an example. Thus, the present disclosure is not limited to the illustrated details. Like reference numerals refer to like elements throughout. In the following description, when the detailed description of the relevant known function or configuration is determined to unnecessarily obscure an important point of the present disclosure, the detailed description of such known function or configuration may be omitted. 
     In describing a position relationship, when a position relation between two parts is described as, for example, “on,” “over,” “under,” “adjacent,” or “next,” one or more other parts may be disposed between the two parts unless a more limiting term, such as “direct(ly),” is used. 
     It will be understood that, although the terms “first,” “second,” etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of the present disclosure. 
     Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments as mentioned above. 
     As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. It should also be noted that the term “or” is generally employed in its broadest sense, that is, as meaning “and/or” unless the content clearly dictates otherwise. 
       FIG.  1    is a perspective view of a system according to some embodiments of the present disclosure. 
     As shown, a system  100  may be implemented as a cooking system. However, it will be apparent to a person of ordinary skill in the art that the applications of the various concepts disclosed in this disclosure is not limited to a cooking system. However, a cooking system is used as one example of an application. The cooking system  100  includes a cooker hood  110 , which is a type of housing that is capable of housing multiple components within the cooker hood  110 . One component included in the cooker hood  110  is a device or a sensor device  130 . 
     In some embodiments, the cooking system  100  further includes a cooker  120  having thereon one or more cooking plates  140 . The cooker  120  may have control terminals  150  configured to switch the cooking plates  140  ON and OFF and control the temperature of the cooking plates  140 . 
     In the illustration, the cooking plates  140  include 4 cooking plates, e.g.,  140 A,  140 B,  140 C, and  140 D. When the cooking plates are collectively referred to, reference number  140  will be used and when the individual cooking plate is referred to, individual reference number  140 A,  140 B,  140 C, and  140 D will be used. While the cooking plates  140 A- 140 D are described as an induction cooktop or an electric cooktop, the present disclosure is not limited to these. The cooking plates as used herein broadly encompasses any type of heating source capable of heating any cooking ware (e.g., pans, pots, and other cooking utensils). Accordingly, the cooking plates 140 may also include gas ranges as well. 
     The device  130  which includes one or more sensors  200  is positioned on top of the cooker  120  and the cooking plates  140 . In the illustration, there are 4 devices shown which includes device  130 A,  130 B,  130 C, and  130 D. When the devices  130  are collectively referred to, reference number  130  will be used and when the individual device is referred to, individual reference number  130 A,  130 B,  130 C, and  130 D will be used. Each device is substantially similar to each other although the embodiments are not limited to this. For example, in some embodiments, a field of view of an active area  205  of a sensor  200  (see  FIGS.  5 A and  5 B ) may differ for each device. 
     As shown, the devices  130  are above respective cooking plates  140  so that the respective cooking plates  140  are within a field of view of each device  130 . For example, a first device  130 A is above a first cooking plate  140 A and the dotted line, which indicates the field of view further shows that the first cooking plate  140 A is within the field of view of the first device  130 A. Similarly, a second device  130 B is above a second cooking plate  140 B and the dotted line, which indicates the field of view further shows that the second cooking plate  140 B is within the field of view of the second device  130 B. A third device  130 C is above a third cooking plate  140 C and the dotted line, which indicates the field of view further shows that the third cooking plate  140 C is within the field of view of the third device  130 C. A fourth device  130 D is above a fourth cooking plate  140 D and the dotted line, which indicates the field of view further shows that the fourth cooking plate  140 D is within the field of view of the fourth device  130 D. 
     The various components of the device  130  will be further described in connection with  FIG.  3   . In one or more embodiments, the device  130  is configured to sense temperature remotely and is further configured to detect presence of humans or parts of humans (e.g., hands, fingers, heads, arms, bodies, and the like). In some embodiments, the device  130  may also include an alert device (e.g., various safety applications) to signal (e.g., a notification signal in the form of sound or display or any other that is capable of notifying a user of a potential threat or danger) that a user is close to contacting a heated instrument (e.g., pans, pots, cooking plates, or any other objects in the surroundings heated up due to the heated pans, pots, cooking plates). An alert device  280  does not necessarily have to be within the device  130 . The alarm device may be located anywhere within the cooking system  100  and merely needs to be operatively and communicatively coupled to the device  130  (such as by wire or wirelessly) to receive at least one of presence information or temperature information. 
     According to some embodiments, a sensor  200  included in the device  130  is a thermal sensor capable of sensing temperature remotely by receiving infrared data (e.g., infrared light, intensity of infrared signals, infrared wavelengths or the like). In particular, thermal sensors are sensors that detect temperature changes at distant targets through the changes in radiation they emit. Since most objects can be treated as physical “black bodies,” the amount and the spectrum of radiation they emit depend upon their temperature. The amount of radiation increases with temperature, and the peak wavelength of that emission decreases with temperature, such that objects at room temperature of 300 °K have a peak wavelength at the far infrared range of about 10 um, while the Sun, with a surface temperature of 6000 °K., has a peak wavelength at the visible green (e.g., 0.5 um). Therefore, sensors that are sensitive to radiation wavelengths corresponding to significant emission from the target objects can be used to detect changes in their temperature. 
     The temperature change in uncooled thermal sensors can be converted to an electrical signal using various methods. One of the method is thermocouples which can be used to measure the temperature difference between the sensor and the ambient temperature, with low sensitivity to the ambient temperature and there is no need for an applied voltage or current. Another approach utilizes resistive bolometers that measure the absolute temperature of a temperature-sensitive resistor. Further example methods include pyroelectric sensors that change the charge in a capacitor in response to temperature changes. Various methods of the temperature detection known and used in the art may be utilized herein. 
     One non-limiting example of a thermal sensor as used in the embodiments described herein includes a thermally isolated CMOS-SOI-MEMS transistor serving as IR detector (also referred to as “TMOS” sensor or “TMOS” IR sensor), passive infrared sensor, etc. 
     The TMOS sensor is a micromachined CMOS-SOI transistor, which acts as a sensing element. In particular, the TMOS is a microelectromechanical system (MEMS) device based on a suspended, thermally isolated, micro-machined floating transistor which absorbs infrared radiation. The resulting temperature change is transduced into an electric signal. Namely, the thermally isolated floating MOS (metal-oxide-silicon) transistor senses temperature changes induced by either a physical or a chemical phenomenon. The change in temperature modifies the threshold voltage and accordingly the I-V (current-voltage) characteristics of the micro-machined transistor. 
     Further, the TMOS operates at the subthreshold region, therefore requiring low power consumption. Moreover, an inherent gain of the transistor results in the highest temperature sensitivity compared to commercial thermal sensors in the art. This provides various technical benefits as well as its possibility of wide applications. 
     Regardless of the application, like any MEMS device, it is beneficial for the TMOS to be packaged to protect the delicate structure from foreign, external materials such as dust and particles as well as to achieve the optimal performance. Wafer-level processing as well as wafer-level packaging with a controlled vacuum is beneficial to ensure high performance and low cost in manufacturing the TMOS. 
       FIG.  2    is a side view of a system according to some embodiments of the present disclosure. 
     A cooking system includes a heat generating source or a heat generating structure (e.g., cooker plate, heated cooking appliances such as pans and pots, or any other structures heated and therefore emitting infrared data) and a support structure  110 . The support structure  110  may also be referred to as a housing or a cooker hood as shown in  FIG.  2   . 
     As shown, various cooking ware may be adjacent to the cooker  120 . For example, a countertop is adjacent to the cooker  120  and on a surface  125  of the countertop, a pot  160  is resting. The pot  160  may be already heated up using the first cooking plate  140 A or the pot  160  may be ready to be mounted on the first cooking plate  140 A for cooking, thus not being heated at all. On the other side, a pan  170  is on the surface  125  of the countertop adjacent to the second cooking plate  140 B. Other various objects including cooking utensils (not shown) may be heated up if they are disposed near the cooking plates  140 . 
     For example purposes, assume that the pot  160  and the pan  170  have been previously heated through the first cooking plate  140 A and the second cooking plate  140 B, respectively, and they have been placed on the surface  125  of the countertop adjacent to the cooker  120 . A heat flow (or heat radiation or heat emission)  162  of the pot  160 , a heat flow  142  of the first cooking plate  140 A, a heat flow  144  of the second cooking plate  140 B, and a heat flow  172  of the pan  170  are shown. 
     In some embodiments, the cooker hood  110  includes a ventilation system that is capable of venting away cooking odors and filter out heat, smoke, grease, and moisture. A vent of the ventilation system may be positioned adjacent to a first device  130 A and a second device  130 B (and a third device  130 C and a fourth device  130 D, although not shown in the side view of  FIG.  2   ). The ventilation system incorporated in the cooker hood  110  at least partially affects the heat flow by causing the heat flow to be directed close to the first device  130 A and the second device  130 B. Such heat flow causes the temperature of the first device  130 A and the second device  130 B to rise when the devices  130  are heated up due to the heat flow from the various objects (e.g., cooking plates, pans, pots, kitchen utensils, etc.). The detailed mechanism for compensating the temperature increase of the device  130  itself will be explained later on. 
     The first device  130 A is configured to sense and collect infrared data of the various objects that come within a first field of view θ 1  of the first device  130 A using a sensor  200  (for example, a TMOS IR sensor) incorporated within the first device  130 A. The field of view may be adjusted to include the various heat generating structures (e.g., burner, cooker, cooking plates, pans, pots, kitchen utensils, or the like) as well as the material (e.g., steel, rubber, or the like) adjacent to the heat generating structures. 
     In  FIG.  2   , the first cooking plate  140 A and the pot  160  is within the first field of view θ 1  of the first device  130 A. Similarly, the second device  130 B is configured to sense infrared data of the various objects that come within a second field of view θ 2  of the second device  130 B using a sensor (for example, a TMOS IR sensor) incorporated within the second device  130 B. In  FIG.  2   , the second cooking plate  140 B and the pan  170  is within the second field of view θ 2  of the second device  130 B. In some embodiments, the second device  130 B, the third device  130 C, and the fourth device  130 D may be configured to be identical or similar to the first device  130 A. However, depending on the type of application and its use, in other embodiments, the structure and the function of the first, second, third, and fourth device may be different from each other. 
     The temperature of the pot  160 , the heat flow  162  from the pot  160 , the temperature of the first cooking plate  140 A, and the heat flow  142  from the first cooking plate  140 A are sensed by the first device  130 A as it is within the first field of view θ 1 . Similarly, the temperature of the pan  170 , the heat flow  172  from the pan  170 , the temperature of the second cooking plate  140 B, and the heat flow  144  from the second cooking plate  140 B are sensed by the second device  130 B as it is within the second field of view θ 2 . 
     In some embodiments, the first field of view θ 1  of the first device  130 A and the second field of view θ 2  of the second device  130 B may overlap and have an overlapping area  135 . If there are heated objects within the overlapping area  135 , each of the first device  130 A and the second device  130 B determines the temperature of the heated objects separately and determines the degree of temperature rise of the respective device caused by the heat flow from the heated objects. 
     In some embodiments, a field of view of the device  130  may be intentionally narrowed so that the accuracy of the temperature measurement of the objects within the field of view is further enhanced. In  FIG.  2   , the first field of view θ 1  is about 70 degrees to 90 degrees and the second field of view θ 2  may have similar range. However, in  FIG.  4   , a lens  220  is coupled to a sensor  200  of the device  130 , which narrows the field of view of the device  130 . Here, due to the lens  220 , the first field of view θ 1  may now have a view that is less than about 70 degrees and the second field of view θ 2  may have similar range as well. 
     Further, the field of view of the device  130  may be adjusted according to a distance H1 between the device  130  and the cooker  120 . Often, the cooker  120  and the cooker hood  110  are sold separately in the market. Further, based on the unique structure and design of each household’s kitchen, the distance H1 may vary. If distance H1 is too far apart, the objects caught within the field of view can be multiple objects. These cases may lead to an inaccurate determination of the temperature of the objects within the field of view. In these circumstances, the field of view of the device  130  may be adjusted by coupling a lens  220  on the sensor  200  of the device  130 . This way, even in cases where a distance H2 as shown in  FIG.  4    is greater than distance H1, the field of view can be narrowed and efficiently capture the heated objects within the narrowed field of view shown in  FIG.  4   . Accordingly, in case the cooker hood  110  and the cooker  120  is sold separately and installed separately and therefore cause distance H2 between the cooker hood  110  and the cooker  120  to vary, the lens  220  may adjust the field of view to take into account distance H2. 
       FIG.  3    is a block diagram of a device according to some embodiments of the present disclosure. 
     A device  130  includes a sensor  200  and a processor  210  operatively coupled to the sensor  200 . In some embodiments, the device  130  includes a lens  220  that is coupled to the sensor  200  to adjust the field of view of an active area  205  of the sensor  200 . Further details of the lens  220  is explained in conjunction with  FIGS.  4  and  5 B . Depending on the type of the lens  220 , the field of view of the sensor  200  may be widened or narrowed as needed. The embodiment of  FIGS.  4  and  5 B  illustrate the field of view of the sensor  200  (or the field of view of the device  130 ) being narrowed to focus on the heat generating source (e.g., cooking plate, pot, pan, or the like) within the field of view. 
     In some embodiments, the device  130  includes an alert device  280  configured to signal one or more users of danger caused by heated objects through a notification signal based on various thresholds (e.g., multiple levels of temperature thresholds and multiple levels of presence thresholds). For example, the alert device  280  may flash or flicker a red light to indicate that the cooking plate  140  is above a certain threshold temperature that can cause harm to the user without any sound. In some instances, the alert device  280  can sound the alarm when the device  130  determines that a user or a part of the user is getting close to a heated object or objects that is above a certain threshold temperature that can cause harm to the user. Other methods may be used besides sound or display to signal the user. The methods can be used alone or in combination. For instance, the alert device  280  may sound the alarm as well as flicker light to indicate that an object is hot and dangerous. 
     In some embodiments, the alert device  280  is configured to sound an alarm based on one or more temperature levels (or temperature thresholds). For example, a first threshold temperature indicative of a first risk (e.g., mild danger due to heat) and a second threshold temperature indicative of a second risk (e.g., serious danger due to heat) that has a higher temperature than the first threshold temperature may be set through the processor  210  so that when the cooking plate’s temperature reaches a temperature level between the first and second threshold temperature, a first alarm goes off. If the cooking plate’s temperature reaches a temperature level above the second threshold temperature, a second alarm that is different from the first alarm goes off. If the cooking plate’s temperature fails to reach a temperature level above the first threshold temperature, no alarm will go off. 
     Similarly, in some embodiments, the alert device  280  is configured to sound an alarm based on presence detection detected through the sensor  200 . 
     The processor  210  includes various circuitry (e.g.,  230 ,  240 ,  250 , and  260 ) to perform the functions of remote temperature measurement and presence detection. These various circuitry may be incorporated within the processor  210  as shown in  FIG.  3    or may be located outside of the processor  210  as a separate component or device and operatively coupled to the processor  210  to perform the functions described herein. Further, the functions of remote temperature measurement and presence detection may also be implemented through software. 
     The term “processor” may include any electrical circuitry, features, components, an assembly of electronic components or the like. That is, this term broadly encompasses any processor-based or microprocessor-based system including systems using microcontrollers, integrated circuit, chip, microchip, reduced instruction set computers (RISC), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), graphical processing units (GPUs), logic circuits, and any other circuit or processor capable of executing the various operations and functions described herein. The above examples are examples only, and are thus not intended to limit in any way the definition or meaning of the term “processor.” 
     In some embodiments, the various processors, circuits, sub-circuits described herein may be included in or otherwise implemented by processing circuitry such as a microprocessor, microcontroller, or the like. 
     For instance, the processor  210  includes a temperature determination circuit  230 . The temperature determination circuit  230  is configured to receive sensor data (e.g., infrared data received from the sensor  200 ) and process the sensor data to output temperature measurement of one or more objects that are captured within the field of view of the sensor  200 . The temperature determination circuit  230  is also configured to detect the temperature of at least one of the circuits within the processor  210 . For example, the temperature determination circuit  230  can measure the temperature of an ASIC implemented within the processor  210 . ASIC is one example of implementing the various circuits and functions within the processor  210 . As mentioned, a person of ordinary skill in the art will readily appreciate that the functions can be implemented using other processor-based devices. In order to measure the temperature of, for example, an ASIC, the temperature determination circuit  230  may include any suitable temperature measurement module or sensor. 
     The sensor data obtained from the sensor  200  includes raw infrared data. The raw infrared data include infrared light, intensity of infrared signals, or intensities of infrared wavelengths. In one embodiment, the raw infrared data includes numerical values indicative of infrared intensity. The term “raw” is used in the sense that these numerical values are not temperatures that can be described in Celsius or Fahrenheit. The temperature determination circuit  230  receives the infrared signals in the infrared light and translates the raw infrared data to a temperature represented in Celsius or Fahrenheit. In one embodiment, Analog-to-Digital Converters (ADCs) may be used to translate the intensities of infrared signals to a temperature value. 
     Below is an example formula in the art for determining a temperature of an object (T obj ) based on raw infrared data obtained from an object (T objraw ).   
     A person of ordinary skill in the art will readily appreciate and understand the above formula and its variables including coefficients. For example, ε indicates emissivity of an object, Offset indicates the amount of offset, T asic  indicates the temperature of the ASIC included in the processor  210 , and k, Ga, Fb are coefficients which are known or can be obtained empirically, and if i==0 then Tobj(°C) i-1 =25 (°C). 
     The processor  210  also includes a first compensation circuit  240 . The first compensation circuit  240  is configured to compensate for the discrepancies of a temperature of an object within the field of view of the sensor  200  caused by the increase in the temperature of the ASIC in the processor  210 . 
       FIGS.  7  and  8    illustrate a sample experiment conducted by the inventors of the present disclosure to assess the degree of a heat emission contributing to the rise of temperature of a processor (for instance, an ASIC) in a device  130 . 
     In  FIG.  7   , a temperature of a cooking plate (for example,  140 A) is set at 25° C., 50° C., 100° C., 150° C., 200° C., and 300° C. at different times. The temperature of the cooking plate is monitored from 0 seconds to about 3000 seconds. 
       FIG.  8    shows the change of temperature of the processor  210  or the ASIC included in the device  130  in the same period as  FIG.  7    (e.g., from 0 seconds to about 3000 seconds). This temperature change over time is caused by the heat flow (e.g.,  162 ,  142 ,  144 ,  172 ) which causes to raise the temperature of the processor  210  or the ASIC included in the device  130 . Due to the location of the device which is likely going to be under a cooker hood  110 , the heat flow from heat generating sources or structures (e.g., cooking plate, heated pot, heated pan, or the like) below the device  100  will cause the temperature rise of the device itself (e.g., sensor, processor, or the like). The temperature of the device itself (in particular, the temperature of the processor) is important in the relation of infrared exchange between the heat generating source and the sensor  200  for collecting infrared themselves. 
     In this regard, determining the temperature of the device (or the processor) is beneficial in accurately obtaining the temperature of the object within the field of view of the sensor. For instance, the change in the collected infrared could be caused by the temperature change of the processor inside the device. That is, the objects within the field of view might not have changed in temperature at all and it is the processor inside the device that is changing in temperature. Accordingly, it is beneficial for the temperature of the processor (or ASIC) to be compensated for accurate temperature measurement as the processor could be also changing in temperature as shown in  FIG.  8   . 
     As mentioned, the temperature rise in the processor  210  itself causes the inaccurate determination of the temperature of the actual object under detection. Accordingly, the first compensation circuit  240  compensates the rise of temperature of the processor caused by the heat flow from various heated sources within the field of view. Below is Formula 2 which is a modification made on top of Formula 1 to compensate for the rise of temperature in the components of the processor  210  (e.g., ASIC).   
     Here, the first compensation circuit  240  internally compensates the temperature of the ASIC (e.g., T asic ). Here, m and c are coefficients that are known or can be obtained empirically. For example, the coefficients are identifiable based on the characteristics of the materials (e.g., the type of materials, emissivity of the materials, and other properties of the materials) around the cooking plate and within the field of view. 
     The temperature of the ASIC is linearly compensated from T objraw  so that the outputted temperature of the object T obj  is accurately represented. As described in Formula 2, one method of applying linear compensation is to subtract (m*T asic +c) value from T objraw  in the numerator. In one embodiment, T objraw  and T asic  is an output of the ASIC. 
     The processor  210  further includes a second compensation circuit  250 . The second compensation circuit  250  compensates by taking into account the emissivity of the various objects in the surroundings (or various objects within the field of view). Below is Formula 3 which is a modification made on top of Formula 2 to compensate for the emissivity of various objects within the field of view of the sensor  200 .   
     Here, the second compensation circuit  250  internally compensates the value of emissivity ε * k based on surrounding objects by applying an additional correlation coefficient k corr . 
     Every object emits thermal radiation depending on its temperature. Emissivity is the measure of an object’s ability to emit infrared energy. Emitted energy indicates the temperature of the object. To be specific, the emissivity of the surface of a material is its effectiveness in emitting energy as thermal radiation. Thermal radiation is electromagnetic radiation that may include both visible radiation (light) and infrared radiation. Quantitatively, emissivity is the ratio of the thermal radiation from a surface to the radiation from an ideal black surface at the same temperature as given by the Stefan-Boltzmann law. The ratio varies from 0 to 1. For example, metallic surface like aluminum, copper, silver has emissivity close to 0. On the other hand, glass, water as well as human body have emissivity close to 1. The surface of a perfect black body (with an emissivity of 1) emits thermal radiation at the rate of approximately 448 watts per square meter at room temperature (25° C.). All real objects have emissivities less than 1.0, and emit radiation at correspondingly lower rates. 
     The radiation power of a black body is known and is given by Stefan-Boltzmann law. The Stefan-Boltzmann law describes the power radiated from a black body in terms of its temperature. Specifically, the Stefan-Boltzmann law states that the total energy radiated per unit surface area of a black body across all wavelengths per unit time j* (also known as the black-body radiant emittance) is directly proportional to the fourth power of the black body’s thermodynamic temperature T: j* = σT 4 . The constant of proportionality σ, called the Stefan-Boltzmann constant, is derived from other known physical constants. 
     That is, based on the type of material, the emissivity of the material, and other known properties of the material, the temperature of these materials can be obtained through the processor based on the collected infrared data. As will be explained in connection with  FIG.  9    later on, the properties of the material has to be additionally accounted for to produce an accurate temperature measurement. At point B of  FIG.  9   , it is shown that the temperature of the object T obj  within the field of view of the sensor  200  drops from about 250 degrees to about 30 degrees based on placing an unheated pot  160  on top of a heated cooking plate  140 . Accordingly, such consideration of the type of material, the emissivity of the material has to be made in order to accurately measure the temperature of the object T obj  within the field of view. 
     For example, k corr  is applied to ε and k. That is the ε * k value is further adjusted by k corr  to output ε * k * k corr  in the denominator. The objects in the surroundings are linearly compensated by ε * k * k corr  so that the outputted temperature of the object T obj  is accurately represented. As described in Formula 3, one method of applying compensation is to divide T objraw  - (m*T asic +c) value from ε * k * k corr  along with other factors. 
     Any object or black body that comes within the field of view may emit infrared data. That is, the object does not necessarily have to be a cooking plate in order to emit heat. In the example shown in  FIG.  9   , the unheated pot partially blocked the emission of the cooking plate. Accordingly, the emissivity ε of the various objects within the field of view are adjusted additionally by the aforementioned correlation coefficient k corr  (the surrounding materials’ emissivity is compensated by kcorr). 
     In some cases, k corr  is known by a manufacturer, as the manufacturer making the system  100  will know the range of the field of view of the device  130  included in the cooker hood and will also know what materials or objects comes within the field of view. That is, manufacturers know the materials used in their cooking appliances (e.g., cooking system). Accordingly, the type of material and the emissivity of the materials of the various parts of the cooking appliances can be easily obtained and considered. Here, the type of material and the emissivity of the material including pots and pans are also considered. 
     Emissivity includes hemispherical emissivity, spectral hemispherical emissivity, directional emissivity, spectral directional emissivity and the method of determining and calculating the emissivity of materials are known in the art. Further, emissivities of common surfaces arealso know in the art. For instance, an anodized aluminum has an emissivity of about 0.9, a polished copper has an emissivity of about 0.04, a human’s skin has an emissivity from 0.97 to 0.999, and water (pure) has an emissivity of about 0.96. As such, k corr  can be obtained to apply known compensations for those surrounding materials within the field of view. 
     By compensating for the rise of temperature of the processor itself and adjusting the emissivity of the surrounding materials within the field of view according to Formula 3, the sensor  200  is capable of detecting the temperature of an object from the range of about 25 degrees to about 800 degrees. Further, the accuracy is within about ± 5° C. of the actual temperature of the object throughout the range. The compensation of the temperature of the processor (e.g., ASIC) and the compensation of the surrounding materials provides a technical benefit of improving the accuracty of temperature measurement using infrared sensors. 
       FIG.  9    is an example experiment conducted to both consider the rise of temperature of the processor (e.g., ASIC) due to the heat flow from the heated sources as well as the various objects within the field of view that additionally affect the temperature of an object under detection. 
     In  FIG.  9   , the bolded lines are shown to indicate the temperature of the object T obj  under detection. The dotted lines are shown to indicate the temperature of the processor or the ASIC itself T asic . The object may be a cooking plate  140  and any other cooking tools, kitchen utensils that come within the field of view of the sensor  200 . In  FIG.  9   , a pot is used as an example of a cooking tool that is in the surrounding and within the field of view. However, this is a mere example and kitchen utensils, such as a stainless steel whisk, turner, spoon, tong, or the like can also be used as these objects also rise in temperature when heated up. As shown, various actions (e.g., actions A, B, C, D, E, F) are taking place within the timeframe of the experiment. Initially, the cooking plate is turned off and the cooking plate maintains a steady 25° C. Once the cooking plate is switched ON (action A), the temperature of the object, T obj , which in this case is the cooking plate rises up. It is appreciated that the temperature of the ASIC, T asic , within the device  130  is also increased. The ASIC had an initial temperature of about 25° C. but as the temperature of the cooking plate rises, the temperature of the ASIC also steadily rises from about 25° C. to about 70° C. 
     When a pot with a cover is placed on top of the cooking plate (action B), the temperature of an area where the cooking plate and the pot is disposed sharply drops. T obj  shows that the temperature drops to about 30° C. That is, the temperature is adjusted according to the objects within the field of view. The pot has an emissivity ε pot  but because the pot is unheated and cooled before being disposed on the heated cooking plate, in one embodiment, correlation coefficient k corr , may be introduced to adjust. 
     As the cooking plate is continuously applied heat, the temperature of the pot rises and the water starts to boil about at 100° C. (action C). When the water in the pot starts to boil, the cover of the pot is removed. During the timeframe between action B and action C, it shows that the temperature of the ASIC gradually decreases from 70° C. to about 48° C. This is partially due to the fact that the direct heat flow from the pot does not affect the ASIC in the device  130 . 
     When the pot is removed from the cooking plate (and outside of the field of view so that the temperature of the pot no longer affects the temperature of the object and the ASIC) and cooking plate is turned OFF (action D), an instant increase in temperature T obj  is detected. That is, the temperature T obj  rises up until about 200° C. and because the switch is no longer ON, the temperature steadily decreases. The temperature of the ASIC, T asic , also steadily decreases. 
     The cooking plate is switched to ON (action E) for a few seconds and the cooking plate is switched OFF (action F). It is shown that the temperature of the ASIC, T asic , is affected by this short temperature change as T asic  rises from 28° C. to 33° C. before it starts to dropping again. The graph shows the close correlation between the temperature of the ASIC, T asic  and the temperature T obj  under sensing. 
     The example experiment shown in  FIG.  9    illustrates the benefit of considering the various objects within the surroundings as well as the temperature of the ASIC in accurately determining the temperature of an object within the field of view. Application of these findings are found in Formula 3 as described above. 
     The processor  210  also includes a presence determination circuit  260  that is configured to detect presence or absence of a user based on the collected infrared data form the sensor  200 . The presence determination circuit  260  includes presence detection algorithms that processes the same infrared data for determining temperature. The presence detection algorithm implemented within the presence determination circuit  260  will be explained in conjunction with  FIGS.  10 ,  11 ,  12 , and  14   . 
     In some embodiments, the processor  210  may include a communication circuit  270  capable of performing communication with another device or with an external server. For example, the first device  130 A can communicate information (e.g., collected infrared data of the materials within its field of view) with the second device  130 B so that any heated objects within the overlapping area  135  are not taken into account twice by the first and second device  130 A,  130 B as shown in  FIG.  2   . 
     The communication circuit  270  can be implemented by utilizing various communication schemes know in the art including but not limited to Wi-Fi, Bluetooth, Zigbee, 5G, LTE, or the like. Referring to  FIG.  4   ,  FIG.  4    is a side view of a device having a lens according to some embodiments of the present disclosure.  FIG.  4    also includes an enlarged view of the lens coupled to the device. 
     In some embodiments, a lens  220  is coupled to a device  130  to narrow the field of view of a device  400  or a system  400 . The system  400  in  FIG.  4    is substantially similar to the system  100  in  FIG.  2    except that the device  130  in system  400  includes a lens  220  coupled to the device. 
     In  FIG.  4   , a lens  220 A coupled to the first device  130 A has a first field of view θ 1 . This first field of view θ 1  is narrower than the field of view of the first device  130 A shown in connection with  FIG.  2   . Similarly, a lens  220 B coupled to the second device  130 B has a second field of view θ 2 . In some embodiments, the lens  220 B is identical to the lens  220 A and the second field of view θ 2  is substantially identical to the first field of view θ 1 . However, in other embodiments, the lens  220 B may be different from the lens  220 A and accordingly, the second field of view θ 2  may be different from the first field of view θ 1 . 
     One benefit of the lens or any other structure suitable for performing the function of the lens is that the field of view is narrowed and the objects within the field of view is reduced. This increases the accuracy of the temperature of one or more objects detected within the field of view of the sensor. Another benefit is that the application of a lens enables extending the sensor’s reach. 
     In  FIG.  4   , the pot  160  with the cover is on the first cooking plate  140 A. Depending on whether the pot  160  was initially heated or cooled, the heat flow  402  radiated from the pot  160  and the first cooking plate  140 A. The example of temperature of the object (e.g., cooking plate, pot) within the first field of view temporarily dropping was explained in connection with  FIG.  9    when the pot is unheated prior to being placed on top of the heated cooking plate. 
     The heat flow  404  radiated from the pan  170  and the second cooking plate  140 B is also detected in a similar manner at the second device  130 B. As shown in the enlarged view of the sensor device  130 B having the lens  220 B, the lens  220 B is arranged on top of the sensor  200 . The cross-sectional view of the device  130  with a lens  220  and without a lens will be described in conjunction with  FIGS.  5 A and  5 B  below. 
       FIG.  5 A  is a cross-sectional view of a device according to some embodiments. 
     The cross-sectional view of the device  130  shows a sensor  200 . The sensor is included in a package  310  that has a window  320  for receiving sensed data. A cover  330  is over the package  310  of the sensor  200 . The cover  330  includes an exposure hole  340  that is wider than a width W of the window  320  of the package  310 . The rest of the package  310  is surrounded by a housing  500 . In some embodiments, the housing  500  and the cover  330  may be integrally formed and does not have to be a separate component. The sensor  200  is housed in a package (or housing)  500  to protect the sensor  200  from unwanted radiation. The window on top is closed with, for example, a silicon window  320  which is transparent for thermal radiation. 
     The field of view  350  of the sensor  200  is illustrated as a circular sector but a person of ordinary skill in the art would readily appreciate that the field of view  350  has a cone shape. 
     The cover window  320  can provide physical protection of a sensor module  200 , including dust prevention. The exposure hole  340  is appropriately arranged considering various geometrical constraints in order to avoid the field of view limitation. 
     The IR sensor which is one example of the sensor  200  is able to detect radiation emitted by a body at a certain temperature according to black-body emission Plank’s law. The sensor  200  collects IR radiation without any obstacles to the radiation optical path. This feature enables the sensor  200  to operate as a human presence and motion sensor in different application contexts such as alarm systems, anti-intruder systems, smart lighting, and room occupancy. In some embodiments, the sensor  200  has high sensitivity for working as a presence and motion sensor. The sensor  200  is also capable of detecting temperature remotely as previously explained. The sensor  200  may be also be implemented with an integrated silicon IR filter. 
     An example IR sensor according to one embodiment of the present disclosure measures in the wavelength range from about 5 to 15 µm. Human body peak radiation is about 9.8 µm, therefore it is about in the center of IR bandwidth, which makes it capable of detecting presence through infrared signals. The method of how the sensor according to the present disclosure detects both temperature measurement and object presence will be further explained below. 
       FIG.  5 B  is a cross-sectional view of a device having a lens mounted on a sensor according to some embodiments. 
     The difference between  FIG.  5 B  and  FIG.  5 A  is that a lens  220  is disposed on a cover  330 . That is, in place of the exposure hole  340  in  FIG.  5 A , the lens  220  is disposed. The lens  220  is further centered on the cover window  320  so that any data collected through the lens  220  is gathered at an active area  205  of a sensor  200 . That is, the lens  220  collects the data or radiation (e.g., IR radiation) and provides to the active area  205  of a sensor  200 . A lens  220  can be used as a collector to focus the intercepted radiation on the sensor active area  205 . One example of a lens  200  includes a plano-convex lens. 
       FIG.  6 A  is a top view showing a positional relationship between a cooking plate and a sensor. In some embodiments, a center  200 CP of a sensor  200  is aligned with a center  140 CP of a cooking plate  140 . That is, when seen from a top view, the center  200 CP of the sensor  200  is substantially aligned or exactly aligned with the center  140 CP of a cooking plate  140 . More specifically, when seen from a top view, the center  200 CP of an active area  205  of the sensor  200  is substantially aligned or exactly aligned with the center  140 CP of a cooking plate  140 . 
       FIG.  6 B  is a side view showing a positional relationship between a cooking plate and a sensor. As shown, an imaginary perpendicular line  600  is shown to indicate that a center  200 CP of an active area  205  of a sensor  200  is aligned with a center  140 CP of a cooking plate  140 . In some embodiments, having the sensor  200  aligned with the cooking plate  140  may improve the accuracy of the temperature detection. 
       FIG.  10    illustrates sample filters used in presence detection according to some embodiments of the present disclosure.  FIG.  11    illustrates a presence filter based on the sample filters shown in  FIG.  10   .  FIG.  12    illustrates a sample flow of the process of presence detection according to some embodiments of the present disclosure. 
     One of the technical benefits of the present disclosure is that based on the same raw infrared data used for remote temperature measurement can be used for detecting presence.  FIGS.  1 - 9    have been explained from a perspective of a remote temperature measurement. That is, the raw infrared data has been processed so that the processor converts the raw infrared data and outputs a temperature value of one or more objects. However, as mentioned above, the same data collected from the TMOS IR sensor or simply sensor  200  can be used for presence detection based on a presence algorithm (see  FIG.  12   ) according to one or more embodiments of the present disclosure. The presence algorithm is implemented in the presence determination circuit  260 . That is, the raw infrared data is processed so that a presence within the field of view of the sensor is detected based on the same raw infrared data used for determining the temperature of one or more objects. This is further illustrated in connection with  FIG.  14   . 
     The functions and the features described below are implemented in the presence determination circuit  260  as presence algorithms. 
     Referring to  FIG.  12   , at  1210 , initially the settings of the device  100  is established. The settings of the device  100  includes, but are not limited to, a sampling rate (ODR; output data rate), gain, etc. For example, ODR which is the rate at which a sensor obtains new measurements, or samples can be measured in number of samples per second (Hz). In one embodiment, the ODR may be set to 8 Hz and the gain may be set to 16. However, this is merely an example number and the sampling rate, gain, and other values can be set different to achieve different performance of the device  100 . For example, the ODR and the gain may be adjusted to be more sensitive or less sensitive as needed. 
     At  1220 , raw infrared data (e.g., intensity of infrared signals) are obtained by the sensor  200  for using the data as presence detection. As noted, the same raw infrared data is used to determine the temperature of an object. Accordingly, the settings for the device  100  is the same with ODR at 8 Hz and gain at 16. The device settings do not have to altered or the type of raw infrared data does not have to be collected again to perform both functions of remote temperature measurement and presence detection. 
     At  1230 , the temperature of the object (T obj ) is obtained through the sensor  200  and at  1240 , the ambient temperature (T amb ) is obtained through the sensor  200 . For example, here, a chip included in the device  100  amplifies the IR signal, and converts it to digital and further provides the two main parameters, T amb  and T obj  described above. Namely, T amb  is the temperature of the sensor that is ambient temperature in steady state condition, T obj  is the signal proportional to the IR radiation that reaches the field of view of the sensor  200 . The ambient temperature T amb  and the object temperature T obj  is separately obtained in order to detect the presence of both a still subject and a moving subject. Ambient temperature is given less weight or low sensitivity as compared to the temperature of an object. Method of measuring ambient temperature temperature is well-established in the related art. Obtaining both the ambient temperature T amb  and the object temperature T obj  from the sensor  200  enables the presence determination circuit  260  to determine whether there is a presence of a subject (e.g., user, part of a user such as arm, hand) as well as if they are still or moving. These temperature data for T obj  and T amb  are applied with filters at  1250 . In one embodiment, certain filters are applied to the collected raw infrared data by the sensor  200  at  1260  and at  1270 . One example filter is a first low pass filter F1 and a second low pass filter F2 which is also shown in  FIG.  10   . When a subject (e.g., a user, or a part of the user) is moving within the field of view of the sensor  200 , the first low pass filter F1 and the second low pass filter F2 is applied to the infrared data collected based on the subject’s movement within the field of view. Then the difference of the output from the two filters is obtained at  1280 . This is shown as a presence filter PM in  FIG.  11    which is, in one embodiment, a subtraction between the first low pass filter F1 and the second low pass filter F2. That is, presence filter for processing presence signals are generaed based on a difference between an outcome of applying the first low pass filter F1 to the infrared data and an outcome of applying the second low pass filter F2 to the same infrared data. 
     The presence determination circuit  260  further computes the absolute value (ABS*) of the presence filter PM producing presence signals at  1290 . Then at  1310 , the presence determination circuit  260  compares the absolute value of the presence filter PM with the various thresholds (e.g., presence threshold P THS  and hysteresis threshold P HYS  at  1300 ). In one embodiment, the presence signals are compared with a difference of a presence threshold and a hysteresis threshold to determine a presence of a subject with the field of view. 
     Presence flag PF or P Flag is a logic value of 0 and 1 where 0 indicates no presence and 1 indicates presence. At  1320 , the presence signals from the presence filter PM are compared with the presence threshold P THS  and hysteresis threshold P HYS  and if there is presence, a logic value of 1 is output. If there is no presence, a logic value of 0 is output. 
     For example, the presence determination circuit may determine that a subject is present when the presence signals are greater than the difference of the presence threshold and the hysteresis threshold. On the other hand, the presence determination circuit may determine that the subject is absent when the presence signals are smaller than the difference of the presence threshold and the hysteresis threshold. Based on the output, an alarm may sound if the value is 1 at  1330 . In particular, a notification signal may be transmitted from the presence determination circuit to the alert device  280  in response to the presence signals being greater than the difference of the presence threshold and the hysteresis threshold. On the other hand, if the value is 0, the alarm will be disabled. 
     The example algorithm for presence detection is further explained in connection with  FIGS.  10  and  11   . In one embodiment, two thresholds are introduced in order to accurately detect a presence of a subject. A first threshold is a presence threshold P THS . When the presence signal as shown in  FIG.  11    is above the presence threshold P THS , then the processor determines that there is a presence of a subject within the field of view. Another threshold considered is the hysteresis threshold P HYS . The hysteresis threshold P HYS  is provided to account for the oscillation in the presence signals (see 0 to A and C to 240 in  FIG.  11   ). That is, a second threshold, P THS  - P HYS , is further taken into account for avoiding oscillation of the presence signals around a threshold value. That is, for example, the processor may erroneously determine that a presence is detected whenever the presence signal slightly goes above the threshold value (e.g., presence threshold P THS ) due to the oscillation of the presence signals caused by noise. Accordingly, the second threshold, P THS  - P HYS , reduces the problem of oscillation in presence signals to improve the accuracy of presence detection. 
     Referring to  FIG.  11   , when the presence signal is greater than P THS  (see A of  FIG.  11   ) and the output of a presence flag PF in the previous measurement is 0 (which is indicative of no presence detected), the value of the low pass filter F2 will be frozen (see B of  FIG.  10   ) and presence flag PF will go to 1 (which is indicative of presence). While the presence flag PF is 1 (for example, between A and C in  FIG.  11   ), the input for the low pass filter F2 may remain as a constant value (“Value Freeze”) and the output of the low pass filter F2 will be constant. When the presence flag PF goes to 0 (see C at  FIG.  11   ) and the presence signal will be lower than P THS  - P HYS  at point C (see  FIG.  11   ). From this instant (at point D at  FIG.  10   ) the low pass filter F2 may be free to evolve with T obj  as input. 
     The aforementioned method is one example method of detecting presence. Other various method may be used by the IR sensor to detect presence. For example, if an object with emissivity close to 1 is covering the entire field of view of the sensor, then the T obj  will be proportional of the object temperature. As previously mentioned, human body has an emissivity close to 1, which allows the IR sensor to detect presence of a human body. If the temperature of the object is higher than ambient temperature T amb , then T obj  will be positive. If the temperature of the object is lower than ambient temperature T amb , then T obj  will be negative. Further, if the emissivity of the object in front of the sensor is zero, then T obj  is expected to be approximatively zero according to imposed calibration. 
       FIG.  13    is a flow chart according to a temperature compensation method according to some embodiments of the present disclosure. 
     At  1350 , infrared signals are collected using a sensor. The infrared signals are broadly used herein to indicate any suitable signals from infrared light that is used at the sensor  200  for measuring temperature of an object (or objects) within the field of view of the sensor  200 . One example of infrared signals may include infrared light, infrared wavelengths, intensities of infrared wavelengths, or the like. 
     At  1360 , the temperature of the object is determined using the temperature determination circuit  230  based on a raw infrared data including infrared signals and the properties of infrared signals such as intensity. 
     At  1370 , the temperature of a processor  210  or if it is implemented using an ASIC, the temperature of the ASIC, is measured using the temperature determination circuit  230 . The temperature of the ASIC is used by the first compensation circuit  240  to compensate the temperature of the object based on the rise of temperature in the ASIC. This process is explained at  1390 . 
     At  1380 , the properties of materials in the surroundings within the field of view of the sensor  200  is also determined. These properties which include the type or materials and the emissivity of the materials are taken into account and used by the second compensation circuit  250 . 
     At  1390 , the temperature of the object within the field of view of the sensor is adjusted based on the temperature of the ASIC and the properties of materials in the surroundings within the field of view of the sensor  200 . The first and second compensation circuit determines the degree of compensation and outputs the temperature of the object based on Formula 3. 
       FIG.  14    illustrates a sample flow of the process of a device performing both temperature measurement and presence detection according to some embodiments of the present disclosure. 
     The process is initiated at  1400 . At  1410 , the settings of a device  100  or specifically the settings of a device  130  is set. For example, the ODR may be set to 8 Hz and the gain may be set to 16. However, as mentioned previously, this is merely an example and various different settings may be used. As will be discussed below, the same raw infrared data (e.g., calibration data) is used for determining temperature as well as presence. 
     At  1420 , the raw infrared data which is in the form of intensity of infrared wavelengths are collected through a sensor  200 . At  1430 , the temperature of one or more objects are obtained based on Formula 3 which takes into account both the rise of temperature in the processor (e.g., ASIC) as well as the emissivity of surrounding materials within the field of view. 
     At  1440 , an alarm may be set to go off based on one or more temperature levels. The alert device  280  may be set accordingly to sound the alarm at one or more temperature levels programmed. 
     At  1450 , delta value of a temperature (e.g., difference between a current temperature measurement and a previous temperature measurement of an object) dTemp is calculated by the processor  210  to determine whether the object is heating or cooling. When dTemp is greater than 0, this is indicative of the fact that the temperature is rising (e.g. heating). On the other hand, when dTemp is smaller than 0, this is indicative of the fact that the temperature is dropping (e.g., cooling). 
     At  1460 , when the measured temperature is above a safety temperature threshold T safety , a presence detection mechanism is enabled at  1470 . However, in some applications, the presence detection mechanism may be enabled by the user regardless of comparing the currently measured temperature with the safety temperature threshold T safety . The safety temperature threshold T safety  is indicative a temperature threshold as set by a user. For example, a mother cooking dinner may set 60 degrees as a safety temperature threshold T safety  while she is away so that her child is alerted using presence detection when the child tries to approach the heated cooker and the other heated objects on and adjacent to the cooker. 
     At  1480 , when the temperature is cooling down, and when the measured temperature is below a safety temperature threshold T safety , a presence detection mechanism is disabled at  1490 . For example, if the current temperature is below the safety temperature threshold T safety  of 60 degrees, the presence detection mechanism is disabled as there is no threat or danger associated with heated objects on and adjacent to the cooker. 
     In some embodiments, the activation of the presence detection algorithm can be set regardless of comparing the safety threshold temperature by the user, as described above. 
     After the settings of the device is completed at  1410 , the raw infrared data which is in the form of intensity of infrared signals are collected through the sensor  200  at  1500 . The infrared data collected at  1420  and the infrared data collected at  1500  is identical and collected through an identical process. That is, while the flow shown in  FIG.  14    has used separate blocks for  1420  and  1500 , these steps are identical and can be consolidated together. That is, the calibration data for Tobj in  1420  and calibration data for presence detection at  1500  are the same. Merely, different processes or algorithms are applied to analyze the raw data. For the former data collected at  1420 , temperature determination process using Formula 3 is applied, and for the latter data collected at  1500 , presence determination process using presence algorithm described in  FIGS.  10 - 13    is applied (see  1510 ). 
     At  1520 , a presence flag PF or P Flag is set up and the presence signals are compared with the presence filter PM (see  FIG.  11   ). If the P Flag output is logic value 0 which is indicative of no presence, the step returns to  1500  and continues to  1510  to further analyze based on updated infrared data (or load new calibration data). If the P Flag output is logic value 1 which is indicative of presence, an alarm may sound from the alert device  280 . 
     The various embodiments described above can be combined to provide further embodiments. All of the U.S. Pat., U.S. Pat. application publications, U.S. Pat. applications, foreign patents, foreign patent applications and non-patent publications referred to in this specification and/or listed in the Application Data Sheet are incorporated herein by reference, in their entirety. Aspects of the embodiments can be modified, if necessary to employ concepts of the various patents, applications and publications to provide yet further embodiments. 
     These and other changes can be made to the embodiments in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure.