Abstract: The present invention relates to a method of determining stock in an inventory. The method comprises obtaining one or more images comprising one or more objects. Further, estimating a three dimensional (3D) location of a Stock Keeping Unit (SKU) marker associated with each of one or more visible objects. Furthermore, determining a stacking pattern of the one or more objects for each level on the pallet using one of the 3D location of SKU marker and a learning model. Thereafter, detecting at least one of presence or absence of one or more undetected objects at each level based on the stacking pattern and the 3D location of the SKU marker. Finally, determining the stock in the inventory based on the presence or the absence of the one or more undetected objects and the one or more visible objects.

Abstract: This disclosure relates to system and method for cleaning surfaces using drones. The method includes identifying, by a first drone, a cleaning strip in contact with a surface. The cleaning strip connects a second drone and a third drone. The second drone is communicatively coupled with the third drone. The first drone is communicatively coupled with each of the second drone and the third drone. The method further includes releasing a cleaning agent at a preconfigured pressure upon a current target region of the surface near the cleaning strip. The method further includes relocating the cleaning strip upon the current target region. The method further includes performing a set of oscillations through the cleaning strip across the current target region. Each of the set of oscillations includes coordinating a displacement of the cleaning strip by a predefined distance, alternating towards each of ends of the cleaning strip.

Abstract: System and method of detecting infestation in agricultural products is disclosed. In one embodiment, an infestation detection system captures hyperspectral imaging data and depth imaging data for a plurality of points on an agricultural product upon directing a light source at the agricultural product. The system analyses the captured imaging data to derive morphological details as well as spectral signatures for complete 360° view of the plurality of points on the agricultural product. In an embodiment, the spectral signatures may be corrected for one or more pixels associated with the plurality of points in the agricultural product by integrating the hyperspectral imaging data with the depth imaging data. The system further classifies one or more regions of the agricultural product based on matching of spectral signatures for the one or more pixels with pre-defined spectral signatures stored for a plurality of agricultural products, and accordingly detect infestation.

Abstract: This disclosure relates to system and method for cleaning surfaces using drones. The method includes identifying, by a first drone, a cleaning strip in contact with a surface. The cleaning strip connects a second drone and a third drone. The second drone is communicatively coupled with the third drone. The first drone is communicatively coupled with each of the second drone and the third drone. The method further includes releasing a cleaning agent at a preconfigured pressure upon a current target region of the surface near the cleaning strip. The method further includes relocating the cleaning strip upon the current target region. The method further includes performing a set of oscillations through the cleaning strip across the current target region. Each of the set of oscillations includes coordinating a displacement of the cleaning strip by a predefined distance, alternating towards each of ends of the cleaning strip.

Abstract: System and method of detecting infestation in agricultural products is disclosed. In one embodiment, an infestation detection system captures hyperspectral imaging data and depth imaging data for a plurality of points on an agricultural product upon directing a light source at the agricultural product. The system analyses the captured imaging data to derive morphological details as well as spectral signatures for complete 360° view of the plurality of points on the agricultural product. In an embodiment, the spectral signatures may be corrected for one or more pixels associated with the plurality of points in the agricultural product by integrating the hyperspectral imaging data with the depth imaging data. The system further classifies one or more regions of the agricultural product based on matching of spectral signatures for the one or more pixels with pre-defined spectral signatures stored for a plurality of agricultural products, and accordingly detect infestation.

Abstract: The present invention relates to a method of determining stock in an inventory. The method comprises obtaining one or more images comprising one or more objects. Further, estimating a three dimensional (3D) location of a Stock Keeping Unit (SKU) marker associated with each of one or more visible objects. Furthermore, determining a stacking pattern of the one or more objects for each level on the pallet using one of the 3D location of SKU marker and a learning model. Thereafter, detecting at least one of presence or absence of one or more undetected objects at each level based on the stacking pattern and the 3D location of the SKU marker. Finally, determining the stock in the inventory based on the presence or the absence of the one or more undetected objects and the one or more visible objects.

Abstract: The present disclosure relates to a method and system for recommending optimal ergonomic position for a user of a computing device by a recommendation system. The recommendation system receives user data from one or more data sources and extracts a profile of the user from a repository based on the user data. The recommendation system identifies one or more critical areas of the user, where each of the critical areas are associated with a plurality of pre-defined position parameters and also monitor the plurality of pre-defined position parameters of the user to determine corresponding values. The recommendation system compare the values of the plurality of pre-defined position parameters with predefined values of the pre-defined position parameters and identify deviations in one or more of the plurality of pre-defined position parameters based on the comparison and provide recommendations for correcting the deviations from the pre-defined position parameters to the user.

Abstract: A method and a device are described for non-invasive monitoring of blood glucose level of a user. The method includes determining an electrical skin impedance between a first point and a second point of a surface of skin of user using a skin impedance sensor. In an embodiment, electrical skin impedance is indicative of an opacity of surface of skin between first point and second point. The method includes determining a temperature and a hyper spectral signature of skin of user using a temperature sensor and a hyperspectral sensor. The method includes updating a light intensity of a light source based on temperature and hyperspectral signature. In an embodiment, surface of the skin is illuminated based on updated light intensity of light source. The method includes computing a blood glucose level using temperature, hyper spectral signature, and electrical skin impedance. The method includes providing computed blood glucose level to user.

Abstract: The present disclosure relates to a method and system for recommending optimal ergonomic position for a user of a computing device by a recommendation system. The recommendation system receives user data from one or more data sources and extracts a profile of the user from a repository based on the user data. The recommendation system identifies one or more critical areas of the user, where each of the critical areas are associated with a plurality of pre-defined position parameters and also monitor the plurality of pre-defined position parameters of the user to determine corresponding values. The recommendation system compare the values of the plurality of pre-defined position parameters with predefined values of the pre-defined position parameters and identify deviations in one or more of the plurality of pre-defined position parameters based on the comparison and provide recommendations for correcting the deviations from the pre-defined position parameters to the user.

Abstract: A method, shelf life analysis computing device, and non-transitory computer readable medium for determining shelf life of a consumable product is disclosed. The system may comprise one or more activity monitoring sensors to detect an activity associated with the consumable product. The system may further comprise one or more quality sensors to collect quality data of the consumable product upon detecting the activity. The shelf life of the consumable product may then be determined based on the quality data of the consumable product.

Abstract: This disclosure generally relates to spectral imaging and, more particularly, to methods and systems for speed calibration in spectral imaging systems. In one embodiment, a spectral imaging system is disclosed, comprising: an imaging sensor configured to acquire image data for an imaged object; a multi-band wavelength filter disposed to filter light detected by the imaging sensor; and a motion stage configured to cause relative motion between the imaged object and the multi-band wavelength filter at a motion rate that is based on a frame rate of the imaging sensor and a number of wavelength bands of the wavelength filter utilized to filter light detected by the imaging sensor; wherein the motion rate is set such that light detected by the imaging sensor corresponding to a portion of the imaged object is filtered by successive wavelength bands of the wavelength filter for successive frames capturing the portion of the imaged object.