DESC:Form 2
The patent Act 1970
(39 of 1970)
AND
Patent Rules 2003
Complete Specification
(Sec 10 and Rule 13)
Title: Drones with offline capabilities
Applicant(s)
AMX Innovation Private Limited

Nationality India
Address No. 132, 4th Floor, Chitrapur Bhavan, 15th Cross, 8th Main Road, Malleshwaram, Bengaluru – 560055, Karnataka, India.

The following specification, particularly describes the invention and the manner in which it is to be performed.

DESCRIPTION
FIELD OF INVENTION
[0001] The present invention relates to an Unmanned Aerial Vehicle (UAV) or drone and more particularly to a method and system to develop a drones with an on-board image processing for a drone and an offline capabilities of transmitting a processed image data to a base station.
RELATED ART
[0002] Image processing is an effective tool for analysis in agricultural fields for various applications. The automated analysis is mainly beneficial for the farmers where expert knowledge and advice is not readily available or affordable. The technological advancements used in the development of precision agriculture machinery prove to be cheaper and faster than on-ground human intervention and data collection.
[0003] The application of image processing techniques used in the field of agriculture where the images are captured through remote sensing, involving aircraft or satellites, and then processed and analyzed using processor. Along with the image processing, a communication systems is also used that help the farmers to achieve maximum yield without much loss in agricultural fields. The image processing applications in agricultural applications is growing steadily with the availability of higher-quality measurements coupled with modern algorithms and multiple sources of information.
[0004] The utilization of image processing techniques with machine learning algorithms in agricultural applications such as: determining water stress, quality of yields, and use of pesticides, to monitor the irrigation and water availability in the farms during and pre-harvesting operations, detection of weeds growing, determination of quality of yield and in automated sorting and grading of crops and farm products characterized by color, size and shape.
[0005] However, implementing these methods all together in a single device such as unmanned aerial vehicles (UAV)/ drones is difficult due to the complexity in achieving portability and compactness. Further, for the real time communication of data from drone to a base station requires online communication which is not affordable and feasible for farmers.
[0006] Hence, an effective and an efficient Unmanned Aerial Vehicle (UAV) or drone is required with an on-board image processing for a drone and an offline capabilities of transmitting a processed image data to a base station.

SUMMARY
[0007] In one embodiment, a drone with offline capabilities comprising: an inbuilt camera to capture images of a crop in the agricultural field; a memory unit to store the captured images of a crop; on-board processing unit to process the stored images based on the predefined trained model database using various types of image processing techniques to obtain a analyzed data of yield of a crop; and a transmitter to transmit the analyzed data to the single or multiple end user device through a single communication channel, wherein the drone with offline capabilities transmit a analyzed data to a single or multiple end user device in offline mode without involvement of the internet intervention.
[0008] Several aspects are described below, with reference to diagrams. It should be understood that numerous specific details, relationships, and methods are set forth to provide a full understanding of the present disclosure. One who skilled in the relevant art, however, will readily recognize that the present disclosure can be practiced without one or more of the specific details, or with other methods, etc. In other instances, well-known structures or operations are not shown in detail to avoid obscuring the features of the present disclosure.
BRIEF DESCRIPTION OF DRAWINGS
[0009] Fig. 1 is a schematic view illustrating a conventional drone online data communication system.
[0010] Fig. 2 is a schematic view illustrating a drone offline data communication system in an embodiment of the present disclosure.
[0011] Fig. 3A and Fig. 3B are schematic views illustrating a drone with on-board processing unit and offline capabilities for transmission of data in an embodiment of the present disclosure.
[0012] Fig. 4 is a flow chart illustrating the method of analyzing a yield of the crop using a drone with on-board processing unit and offline capabilities for transmission of data in an embodiment of the present disclosure.
DETAILED DESCRIPTION OF THE PREFERRED EXAMPLES
[0013] Fig. 1 is a schematic view illustrating a conventional drone online data communication system. As shown in 100, the conventional online data communication system comprising a drone 104 with a inbuilt camera 122 captures real time images of a crop and then sends it to a base station 102 with a image processing unit and other communicating devices. Then the image processing unit of the base station 102 processes the captured images of crop to determine the whether yield of crop is good or bad. The captured images from the drone 104 are transmitted to a cloud database unit 106 and then stored in a server unit 108 for further processing. The captured images are transmitted to plurality of end user devices 116,118 and 120 where the image processing takes place to determine the desired results and analysis regarding the yield of crop. This conventional data communication system also requires internet or Ethernet to transmit the information or the captured images to other external devices which is expensive and requires long time as the network gets affected due to external factors. Thus, this system requires multiple communication channel1 110, communication channel2 112 and communication channels3 114 to transmit data or the captured images from the drone 102 camera 112 to a base station 102 or a server unit 108 or an end user devices 116,118 and 120.
[0014] Fig. 2 is a schematic view illustrating a drone offline data communication system in an embodiment of the present disclosure. As shown in 200, the offline data communication system comprises of a drone 202 with offline capabilities where an inbuilt camera 204 of the drone 202 captures the images of the crop in the agricultural field and gets stored in a memory unit 210. The stored images are processed by a on-board processing unit 208 based on the predefined trained model database using various types of image processing techniques and stores the processed images in the memory unit 210 to determines the productivity of the crop is good or bad. This results in a generating a detailed report with analysis of crop yield, quality and notifies the user where individual inspection is required. And this generated detailed analysis report is transmitted using a transmitter 206 to the end user device 214 through a single communication channel 212 without usage of any network.
[0015] Fig. 3A and Fig. 3B are schematic views illustrating a drone with on-board processing unit and offline capabilities for transmission of data in an embodiment of the present disclosure. As shown in 300 and 320, is a drone 302 with on-board processing unit 308 and offline capabilities that comprises of an inbuilt camera 304, a transmitter 306, on-board processing unit 308 and a memory unit 310. The inbuilt camera 304 of the drone 302 captures the images of the crop in the agricultural field and gets stored in a memory unit 310. The stored images are processed by a on-board processing unit 308 based on the predefined trained model database using various types of image processing techniques and stores them in the memory unit 310 to determines the productivity of the crop is good or bad. This results in a generating a detailed report with analysis of crop yield, quality and notifies the user where individual inspection is required. And this generated detailed analysis report is transmitted using a transmitter 306 to the single or multiple end user device through a single communication channel without usage of any network.
[0016] Fig. 4 is a flow chart illustrating the method of analyzing a yield of the crop using a drone with on-board processing unit and offline capabilities for transmission of data in an embodiment of the present disclosure. As shown in 400, initially, in step 401, the inbuilt camera of the drone captures the raw images of the crop from a farm land. In step 402, the captured raw images of a crop are stored in an on-board memory unit of the drone. In step 403, the stored raw images of a crop are processed in the image processor unit that enhances the pixel size and image quality to make suitable for extraction of features from it. The stored raw images of the crop is processed based on a predefined trained model database comprising plurality of processed and trained images to obtain a processed data with various parameters of the crop. In step 404, the processed data with various parameters of the crop is collected from the trained model database and the image processor unit is analyzed to obtain an analyzed data regarding the yield of the crops along with the identification of weeds. In step 405, the analyzed data is then transmitted to a base station through a transmitter in offline mode.
[0017] In an embodiment, the inbuilt camera drone with offline capabilities recognizes and differentiates the good and bad yield of crops or plants or flowers or fruit or vegetables or others. It also counts the number of individual crops or plants or flowers or fruits or vegetables and removes redundancy besides providing the distance between crops/flowers etc. Further, it generates a detailed report with analysis of crop yield, quality and notifies the user where individual inspection is required using all the collected and processed data in real time which simultaneously transmits them during the drone’s manual, autonomous or semi-autonomous operations. The entire processing and transmission happens offline where there is no complete involvement of the internet intervention.
[0018] In an embodiment, the redundancy is controlled by the drone with offline capabilities wherein the inspected location is not considered again for repetitive image capturing and processing. This helps the user to determine precise yield quantity from his farm land. The entire processed information is stored in the memory as well as transmitted to an end user device through an industrial, scientific and medical (ISM) radio bands. Thus, offline and real time data processing and transmission is achieved by using the drone with offline capabilities.
[0019] While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of the present disclosure should not be limited by any of the above- discussed embodiments, but should be defined only in accordance with the following claims and their equivalents.

,CLAIMS:CLAIMS
I/We Claim,
1. A drone with offline capabilities 300 comprising:
an inbuilt camera 304 to capture images of a crop in the agricultural field;
a memory unit 310 to store the captured images of a crop;
on-board processing unit 308 to process the stored images based on the predefined trained model database using various types of image processing techniques to obtain a analyzed data of yield of a crop; and
a transmitter 306 to transmit the analyzed data to the single or multiple end user device through a single communication channel,
wherein the drone with offline capabilities transmit a analyzed data to a single or multiple end user device in offline mode without involvement of the internet intervention.
2. A method of analyzing a yield of the crop using a drone with on-board processing unit and offline capabilities for transmission of data 400 comprising:
capturing the raw images of a crop from a farm land using a inbuilt camera of the drone 401;
storing the captured raw images of a crop in an on-board memory unit of the drone 402;
processing the stored raw images of a crop in the image processor unit based on a predefined trained model database to obtain a processed data with various parameters of the crop 403;
analyzing the processed data with various parameters of the crop to obtain an analyzed data regarding the yield of the crops 404; and
transmitting the analyzed data to a base station through a transmitter in offline mode,
wherein the analyzed data generated comprises of analysis of yield and quality of the crop notifies a user where individual inspection is required.
3. Method, system and apparatus providing one or more features as described in the paragraphs of this specification.

Date: 13-07-2020 Signature………………………
OMPRAKASH S.N
Agent for Applicant
IN/PA-1095