Description:3. PREAMBLE OF THE DESCRIPTION
The following specification particularly describes the invention and the manner in which it is to be performed

Title of The Invention
AI AND DEEP LEARNING BASED DUSTBIN ROBOT FOR OFFICES AND COMMUNITY
Field of the Invention
This invention relates to AI and deep learning based dustbin robot for offices and community.
Background of the Invention
CN108908373B: The invention discloses a garbage classification recycling robot, which comprises a square underframe, wherein caster frames and a steering motor for driving the caster frames to rotate are arranged at four corners of the underframe; the caster frame is provided with a walking wheel and a walking motor for driving the walking wheel to rotate; a left side plate, a right side plate and a rear side plate are arranged on the underframe; a garbage classification recycling bin is arranged between the left side plate and the right side plate on the bottom frame; the garbage classification recycling bin is provided with garbage compacting devices at recycling ports; the garbage compacting devices are all provided with garbage crushing devices; the mechanical grippers are mounted at two ends of the top of the garbage classification recycling bin, the first camera is mounted in the middle of the top end of the garbage classification recycling bin, and the second camera for capturing garbage is mounted on the rear side plate; the garbage classification recycling robot is simple in structure and capable of automatically completing classification, crushing and pressing of garbage.
US10214350B2: An intelligent and information multi-vehicle collaboratively operating municipal refuse collection and transfer system and method are provided. The system comprises an automated system with multiple-degree of freedom intelligent dustbin grabbing, an operating system with two types of refuse vehicles collaborating, a multi-vehicle collaborative operation information system, and a fixed-point refuse collection operation confirmation and remote monitoring information management system for coordinating overall operation of the systems. The automated system with multiple-degree of freedom intelligent dustbin grabbing system is used for the refuse vehicles to automatically collect dustbins; the operating system with two types of refuse vehicles collaborating comprises a plurality of small- and medium-sized refuse vehicles and large capacity refuse vehicles. The small- and medium-sized refuse vehicles collect refuse in the dustbins according to multi-vehicle collaborative operation information with the support of the multi-vehicle collaborative operation information system, and the large capacity refuse vehicles are used to dock with the collected refuse and transport the refuse out of town with the support of the multi-vehicle collaborative operation information system. The method is the implementation of the above system. The system and method have good operability and high degree of intelligence and provide good results of refuse disposal.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is development of a garbage collecting robot that is equipped with advanced machine learning and cloud-based capabilities. Such a robot could collect garbage in public spaces, navigate around obstacles, and empty garbage cans in real-time, with minimal human intervention. The robot could leverage cloud computing to access real-time data about the status of public spaces, enabling it to optimize its routes and make informed decisions about where and when to collect garbage. Additionally, it could use deep learning to analyze data about the types and quantities of garbage in different areas, allowing it to adjust its collection strategies and optimize its performance over time.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
Fig-1 consists of computing unit, offline geo map, microphone, GPS, speaker, deep learning, relay, motors, battery power supply, external socket, Wi-Fi, container lid, dustbin calling button, cloud server, mobile app and users. First of all, when any user needs to throw the garbage at any time from an office or a community then he will call the robot by using the mobile app or dustbin calling button. This information will be sent immediately to the cloud server and then to the computing unit of the robot through Wi-Fi. After receiving the information the robot will move to the required place by using the offline geo map in which all the places are already stored. The relay and motors will activate and it will start moving to the required place. When it will reach at the correct place then it will ring the bell, greet the person by using the speaker, by using relay open the container lid and collect the garbage from him. If any user wants to say something to the robot then it will be done by using the microphone. If multiple users will call the robot at the same time then by using deep learning the robot will scan which place is near or where it can be reached quickly. Deep learning will help the robot in object recognition, navigation, motion control, speech and gesture recognition and human robot-interaction. External socket will give power to the battery power supply that will be powering computing unit, motors, relay, offline geo map, microphone, GPS, speaker and Wi-Fi.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein: Fig-1 consists of computing unit, offline geo map, microphone, GPS, speaker, deep learning, relay, motors, battery power supply, external socket, Wi-Fi, container lid, dustbin calling button, cloud server, mobile app and users. First of all, when any user needs to throw the garbage at any time from an office or a community then he will call the robot by using the mobile app or dustbin calling button. This information will be sent immediately to the cloud server and then to the computing unit of the robot through Wi-Fi. After receiving the information the robot will move to the required place by using the offline geo map in which all the places are already stored. The relay and motors will activate and it will start moving to the required place. When it will reach at the correct place then it will ring the bell, greet the person by using the speaker, by using relay open the container lid and collect the garbage from him. If any user wants to say something to the robot then it will be done by using the microphone. If multiple users will call the robot at the same time then by using deep learning the robot will scan which place is near or where it can be reached quickly. Deep learning will help the robot in object recognition, navigation, motion control, speech and gesture recognition and human robot-interaction. External socket will give power to the battery power supply that will be powering computing unit, motors, relay, offline geo map, microphone, GPS, speaker and Wi-Fi.
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
Fig-1 consists of computing unit, offline geo map, microphone, GPS, speaker, deep learning, relay, motors, battery power supply, external socket, Wi-Fi, container lid, dustbin calling button, cloud server, mobile app and users. First of all, when any user needs to throw the garbage at any time from an office or a community then he will call the robot by using the mobile app or dustbin calling button. This information will be sent immediately to the cloud server and then to the computing unit of the robot through Wi-Fi. After receiving the information the robot will move to the required place by using the offline geo map in which all the places are already stored. The relay and motors will activate and it will start moving to the required place. When it will reach at the correct place then it will ring the bell, greet the person by using the speaker, by using relay open the container lid and collect the garbage from him. If any user wants to say something to the robot then it will be done by using the microphone. If multiple users will call the robot at the same time then by using deep learning the robot will scan which place is near or where it can be reached quickly. Deep learning will help the robot in object recognition, navigation, motion control, speech and gesture recognition and human robot-interaction. External socket will give power to the battery power supply that will be powering computing unit, motors, relay, offline geo map, microphone, GPS, speaker and Wi-Fi.
ADVANTAGES OF THE INVENTION:
Increased efficiency: Robots can operate without getting tired or needing breaks, which can increase the speed and efficiency of garbage collection.
Reduced cost: By automating garbage collection, flats can reduce labour cost. This can help to make garbage collection more cost effective.
Improved safety: Garbage collection can be a hazardous job, involving heavy lifting, exposure to sharp objects and other safety risks. By using robots these risks can be minimized, protecting workers and reducing the likelihood accidents and injuries.
Consistency: Robots can be programmed to follow specific routes and schedules, ensuring that garbage is collected on time and in a consistent manner. This can help to improve the overall cleanliness and appearance of flats.
, Claims:1. AI and deep learning based dustbin robot for offices and community system is comprises with computing unit, offline geo map, microphone, GPS, speaker, deep learning, relay, motors, battery power supply, external socket, Wi-Fi, container lid, dustbin calling button, cloud server, mobile app and users.
2. The system is claimed in claim 1, wherein which is when any user needs to throw the garbage at any time from an office or a community then he will call the robot by using the mobile app or dustbin calling button.
3. The system is claimed in claim 1, wherein information will be sent immediately to the cloud server and then to the computing unit of the robot through Wi-Fi.
4. The system is claimed in claim 1, wherein which is receiving the information the robot will move to the required place by using the offline geo map in which all the places are already stored.
5. The system is claimed in claim 1, wherein which is consist of….