LORA-BASED SOLUTION FOR EFFICIENCY AND HEALTH MONITORING OF HIGH-CAPACITY TRUCK-MOUNTED CHIPPER IN FORESTRY OPERATIONS

Abstract

A Lora-based system for efficiency and health monitoring of high-capacity truck-mounted chipper in forestry operations comprises LBSET_MCMote (10) is an onboard sensing unit that continuously gathers vital data on vibration, temperature, and pressure from a high-capacity truck-mounted chipper, it is outfitted with a Raspberry Pi Processor Board (10E), Lora RF Module (10F), MEMS Vibration Sensor (10A), Temperature Sensor (10B), Pressure Sensor (10C), and Power Supply (10D), this allows for real-time monitoring and contributes to the overall effectiveness and health assessment of the forestry equipment utilizing both the LoRa RF Module and the ESP8266 WiFi Board to establish seamless connectivity between the high-capacity truck-mounted chipper and the cloud-based IoT platform, the LBSER_MCMote which is outfitted with a Raspberry Pi Processor Board, Lora RF Module, ESP8266 WiFi Board, Touch HMI Display, and Power Supply serves as a central communication hub, additionally, it offers operators a user-friendly interface through the Touch HMI Display, allowing them to access real-time insights and critical alerts, thereby improving the overall efficiency and maintenance of forestry operations.

Specification

Description:FIELD OF THE INVENTION
This invention relates to lora-based solution for efficiency and health monitoring of high-capacity truck-mounted chipper in forestry operations.
BACKGROUND OF THE INVENTION
This innovative technology, which provides real-time monitoring and analysis of the effectiveness and condition of a high-capacity truck-mounted chipper, is an essential part of forestry operations. By means of an intricate combination of sensors and communication technologies, the system reliably gathers vital information regarding temperature, pressure, and vibration. After that, this data is easily transferred to a cloud-based platform, where sophisticated machine learning algorithms examine it to look for trends and abnormalities. When inconsistencies are found, alarms are generated and presented on an intuitive user interface and a web dashboard that an authorised operator can view.
One of the biggest challenges facing the forestry industry is successfully managing and ensuring the safety of large truck-mounted chippers during operation. Existing surveillance systems often have restricted functionality, making it challenging to detect possible problems early on. The absence of a strong solution that combines cloud-based analytics, long-range communication, and advanced sensor technologies hinders the industry's ability to address equipment health and efficiency issues in a proactive manner.
CN107263655A: This technology discloses a kind of cutterhead fixing device of wood chipper, including cutterhead, the outer circumferential walls of the cutterhead offer equally distributed insert groove, and the quantity of insert groove is eight to ten, blade is formed between described two insert grooves to lean on, the side two ends that the blade is leaned on are offered is threaded with the first blade fastening bolt and the second blade fastening bolt respectively in two screwed holes parallel to the circumference of cutterhead, and two screwed holes.The first motor rotated with movable knife disc is fixed on contiguous block, contiguous block can be moved up and down by the second motor with screw mandrel, move up and down cutterhead, and timber is processed with the need for tackling different thicknesses size, improve the efficiency of wood chipping equipment, the each blade of cutterhead is installed with two fastening bolts, and thrust is strong, blade is brought into close contact with cutterhead, rigidity reinforced, reduce the blade caused by vibrations to be lost, cost is lower, and processing effect is more preferable.
RESEARCH GAP: Lora based innovative solution for remotely health monitoring of High-Capacity Truck-Mounted Chipper in Forestry is the novelty of the system.
CN212193553U: The utility model discloses a drum chipper, the top of the frame is fixedly connected with a chipper shell, the front plate and the back plate are respectively fixedly connected with the front side and the back side of the frame, one side of the top plate is rotatably connected with one side of the front plate and the back plate, the other side of the front plate and the back plate is provided with a feeding part, a driving gear is sleeved on the feeding motor, a driven gear is sleeved on the material conveying roller shaft, a transmission chain is sleeved between the driving gear and the driven gear, a chipper cavity at one side of the material conveying roller shaft is arranged between the front plate and the back plate, one side of the top plate is provided with a chipper motor, the output shaft of the chipper motor is connected to a chipper shaft through a transmission belt, two ends of the chipper shaft respectively pass through the front plate and the back plate, a chipper roller is sleeved on the surface of the chipper shaft, a plurality of blades are evenly arranged on the surface of the chipper, and a discharge hole is reserved at the bottom of the frame. The utility model discloses effectively make timber cutting even.
RESEARCH GAP: Lora based innovative solution for remotely health monitoring of High-Capacity Truck-Mounted Chipper in Forestry is the novelty of the system.
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.
The two primary components of the collaborative system that powers the invention are LBSET_MCMote and LBSER_MCMote. The high-capacity truck-mounted chipper uses the LBSET_MCMote as its sensing unit. It is equipped with a Raspberry Pi Processor Board, LoRa RF Module, MEMS Vibration Sensor, Temperature Sensor, Pressure Sensor, and Power Supply. This module continuously collects vital operational data, such as pressure conditions, temperature swings, and vibration levels, providing a thorough understanding of the chipper's performance and well-being. The LoRa RF Module facilitates communication between LBSET_MCMote and LBSER_MCMote, guaranteeing smooth data transfer, particularly in remote forestry locations. An ESP8266 WiFi Board is also included with LBSER_MCMote, which acts as an additional communication channel and increases the range of data transfer. After that, the gathered data is sent to a cloud server that has been specially built for this innovation.
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:
FIGURE 1: SYSTEM ARCHITECTURE
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.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
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.
The two primary components of the collaborative system that powers the invention are LBSET_MCMote and LBSER_MCMote. The high-capacity truck-mounted chipper uses the LBSET_MCMote as its sensing unit. It is equipped with a Raspberry Pi Processor Board, LoRa RF Module, MEMS Vibration Sensor, Temperature Sensor, Pressure Sensor, and Power Supply. This module continuously collects vital operational data, such as pressure conditions, temperature swings, and vibration levels, providing a thorough understanding of the chipper's performance and well-being. The LoRa RF Module facilitates communication between LBSET_MCMote and LBSER_MCMote, guaranteeing smooth data transfer, particularly in remote forestry locations. An ESP8266 WiFi Board is also included with LBSER_MCMote, which acts as an additional communication channel and increases the range of data transfer. After that, the gathered data is sent to a cloud server that has been specially built for this innovation.
This Internet of Things technology runs on the cloud and serves as the main hub for processing and storing data. Predefined machine learning algorithms activate once in the cloud. The gathered data is examined by these algorithms, which consider timestamps for temporal context. The purpose of the analysis is to find trends, abnormalities, and any problems pertaining to the efficiency and well-being of the chipper. Should a critical discrepancy be found during the study, the system will trigger an alert. This multifaceted alert system includes notifications that can be accessed by user authentication on a customized web dashboard as well as the Touch HMI Display that is mounted on the LBSER_MCMote. The web dashboard allows operators to remotely monitor and take rapid action when necessary by giving them a thorough overview of the chipper's operational state. In addition to the display interfaces, the system makes sure that emails are used to convey alerts. By ensuring that operators are quickly notified of possible problems, this multi-channel alerting system promotes proactive maintenance and reduces downtime.
BEST METHOD OF WORKING
The LBSET_MCMote is an onboard sensing unit that continuously gathers vital data on vibration, temperature, and pressure from a high-capacity truck-mounted chipper. It is outfitted with a Raspberry Pi Processor Board, Lora RF Module, MEMS Vibration Sensor, Temperature Sensor, Pressure Sensor, and Power Supply. This allows for real-time monitoring and contributes to the overall effectiveness and health assessment of the forestry equipment.
Utilizing both the LoRa RF Module and the ESP8266 WiFi Board to establish seamless connectivity between the high-capacity truck-mounted chipper and the cloud-based IoT platform, the LBSER_MCMote-which is outfitted with a Raspberry Pi Processor Board, Lora RF Module, ESP8266 WiFi Board, Touch HMI Display, and Power Supply-serves as a central communication hub. Additionally, it offers operators a user-friendly interface through the Touch HMI Display, allowing them to access real-time insights and critical alerts, thereby improving the overall efficiency and maintenance of forestry operations.
The inventive solution intended for efficiency and health monitoring of high-capacity truck-mounted chippers in forestry operations uses the Raspberry Pi Processor Board, which is integrated into both of the motes, to facilitate data processing, analysis, and communication tasks to enable real-time monitoring, data analytics, and seamless connectivity.
Both of the motes have a LoRa RF Module that allows long-range wireless data transmission between the LBSET_MCMote and the LBSER_MCMote. This makes it easier for real-time operational data from the high-capacity truck-mounted chipper to be continuously transferred to the cloud-based IoT platform for forestry operations.
The essential real-time data on the operational conditions of a high-capacity truck-mounted chipper is provided by the MEMS Vibration Sensor, Temperature Sensor, and Pressure Sensor, all of which are connected in LBSET_MCMote. This allows for thorough health monitoring and efficiency assessment in forestry operations.
To improve connectivity options, the ESP8266 WiFi Board connected to LBSER_MCMote offers a different communication channel, enables wider data transmission, and makes it easier for the high-capacity truck-mounted chipper and the cloud-based IoT platform to communicate with each other in forestry operations.
During forestry operations, the Touch HMI Display interfaced on LBSER_MCMote is utilized to give operators real-time insights in the user interface, alarms, and a thorough overview of the high-capacity truck-mounted chipper's operational state.
ADVANTAGES OF THE INVENTION
1. The onboard sensing device, LBSET_MCMote, uses a combination of sophisticated sensors and a Raspberry Pi Processor Board to reliably collect vital information on temperature, pressure, and vibration from a truck-mounted, high-capacity chipper. This makes it possible to monitor in real time, which helps with the evaluation of the general health and performance of forestry equipment.
2. The high-capacity truck-mounted chipper and the cloud-based IoT platform are seamlessly connected by means of the ESP8266 WiFi Board and LoRa RF Module, which are both utilized by the LBSER_MCMote, which serves as the primary communication hub. Furthermore, it offers an intuitive user interface via the Touch HMI Display, enabling operators to view important alerts and real-time data. This improves forestry operations' general effectiveness and upkeep.
3. In order to enable long-range wireless data transmission between LBSET_MCMote and LBSER_MCMote, the LoRa RF Module is essential as a communication link. This makes it easier for forestry operations to continuously transfer real-time operational data from the high-capacity truck-mounted chipper to the cloud-based IoT platform.
4. The temperature, pressure, and vibration sensors in the LBSET_MCMote together provide vital real-time information on the working conditions of a large truck-mounted chipper. This capacity makes it possible to monitor the overall health and evaluate the efficiency of forestry operations.
5. The ESP8266 WiFi Board in LBSER_MCMote offers a different communication channel, which improves connectivity options. Broader data transmission is made possible by this feature, which makes it easier for the high-capacity truck-mounted chipper and the cloud-based IoT platform to communicate with each other in forestry operations.
6. LBSER_MCMote's Touch HMI Display functions as an intuitive user interface, providing operators with real-time information, notifications, and a thorough rundown of the high-capacity truck-mounted chipper's operational status during forestry operations.
, Claims:1. A Lora-based system for efficiency and health monitoring of high-capacity truck-mounted chipper in forestry operations comprises LBSET_MCMote (10) is an onboard sensing unit that continuously gathers vital data on vibration, temperature, and pressure from a high-capacity truck-mounted chipper, it is outfitted with a Raspberry Pi Processor Board (10E), Lora RF Module (10F), MEMS Vibration Sensor (10A), Temperature Sensor (10B), Pressure Sensor (10C), and Power Supply (10D), this allows for real-time monitoring and contributes to the overall effectiveness and health assessment of the forestry equipment.
2. The system as claimed in claim 1, wherein utilizing both the LoRa RF Module and the ESP8266 WiFi Board to establish seamless connectivity between the high-capacity truck-mounted chipper and the cloud-based IoT platform, the LBSER_MCMote which is outfitted with a Raspberry Pi Processor Board, Lora RF Module, ESP8266 WiFi Board, Touch HMI Display, and Power Supply serves as a central communication hub, additionally, it offers operators a user-friendly interface through the Touch HMI Display, allowing them to access real-time insights and critical alerts, thereby improving the overall efficiency and maintenance of forestry operations.
3. The system as claimed in claim 1, wherein the inventive solution intended for efficiency and health monitoring of high-capacity truck-mounted chippers in forestry operations uses the Raspberry Pi Processor Board, which is integrated into both of the motes, to facilitate data processing, analysis, and communication tasks to enable real-time monitoring, data analytics, and seamless connectivity.
4. The system as claimed in claim 1, wherein Bboth of the motes have a LoRa RF Module that allows long-range wireless data transmission between the LBSET_MCMote and the LBSER_MCMote, this makes it easier for real-time operational data from the high-capacity truck-mounted chipper to be continuously transferred to the cloud-based IoT platform for forestry operations.
5. The system as claimed in claim 1, wherein the essential real-time data on the operational conditions of a high-capacity truck-mounted chipper is provided by the MEMS Vibration Sensor, Temperature Sensor, and Pressure Sensor, all of which are connected in LBSET_MCMote, this allows for thorough health monitoring and efficiency assessment in forestry operations.
6. The system as claimed in claim 1, wherein to improve connectivity options, the ESP8266 WiFi Board connected to LBSER_MCMote offers a different communication channel, enables wider data transmission, and makes it easier for the high-capacity truck-mounted chipper and the cloud-based IoT platform to communicate with each other in forestry operations.
7. The system as claimed in claim 1, wherein during forestry operations, the Touch HMI Display interfaced on LBSER_MCMote is utilized to give operators real-time insights in the user interface, alarms, and a thorough overview of the high-capacity truck-mounted chipper's operational state.

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