ADVANCED FOREST MOISTURE PREDICTION SYSTEM THROUGH XBEE RF WPAN TECHNOLOGY FOR ENHANCED MONITORING AND MANAGEMENT

Abstract

An advanced forest moisture prediction system through xbee rf wpan technology for enhanced monitoring and management comprises AFMTP_CTMote (100) is used to enable real-time monitoring of environmental parameters in forested areas, facilitate data collection, wireless communication, and a sustainable power supply for improved forest moisture prediction and management, it is equipped with an ATmega32 MCU Board (100H), an XBee RF Module with Base (100A), a Soil Sensor (100G), a DHT Sensor (100F), an Air Pressure Sensor (100D), an Indicator (100B), and a Solar Powered Power Supply (100C) to enable real-time monitoring, analysis, and proactive management of forest moisture levels, the AFMTP_CTMote, which is outfitted with an ATmega32 MCU Board, an XBee RF Module with Base, an ESP01 Wifi Board, a GSM Modem, a buzzer, and a solar-powered power supply, is used to gather vital data on temperature, humidity, wind speed, and air pressure, the data is transmitted wirelessly.

Specification

Description:FIELD OF THE INVENTION
This invention relates to advanced forest moisture prediction system through xbee rf wpan technology for enhanced monitoring and management.
BACKGROUND OF THE INVENTION
This innovative system uses a network of state-of-the-art gadgets equipped with a variety of sensors and communication features to revolutionize forest management. The system provides forest operators with critical notifications regarding forest moisture levels, trend analysis, and actionable insights through the use of sophisticated algorithms and AI-powered analytics. These capacities enhance the resilience and sustainability of forests by enabling timely decision-making and proactive actions to mitigate hazards such as wildfires, droughts, and environmental degradation.
The problem of improving forest moisture forecast and management in wooded areas is addressed by this innovation. Lack of up-to-date information and extensive coverage is a common problem with conventional methods of monitoring forest conditions, making it challenging to identify and reduce possible hazards like wildfires, droughts, and environmental degradation.
KR102309166B1: A method and system for predicting the spread of a forest fire and monitoring a recurrence using a Disposable IoT terminal are provided. A forest fire monitoring method according to an embodiment of the present invention comprises the steps of: a Drone spraying a Disposable IoT terminal equipped with a temperature sensor and a CO2 sensor; Disposable IoT terminal sprayed, measuring the temperature and CO2 concentration of the atmosphere; The Disposable IoT terminal compares the measured temperature and the CO2 concentration with the temperature and the CO2 concentration measured in the previous time to monitor the occurrence of a forest fire. This enables safer and more effective suppression of forest fires through predicting the spread of forest fires and monitoring re-ignition using Disposable IoT terminals.
RESEARCH GAP: A Wireless XBee based WPAN network equipped technological devices for Forest fire monitoring with the combination of RF and IoT Technology is the novelty of the system.
US10762758B2: Embodiments of the present invention relate to, in general, a fire detection device and notification system configured for generating alerts based on detected environmental conditions (e.g., temperature, humidity, presence of flame or smoke or combustion gas). In some embodiments, the fire detection device employs various sensor devices (e.g., temperature, humidity, flame, smoke, gas, and the like) to collect environmental data and determine whether the detected environmental conditions indicate the presence of or the increased possibility of a fire. In some embodiments, the invention further comprises a notification system for automatically generating and transmitting alerts to one or more computing devices (e.g., responder dispatch systems) based on the detection of hazardous conditions.
RESEARCH GAP: A Wireless XBee based WPAN network equipped technological devices for Forest fire monitoring with the combination of RF and IoT Technology 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.
To improve forest moisture prediction and management, the AFMTP system combines sensor technologies, wireless communication, solar power, cloud computing, and artificial intelligence. The technology helps forest managers to efficiently monitor and safeguard forest ecosystems by providing timely insights and practical recommendations. This novel method works by placing a network of specialized devices in strategic locations throughout forests. These gadgets, which go by the name AFMTP_CTMotes, are fitted with a variety of sensors and communication modules that enable the wireless gathering and sharing of essential environmental data. There are two varieties of AFMTP_CTMotes in the system, and each one serves a certain purpose in the network. The first kind is equipped with sensors, which continuously monitor vital environmental parameters necessary for determining the moisture content of forests. These sensors include soil sensors, DHT sensors for temperature and humidity, wind speed sensors, and air pressure sensors. Moreover, this device's visual indicators provide local observations. In order to strengthen communication capabilities, the second type of AFMTP_CTMote adds features such GSM modems and ESP01 WiFi boards.
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.
To improve forest moisture prediction and management, the AFMTP system combines sensor technologies, wireless communication, solar power, cloud computing, and artificial intelligence. The technology helps forest managers to efficiently monitor and safeguard forest ecosystems by providing timely insights and practical recommendations. This novel method works by placing a network of specialized devices in strategic locations throughout forests. These gadgets, which go by the name AFMTP_CTMotes, are fitted with a variety of sensors and communication modules that enable the wireless gathering and sharing of essential environmental data. There are two varieties of AFMTP_CTMotes in the system, and each one serves a certain purpose in the network. The first kind is equipped with sensors, which continuously monitor vital environmental parameters necessary for determining the moisture content of forests. These sensors include soil sensors, DHT sensors for temperature and humidity, wind speed sensors, and air pressure sensors. Moreover, this device's visual indicators provide local observations. In order to strengthen communication capabilities, the second type of AFMTP_CTMote adds features such GSM modems and ESP01 WiFi boards.
Because both varieties of AFMTP_CTMotes are solar-powered, they can operate continuously even in far-off forest areas, which lessens their dependency on outside power sources. These gadgets, which are dispersed across the forest in strategic locations, create a Wireless Personal Area Network (WPAN) that allows them to communicate with one another and with a central base station. The network's central base station acts as a data hub and is normally located within the WPAN range of all installed AFMTP_CTMotes. The base station, which is outfitted with XBee RF modules, receives data sent by the AFMTP_CTMotes. This data includes air pressure, temperature, humidity, wind speed, and air pressure readings that are obtained in real time from sensors positioned throughout the forest.
The base station transfers sensor data to a cloud server designed specifically for the AFMTP system after receiving it. The infrastructure built on the cloud makes it possible to store, process, and analyze the gathered data effectively. To gain knowledge about trends, prospective hazards, and forest moisture levels, predefined algorithms are used. The studied data is provided to forest managers via an easy-to-use web dashboard that provides real-time environmental parameter visualization, along with trending data charts that show changes over time. Operators are instantly emailed critical notifications that are triggered by predetermined thresholds or abnormal trends. Proactive forest management initiatives and decision-making are also aided by AI-based ideas and recommendations.
BEST METHOD OF WORKING
The AFMTP_CTMote is used to enable real-time monitoring of environmental parameters in forested areas, facilitate data collection, wireless communication, and a sustainable power supply for improved forest moisture prediction and management. It is equipped with an ATmega32 MCU Board, an XBee RF Module with Base, a Soil Sensor, a DHT Sensor, an Air Pressure Sensor, an Indicator, and a Solar Powered Power Supply.
To enable real-time monitoring, analysis, and proactive management of forest moisture levels, the AFMTP_CTMote, which is outfitted with an ATmega32 MCU Board, an XBee RF Module with Base, an ESP01 Wifi Board, a GSM Modem, a buzzer, and a solar-powered power supply, is used to gather vital data on temperature, humidity, wind speed, and air pressure. The data is transmitted wirelessly.
The two nodes' combined XBee RF Module with Base is utilized to enable smooth communication between AFMTP_CTMote devices. It is an essential part of setting up a Wireless Personal Area Network (WPAN) infrastructure, guaranteeing effective data transfer and coordination for all-encompassing forest moisture prediction and management.
In order to accurately predict and manage forest moisture, a variety of sensors are connected in AFMTP_CTMote, including the soil sensor, DHT sensor, wind speed sensor, and air pressure sensor. These sensors work together to provide comprehensive environmental data that allows for real-time monitoring of temperature, humidity, wind speed, and air pressure levels within forest ecosystems.
The AFMTP_CTMote's integrated ESP01 WiFi Board is used to increase the device's communication capabilities. It does this by allowing it to connect to WiFi networks and cloud-based services for smooth data transmission and remote monitoring of forest conditions. This improves the system's accessibility and connectivity for the purpose of managing forests.
The AFMTP_CTMote's integrated GSM modem is used to facilitate cellular network communication, guaranteeing data transmission and remote monitoring capabilities in places where WiFi connectivity may be spotty or nonexistent. This improves the system's coverage and dependability for efficient forest moisture prediction and management.
ADVANTAGES OF THE INVENTION
1. This innovation relies heavily on the AFMTP_CTMote, which makes it possible to monitor environmental factors in wooded areas in real time. By making data collecting, wireless connection, and sustainable power supply easier, it improves the management and prediction of forest moisture.
2. The AFMTP_CTMote functions as a little but essential sensor node in the forest, collecting critical information on temperature, humidity, wind speed, and air pressure. The wireless transmission of this data allows for the analysis, proactive management, and real-time monitoring of forest moisture levels.
3. The XBee RF Module with Base is an essential part of setting up a Wireless Personal Area Network (WPAN) architecture since it makes sure that AFMTP_CTMote devices communicate with each other seamlessly. This makes it easier to transmit and coordinate data efficiently, which is necessary for accurate forest moisture forecast and management.
4. The Soil Sensor, DHT Sensor, Wind Speed Sensor, and Air Pressure Sensor work together to give environmental data that is necessary for precise management and prediction of forest moisture. They make it possible to monitor temperature, humidity, wind speed, soil moisture content, and air pressure levels in forest ecosystems in real time.
, Claims:1. An advanced forest moisture prediction system through xbee rf wpan technology for enhanced monitoring and management comprises AFMTP_CTMote (100) is used to enable real-time monitoring of environmental parameters in forested areas, facilitate data collection, wireless communication, and a sustainable power supply for improved forest moisture prediction and management, it is equipped with an ATmega32 MCU Board (100H), an XBee RF Module with Base (100A), a Soil Sensor (100G), a DHT Sensor (100F), an Air Pressure Sensor (100D), an Indicator (100B), and a Solar Powered Power Supply (100C).
2. The system as claimed in claim 1, wherein to enable real-time monitoring, analysis, and proactive management of forest moisture levels, the AFMTP_CTMote, which is outfitted with an ATmega32 MCU Board, an XBee RF Module with Base, an ESP01 Wifi Board, a GSM Modem, a buzzer, and a solar-powered power supply, is used to gather vital data on temperature, humidity, wind speed, and air pressure, the data is transmitted wirelessly.
3. The system as claimed in claim 1, wherein the two nodes' combined XBee RF Module with Base is utilized to enable smooth communication between AFMTP_CTMote devices, it is an essential part of setting up a Wireless Personal Area Network (WPAN) infrastructure, guaranteeing effective data transfer and coordination for all-encompassing forest moisture prediction and management.
4. The system as claimed in claim 1, wherein order to accurately predict and manage forest moisture, a variety of sensors are connected in AFMTP_CTMote, including the soil sensor, DHT sensor, wind speed sensor, and air pressure sensor, these sensors work together to provide comprehensive environmental data that allows for real-time monitoring of temperature, humidity, wind speed, and air pressure levels within forest ecosystems.
5. The system as claimed in claim 1, wherein the AFMTP_CTMote's integrated ESP01 WiFi Board is used to increase the device's communication capabilities, it does this by allowing it to connect to WiFi networks and cloud-based services for smooth data transmission and remote monitoring of forest conditions, this improves the system's accessibility and connectivity for the purpose of managing forests.
6. The system as claimed in claim 1, wherein the AFMTP_CTMote's integrated GSM modem is used to facilitate cellular network communication, guaranteeing data transmission and remote monitoring capabilities in places where WiFi connectivity may be spotty or nonexistent, this improves the system's coverage and dependability for efficient forest moisture prediction and management.

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