scholarly journals Anti-Smuggling Alarm System for Trees in Forest using Raspberry pi

2021 ◽  
Vol 9 (VI) ◽  
pp. 190-195
Author(s):  
C. Varalakshmi
Keyword(s):  
Forest Fires ◽  
Preventive Measures ◽  
Base Station ◽  
Raspberry Pi ◽  
Alarm System ◽  
Water Pump ◽  
Cosmetic Products ◽  
Mems Sensor ◽  
System Data ◽  
Gps System

Nowadays, There are trees like Sandal; Sagwan etc are going to be smuggled. These trees are very costly and meagre. These are used in the medical and cosmetic products. To restrict their smuggling and to save forests around the globe some preventive measures needs to be deployed. To restrict the smuggling, we have developed a system which consists of two units i.e. Tree Unit and Main Server unit. The Tree Unit consists of MEMS sensor (to detect the inclination of tree when its being cut), Fire sensor (to detect forest fires) and GPS system. Data generated from these sensors is continuously monitored with the raspberry pi. Through the sensors, their output devices are activated via relay switch. The data of different tree units collected by a base station (Main Server Unit) by using WIFI module. For MEMS sensor a buzzer is activated and for Fire sensor a water pump is activated. Generated data is stored in Server over the Wi-Fi module. Forest officials get the alert when any event occurs so that appropriate action taken place. Camera is used to capture Image and send to Gmail. The location where smuggling happens can be tracked by GPS system.

scholarly journals An Iot Based Forest Fire Detection using Raspberry Pi

2019 ◽  
Vol 8 (4) ◽  
pp. 9126-9132
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Early Stage ◽  
Fire Detection ◽  
Base Station ◽  
Raspberry Pi ◽  
Alert Message ◽  
Forest Fire Detection ◽  
Monitoring Stations

As we all know forests are the main source of oxygen and its protection is essential to sustain the human and animal race. Since we all learnt about the necessity of air, yet we lack at taking measures to protect our mother forest. Forest Fires are the main reason for the deforestation and destruction of trees and wildlife. Forest Fires are due to these two ways either by man-made or naturally caused. In either way we have to pay for the loss occurred because we have left with only certain area for the forest. So, we have to take measures to prevent forest fire at its early stage. The main aim of our project is to design and implement an IoT based hardware module that could detect the fire and prevent it by alerting the monitoring stations with an alert message and also provides location to the nearest base station. An automatic message will be sent to the nearest base station in addition to these, it has a 360 degrees rotation camera which helps to provide continuous surveillance. We can rotate the camera in any direction from the base station itself. A buzzer that alarms when the incident is happening and a water motor, this water motor will be on automatically. We can also find location where the incident is taking place with the help of Wi-Fi module. This device helps in identifying the fire at its early stage and helps in the prevention of spread all over the forest.

scholarly journals Investigation of the Earth Ionosphere Using the Radio Emission of Pulsars

2013 ◽  
Vol 22 (1) ◽  
Author(s):  
O. M. Ulyanov ◽  
A. I. Shevtsova ◽  
D. V. Mukha ◽  
A. A. Seredkina
Keyword(s):  
Magnetic Field ◽  
Radio Emission ◽  
Dispersion Measure ◽  
Pulsar Radio ◽  
The Earth ◽  
Lack Of Information ◽  
Rotation Measure ◽  
System Data ◽  
Gps System ◽  
The Impact

AbstractThe investigation of the Earth ionosphere both in a quiet and a disturbed states is still desirable. Despite recent progress in its modeling and in estimating the electron concentration along the line of sight by GPS signals, the impact of the disturbed ionosphere and magnetic field on the wave propagation still remains not sufficiently understood. This is due to lack of information on the polarization of GPS signals, and due to poorly conditioned models of the ionosphere at high altitudes and strong perturbations. In this article we consider a possibility of using the data of pulsar radio emission, along with the traditional GPS system data, for the vertical and oblique sounding of the ionosphere. This approach also allows to monitor parameters of the propagation medium, such as the dispersion measure and the rotation measure using changes of the polarization between pulses. By using a selected pulsar constellation it is possible to increase the number of directions in which parameters of the ionosphere and the magnetic field can be estimated.

scholarly journals Development of a real-time framework for farm monitoring using drone technology

2020 ◽  
Vol 9 (4) ◽  
pp. 244
Author(s):  
Adekunle T. Oyelami ◽  
Adedayo S. Akinade ◽  
Kingsley C. Obianefo
Keyword(s):  
Real Time ◽  
Flight Control ◽  
Video Transmission ◽  
Cost Effective ◽  
Base Station ◽  
Alarm System ◽  
Tracking Systems ◽  
Live Feed ◽  
Real Time Image ◽  
Time Image

This work developed a cost-effective framework for agriculturists to regularly monitor their crops against intruding rodents and other security concerns using modern drone technology through configuration and deployment of an autonomous UAV which also functions as a remotely piloted vehicle. This was done by configuring a quadcopter capable of causing a disturbance when a rodent is observed through an inbuilt alarm system whose sound is amplified to be loud enough to cause the animals to leave the farm area. A framework for real-time image and live video transmission from the farm to a designated remote base station was developed. This was achieved through programming codes that configured the drone to operate an intelligent alarm and object tracking systems which enables a live feed from the UAV using Arduino IDE and Mission Planner for autonomous flight control. The requisite algorithms were developed using the framework of tracking, learning and detection (TLD) in the OpenCV software. The drone movement is equally controlled remotely over a Wi-Fi network using an ESP8266 Wi-Fi module for redirection and controlling of the drone movement to monitor specific locations.

scholarly journals Smart Helmet - Intelligent Safety Helmet

2021 ◽  
pp. 1254-1261
Author(s):  
Sanket Gokule ◽  
Sanket Gilbile ◽  
Shivam Bhat ◽  
Dr. P. B. Kumbharkar ◽  
Vivek Yemul
Keyword(s):  
High Speed ◽  
Emergency Services ◽  
Preventive Measures ◽  
Wearable Devices ◽  
Raspberry Pi ◽  
Road Accidents ◽  
Smart System ◽  
The Past ◽  
Knowing That ◽  
Advanced Technologies

Bike riding is a lot of fun, but accidents happen. People choose motorbikes over cars as it is much cheaper to run, easier to park and flexible in traffic. In India, more than 37 million people are using two wheelers. Since usage is high, accident percentage of two wheelers are also high compared to four wheelers. Motorcycles have a higher rate of fatal accidents than four wheelers. The impacts of these accidents are more dangerous when the driver is involved in a high-speed accident without wearing a helmet. It is highly dangerous and can cause severe deaths. So, wearing a helmet can reduce this number of accidents and may save lives. Smart Helmet - Intelligent Safety Helmet for Motorcyclists is a project undertaken to increase the awareness of wearing helmets among motorcyclists. The idea is obtained after knowing that there has been an increased number of fatal road accidents over the years. Therefore, this project is designed to ensure safety of the motorcyclist. Much research in the past has been done on wearable devices which provide users with a smart system for tracking human actions and also taking preventive measures in emergency conditions. This motivates the use of advanced technologies available today like Raspberry Pi, Impact sensors, GPS, GSM technology. These technologies help us detect the accident and send the location to family members and emergency services.

scholarly journals INTERNET OF THINGS (IOT) BASED ADVANCED ONLINE EXAMINATION USING RASPBERRY PI

2020 ◽  
Vol 5 (5) ◽  
pp. 26-32
Author(s):  
Kunal Pawar ◽  
Pravin Latane
Keyword(s):  
Face Recognition ◽  
Internet Of Things ◽  
Raspberry Pi ◽  
Alarm System ◽  
Iot Applications ◽  
System A ◽  
Implementation Techniques ◽  
Online Examination ◽  
On Line ◽  
Exam System

In this research we have proposed IOT based advanced Online examination using Raspberry pi for Alarm system and border security. With the event of recent education, considering the defect of current online exam system, a replacement projection of online exam system primarily based on Raspberry pi IOT is projected, and also the key implementation techniques and ways also are represented. Internet of Things (IOT) has provided a promising chance to make powerful Examination systems and applications by leverage the growing omnipresence of wireless, RFID mobile and detector devices. a large vary of IOT applications are developed in recent years. In a shot to grasp the event of IOT in on-line examination, here we tend to propose this analysis of IOT, IOT key facultative technologies, major IOT applications in on-line examination and identifies analysis trends and challenges. Here we tend to introduce all the examiner details square measure holds on within the server. Then if somebody needs to starts on-line examination, 1st they ought to apply face recognition (in Open CV based) technique. as a result of it slow unwanted person conjointly enter to Wright the examination, thus this can be the simplest thanks to known any culprits square measure found or not. Then examination enter to Wright the exam, here conjointly I am apply some security. Currently a day’s already queries square measure hold on within the on-line or any paper written copy.

scholarly journals Design Dan Implementasi Wireless Sensor Network Pada Prototype Pendeteksian Material Galodo

2019 ◽  
Vol 11 (1) ◽  
pp. 39-42
Author(s):  
Era Madona ◽  
Muhammad Irmansyah ◽  
Yulastri Yulastri ◽  
Anggara Nasution
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Laboratory Testing ◽  
Flash Flood ◽  
Wireless Sensor ◽  
Raspberry Pi ◽  
Output Data ◽  
Database Server ◽  
Material Detection ◽  
System Data

Flash flood (debris flow) or people of Padang called  “galodo”  is one disaster that could threaten any time, especially at plateau with high rainfall. This study is an attempt to design prototype which is implemented to detect the content of the existing material in river flows due to “Galodo”. This research design and implement the wireless sensor network to transmit information or sensor output data and data receivers on prototype of “Galodo” material detection with laboratory testing scale. This system consist of a transmitter device that includes a sound sensor, Arduino Uno, and XBee S2, and a receiver that includes the XBee S2 and raspberry Pi as a database server. Data in data server are expected can distinguish the water in” Galodo” bring small material such as sand or larger or just contain of water. The information obtained display in graphic on the website to system data monitoring including time delay for sending data from transmitter to receiver.

scholarly journals Smart Internet of Things Based Induction Motor Parameter Monitoring and Control System

2021 ◽  
Vol 9 (6) ◽  
pp. 253-256
Author(s):  
M.Ambika ME ◽  
Madhunisha M.
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Induction Motor ◽  
Data Communication ◽  
Heat Treating ◽  
Research Paper ◽  
Base Station ◽  
Raspberry Pi ◽  
Monitoring And Control ◽  
Remote Station

Automation is the use of various control systems for operating equipment such as machinery, processes in industries such as boilers and heat treating ovens, switching on telephone networks, steering and stabilization of ships, aircraft and other applications with minimal or reduced human intervention. This research paper presents advanced approaches using wireless monitoring system for induction motor based on Internet of Things (IoT) for safe and economic data communication. n the first approach, state of the art fault detection strategy is exhibited for induction motor. This research paper depends on the assessment of measured voltage, current, earth leakage, rotor status and speed. Progressed embedded strategy and utilized to isolate and survey the disappointment seriousness. In this procedure, distinctive sensors are associated with the motor, and the quantities are extracted by utilizing a microcontroller. The Graphical User Interface (GUI) with cloud server IoT is used to transmit the data from base station to remote station. This arrangement allows the client to interface with the framework. The proposed research paper based induction motor control system is validated through the simulation in Raspberry Pi 3 environment.

Advance Development of Warning Alarm System for Earthquake Using MEMS Sensor

2018 ◽  
Vol 9 (12) ◽  
pp. 1553
Author(s):  
TV Prasad ◽  
B Barik ◽  
BL Ratnavalli ◽  
Babu D Satti
Keyword(s):  
Alarm System ◽  
Mems Sensor

scholarly journals Semi-Autonomous Coordinate Configuration Technology of Base Stations in Indoor Positioning System Based on UWB

Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 33
Author(s):  
Xiaofei Yang ◽  
Jun Wang ◽  
Hui Ye ◽  
Jianzhen Li
Keyword(s):  
Large Scale ◽  
Target Location ◽  
Wide Band ◽  
Indoor Positioning ◽  
Base Station ◽  
Base Stations ◽  
Positioning System ◽  
Linear Network ◽  
Gps System ◽  
Indoor Positioning System

In the global positioning system (GPS) denied environment, an indoor positioning system based on ultra-wide band (UWB) technology has been utilized for target location and navigation. It can provide a more accurate positioning measurement than those based on received signal strength (RSS). Although promising, it suffers from some shortcomings that base stations should be preinstalled to obtain reference coordinate information, just as navigation satellites in the GPS system. In order to improve the positioning accuracy, a large number of base stations should be preinstalled and assigned coordinates in the large-scale network. However, the coordinate setup process of the base stations is cumbersome, time consuming, and laborious. For a class of linear network topology, a semi-autonomous coordinate configuration technology of base stations is designed, which refers to three conceptions of segmentation, virtual triangle, and bidirectional calculation. It consists of two stages in every segment: Forward and backward. In the forward stage, it utilizes the manual coordinate setup method to deal with the foremost two base stations, and then the remaining base stations autonomously calculate their coordinates by building the virtual triangle train. In the backward stage, the reverse operation is performed, but the foremost two base stations of the next segment should be used as the head. In the last segment, the last two base stations should be used as the head. Integrating forward and backward data, the base stations could improve their location accuracy. It is shown that our algorithm is feasible and practical in simulation results and can dramatically reduce the system configuration time. In addition, the error and maximum base station number for one segment caused by our algorithm are discussed theoretically.

Intelligent Configuration of Condition Monitoring Algorithms

2015 ◽  
Vol 794 ◽  
pp. 355-362 ◽  
Author(s):  
Abdelhakim Laghmouchi ◽  
Eckhard Hohwieler ◽  
Claudio Geisert ◽  
Eckart Uhlmann
Keyword(s):  
Embedded System ◽  
Condition Monitoring ◽  
Development Process ◽  
Modular Design ◽  
Production Systems ◽  
Raspberry Pi ◽  
Operating Parameters ◽  
Monitoring Tool ◽  
Test Rig ◽  
Mems Sensor

The aim of this paper is to present the design of a condition monitoring tool, its use for the intelligent configuration of pattern recognition algorithms, for fault detection, and for diagnosis applications. The modular design and functionality of the tool will be introduced. The tool, developed and implemented by Fraunhofer IPK, can be used, in particular, to support the development process of algorithms for condition monitoring of wear-susceptible components in production systems. An example of the industrial application of the tool will be presented. This will include the implementation of configured algorithms using the tool on an embedded system using Raspberry Pi 2 and MEMS sensor. Finally, the evaluation of these algorithms on an axis test rig at different operating parameters will be presented.

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