yeshwanthlm Goto Github PK

-100daysofawsautomation

#100DaysOfAutomation

-100daysofcloud

100daysofcloud

100daysofk8s

#100DaysOfK8s

30daysofterraform

#30DaysOfTerraform

amonkincloud-blogs

amonkincloud-blogs

app-service-demo

aws-project-ideas

AWS-Project-Ideas

aws-rds-terraform

AWS RDS Instance with read-replica using Terraform

aws-solutions-architect-associate

Notes for AWS Solutions Architect Associate

aws-vpc-landing-zone-terraform

AWS VPC Landing Zone Terraform Repo

azurefundamentals-az-900-

AZ-900: Azure Fundamentals Exam Preparation Guide

boto3-course-youtube

Boto3-Course-YouTube

build-your-first-crud-api-in-aws

Build Your First CRUD API in AWS

community-programs-which-helps-in-cloud-devops-journey

Community Programs which Helps in Cloud/DevOps Journey

devops-essentials-ieee-webinar

devops-project-1

Jenkins CI/CD Pipeline - SonarQube, Docker, GitHub Webhooks Project

django-on-ec2

A simple todo app built with django

docker-flask-demo

docker-flask-demo

ec2-cloudwatch-monitoring

EC2-CloudWatch-Monitoring

ec2-memory-disk-monitoring

Monitor EC2 Memory and Disk Utilisation using CloudWatch

ec2-nodejs-demo

EC2-NodeJS-Demo

eda-project-on-aws

Step-by-Step Guide to Building a Simple EDA Project on AWS

eks-terraform-jenkins

EKS-Terraform-Jenkins

flask-todo-application

forest-connection

This is a hardware and software system for real time monitoring and detection of forest fires. With its help remote recognition of wood fires is possible as well as high-accuracy positioning of flame base. Hardware part of the system consists of a set of intellectual sensors which are installed inside the forese. The action range of sensors is 250 - 500m depending on the RF device and type of sensor. As for the sensors, video cameras, infrared imagers and other intellectual equipment are used. They detect fire areas by a number of measures and under different conditions. If the sensor detects a fire, the information is transmitted to control unit via various communication channels: optical, radio, wire, GSM, etc. In such a way forest data are transmitted to the software part of our project where they are processed and analyzed. The system will automatically find and identify the fire area. Thereafter the information is passed to special departments via built-in alerting service, Internet and even mobile networks. Characteristics of the System • Fire detection accuracy - up to 250 m • Direction detection accuracy -- 0.5° • Possibility to integration data from other information sources (weather and satellite information). • Possibility of efficient scaling and broadening of the system for coverage range extension. • Number of users - without limit. • Possibility to get information on mobile phones. • Automatic detection of potentially dangerous objects (smoke and flame). Advantages of System 1. Automatization of monitoring 2. Centrally managed monitoring of large areas 3. Opportunity detect fires at an early stage and its spread 4. High accuracy of fire detection 5. Decrease of human factor role when detecting fires 6. Low cost of installation and exploitation of the system in comparison with other forms of monitoring 7. Flexibility of the system depending on relief and customer wants

forrestknight

hackonload

host-resume-on-ec2

Host-Resume-on-EC2

installing-jenkins