an iot based smart solution for leaf disease detection

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IOT in Smart Farming

ChandanaMayaS

918 prasu seminar

gujjeti prasanna

This document discusses an Internet of Things (IoT) based smart agriculture monitoring system. It begins with an introduction to IoT and why it is being implemented in the agriculture sector. It then discusses several applications of IoT in agriculture including crop water management using soil moisture sensors, pest management using passive infrared sensors, precision agriculture, and ensuring food production and safety. The document outlines the implemented method using sensors connected to an Arduino board and Raspberry Pi to monitor data and send alerts. It discusses the advantages of optimizing water use and increasing productivity but notes the potential disadvantage of high initial costs.

Kapil dikshit ppt

kapil dikshit

This document outlines a proposed plant leaf disease detection system using image processing on Android mobile phones. The system aims to help farmers easily and cost-effectively detect plant diseases, identify severity levels, and receive treatment suggestions. It will use algorithms like blob detection and HSV color modeling to analyze leaf images and determine diseases. The Android app is intended to provide an affordable solution to identify a variety of disease types and inform farmers in their local language.

Wireless human health Monitor

Amarendra K Yadav

This document outlines a student project to develop a wireless human health monitoring system. It will use sensors to measure a patient's heartbeat and temperature, transmitting the data via GSM to a receiver where a doctor can monitor the patient's condition remotely. The system aims to make monitoring more affordable and accessible for rural areas. It will help bridge the gap between doctors and patients to save lives. The document describes the existing solutions and their drawbacks, the objectives and modules of the proposed system, and its potential future applications.

Heart Attack Prediction using Machine Learning

mohdshoaibuddin1

PATIENT MONITORING SYSTEM USING IOT

AM Publications

Now-a-days, a growing number of people in a developing countries like India forces to look for new solutions for the continuous monitoring of health check-up. It has become a necessity to visit hospitals frequently for doctor’s consultation, which has become financially related and a time consuming process. To overcome this situation, we propose a design to monitor the patient’s health conditions such as heart beat, temperature, ECG and BP and send the message to guardian using GSM. In the recent development of internet of things(IoT) makes all objects interconnected and been recognized as the next technical revolution. Patient monitoring is one of the IoT application to monitor the patient health status. Internet of things makes medical equipments more efficient by allowing real time monitoring of health. Using IoT doctor can continuously monitor the patient’s on his smart phone and also the patient history will be stored on the web server and doctor can access the information whenever needed from anywhere.

Iot based smart farming

amit kumar pandey

This document discusses how IoT technologies can be applied to smart farming. It describes how sensors, software, connectivity tools, and data analytics can be used to precisely monitor farm conditions and optimize production. Specifically, it explains how precision farming allows customized treatment on a micro-level using tools like sensors to measure soil conditions, humidity, etc. It also discusses applications of IoT in areas like greenhouse automation to control the environment, livestock monitoring to detect health issues early, and use of drones to assess crops and fields.

Sensor based smart agriculture system

AbhijeetKumar346

This document describes a proposed sensor-based intelligent agriculture system. The system would use various sensors deployed around a farm to monitor soil moisture, temperature, humidity, pH and for intruders. The sensor data would be sent to a microcontroller and thresholds would trigger alerts by SMS to the farmer if issues are detected. The system is aimed at reducing human effort, accurately analyzing farm conditions, reducing costs and helping preserve soil fertility.

Smart Agro System

Badrinath Danave

This document describes a smart agro system project created by four students. The system uses a wireless sensor network and sensors to monitor soil properties like moisture, temperature, humidity, and pH levels. It provides farmers recommendations on fertilizer use and irrigation. The objectives are to create an effective, low-cost, user-friendly decision support system. It will help farmers reduce waste, increase yields, and improve their lives. The system hardware uses an Arduino platform and sensors. The software includes an Android app and database. Future work includes cloud storage and adding animal monitoring sensors. The conclusion is that the system will help farmers monitor fields and activities to boost production through efficient water and input use.

430178048 project-ppt-pptx

Anish Mate

The document discusses the development of a smart agriculture system using IoT. Various sensors are used to collect environmental data like soil moisture, temperature, and humidity. The data is sent to a Raspberry Pi gateway and then stored on the cloud. Farmers can monitor the data through a mobile app. If the soil moisture is low, farmers are notified and can turn on motors to supply water. When moisture levels are adequate, they can turn off the motors. The system aims to increase crop yields while reducing water usage.

Modern agriculture with Internet Of Things

MKMK40

This document discusses smart agriculture and Internet of Things (IoT) sensors. It describes how modern agriculture uses data from various sources to manage farm activities, while smart agriculture focuses on soil conditions, weather, and crops. Smart systems differentiate themselves by recording and analyzing data to provide actionable insights. The document then lists several factors that can be measured by IoT sensors, including soil temperature, moisture, weather conditions, and provides details on how soil moisture and rain drop sensors work to measure these variables.

Smart ppt2

Raja Kandagatla

This document summarizes a student project to create a smart farm soil moisture detection system using a Raspberry Pi. The project aims to monitor soil moisture levels locally on an LCD screen or remotely via online dashboards. Key components include a soil moisture sensor, analog to digital converter, Raspberry Pi, and software to read sensor values and display them. The system will send daily emails if moisture drops below a threshold and has potential for automating watering based on soil conditions.

A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase

ijtsrd

The early prognosis of cardiovascular diseases can aid in making decisions to lifestyle changes in high risk patients and in turn reduce their complications. Research has attempted to pinpoint the most influential factors of heart disease as well as accurately predict the overall risk using homogenous data mining techniques. Recent research has delved into amalgamating these techniques using approaches such as hybrid data mining algorithms. This paper proposes a rule based model to compare the accuracies of applying rules to the individual results of logistic regression on the Cleveland Heart Disease Database in order to present an accurate model of predicting heart disease. K. Sandhya Rani | M. Sai Chaitanya | G. Sai Kiran"A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11402.pdf http://www.ijtsrd.com/computer-science/data-miining/11402/a-heart-disease-prediction-model-using-logistic-regression-by-cleveland-database/k-sandhya-rani

IOT BASED SMART AGRICULTURE

sree vidyanikethan engineering college

This document discusses Internet of Things (IoT) applications in agriculture. It defines IoT as the internetworking of physical devices that can transfer data over a network without human interaction. Key IoT applications in agriculture discussed include crop water management using soil moisture sensors, pest management using motion sensors, and precision agriculture. The document outlines an implemented method using Arduino, sensors, and wireless communication to monitor soil moisture levels and detect predator motion to send alerts and reduce crop damage while optimizing water usage.

Artificial Intelligence in Agriculture

Dr. Pavan Kundur

Ai in agriculture

Mitul Mohapatra

Artificial intelligence can benefit the agriculture sector by increasing productivity and sustainability. As the global population grows, AI technologies like drones, automated systems, agricultural robots, remote sensing, and decision support systems can help monitor crop conditions, identify issues, automate processes, and support farmers' decisions. While these applications may have initial financial and expertise barriers, their benefits include enhanced crop yields, quality and safety, efficient farm management, and reduced risks. Overall, AI can help modernize agriculture and optimize outputs to better feed the world's growing population.

Automatic Wireless Health Monitoring System In Hospitals For Patients

Edgefxkits & Solutions

Disease prediction and doctor recommendation system

sabafarheen

This document presents a disease prediction and doctor recommendation system. The system aims to analyze healthcare data to predict diseases and provide accurate risk predictions to help control disease. It uses a naive Bayes classification algorithm to predict diseases based on patient symptoms and medical profiles. The system then recommends specialist doctors for the predicted disease based on filters like location, cost, experience level, and reviews. It was found to accurately predict diseases 63-83% of the time based on previous studies. The goal is to improve prediction using more symptoms and medical cases.

RICE PLANT DISEASE DETECTION AND REMEDIES RECOMMENDATION USING MACHINE LEARNING

IRJET Journal

This document describes a machine learning approach to detect diseases in rice plants from images and recommend remedies. It discusses three common rice diseases - leaf blast, bacterial leaf blight, and hispa - and how a convolutional neural network was trained on thousands of images to classify diseases. The proposed method uses CNN layers to extract features from images and fully connected layers to classify diseases. It aims to help farmers early detect diseases from photos and provide effective treatment recommendations to improve crop yields.

IOT in Agriculture slide.pptx

DHANPDGHALE

This document provides an overview of how Internet of Things (IoT) and big data analytics can be applied to smart agriculture management. It discusses key concepts like IoT, how sensor data is collected and analyzed in big data systems, and how this data can be used to improve decision making for smart agriculture. The document also outlines some of the challenges of implementing these systems at scale, such as technical complexity and economic efficiency concerns. Overall, the document examines how applying IoT and big data analytics can help modernize agriculture and increase productivity, yield, and supply chain optimization.

What's hot (20)

IOT in Smart Farming

918 prasu seminar

Kapil dikshit ppt

Wireless human health Monitor

Heart Attack Prediction using Machine Learning

PATIENT MONITORING SYSTEM USING IOT

Iot based smart farming

Sensor based smart agriculture system

Smart Agro System

430178048 project-ppt-pptx

Modern agriculture with Internet Of Things

Smart ppt2

A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase

IOT BASED SMART AGRICULTURE

Artificial Intelligence in Agriculture

Ai in agriculture

Automatic Wireless Health Monitoring System In Hospitals For Patients

Disease prediction and doctor recommendation system

RICE PLANT DISEASE DETECTION AND REMEDIES RECOMMENDATION USING MACHINE LEARNING

IOT in Agriculture slide.pptx

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IOT-ENABLED SMART AGRICULTURE SYSTEM WITH DEEP LEARNING FOR THE IDENTIFICATIO...

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The document describes an IOT-enabled smart agriculture system that uses deep learning to identify plant diseases. The system consists of IoT devices like sensors and cameras that collect data on plants and send it to a cloud-based deep learning model. The model analyzes the images to identify diseases and sends the information back to farmers. This allows farmers to remotely monitor crops and take timely action to treat diseases, improving efficiency and reducing crop losses. Deep learning enables accurate identification of diseases even with subtle symptoms and can process large amounts of data quickly. The system is expected to become an essential tool for farmers to advance sustainable agriculture practices.

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an iot based smart solution for leaf disease detection