The document proposes a "SMART DAM" project that uses sensors, IoT devices, cloud computing and artificial intelligence to automate dam monitoring and operations. The system would allow dam authorities to remotely monitor water levels, weather data and control flood gates. It would also provide data to researchers and notify local communities of flood risks through siren alarms. The proposed architecture involves sensors transmitting data to a Raspberry Pi, cloud storage and an intelligent decision support system using neural networks to automate gate operations.
The document proposes an Internet of Things (IoT) based system to address issues with garbage disposal and agriculture in India. The system uses sensors in smart garbage bins to detect overflow and notify cleaners. Degradable garbage is converted to organic fertilizer and bio-degradable waste is used for road making. An IoT-enabled drip irrigation system is proposed to efficiently monitor water usage and notify farmers, improving crop yields. The system aims to achieve 100% garbage reuse and provide effective waste management and irrigation solutions.
This document proposes a microcontroller-based wireless power theft monitoring system. The system uses wireless sensor nodes connected to consumers, transformers, and transmission lines to monitor power usage. If differences are detected between measured and reported usage, it could indicate power theft. The system aims to reduce energy wastage and theft by detecting where illegal usage occurs and notifying authorities. Some limitations are an inability to identify exact theft locations or individuals, and potential challenges implementing on a large scale.
In today’s global scenario, water wastage and water shortage are an over rising problem. With the world population rising minute by minute, the need for water is increasing and therefore water conservation is the need of the hour. Today’s industries need huge amount of manpower for system supervision. We have come out with a solution where we use sensors to measure the water level of the storage system and be informed about the same, saving human efforts. Here, sensors are fit in the storage tank at different levels. The sensors are further connected to a microcontroller. The sensors detect the water level and inform it to the microcontroller which displays the storage tank status on the Liquid Crystal Display (LCD). A gate mechanism is also attached to this system which is triggered when the water level reaches the brim of the storage system.
IOT based Water Level Monitoring system is an improved system which will inform the users about the level of liquid and will prevent it from overflowing. To demonstrate this the system makes use of containers, where the ultrasonic sensors placed over the containers to detect the liquid level and compare it with the container’s depth. The system makes use of AVR family microcontroller, Arduino, LCD screen, Wi-Fi modem for sending data and a buzzer. A 12 V transformer is used for power supply in this system. The LCD screen is used to display the status of the level of liquid in the containers. The liquid level is highlighted as colored to show the level of liquid present in the container with the help of a web page to the user. The buzzer starts ringing when the set limit of the liquid is crossed. Thus this system helps
Automated irrigation system based on soil moisture using arduinoVishal Nagar
Automated irrigation system based on soil moisture using arduino
More Details: Contact me 9982228229
www.roofurja.com
vishalnagarcool.blogspot.com
https://www.youtube.com/watch?v=utHRD4B8BxQ
Automatic irrigation system by using 8051rohit chandel
The document describes a controller-based irrigation system that uses a soil moisture sensor and microcontroller to automate irrigation. The system monitors soil moisture levels and uses that data to operate a pump motor to water only when needed, reducing human intervention and ensuring proper irrigation. It senses moisture with a sensor connected to a comparator circuit that interfaces with an 8051 microcontroller programmed to turn a pump on or off. This automation conserves water, increases productivity, reduces labor costs and helps irrigate more land effectively.
ACCIDENT PREVENTION AND DETECTION SYSTEManand bedre
This document describes a student project to develop an Accident Prevention and Detection System (APDS) mobile application. The application uses GPS to track vehicle speed and location. If the speed exceeds a preset limit, the app will sound an alarm. If the user does not respond, emergency contacts will be notified. It will also detect sudden drops in speed and alert nearby hospitals. The goal is to reduce response times and save lives in the event of a vehicular accident. A group of students at K. K. Wagh Polytechnic are developing the Android app under faculty guidance with sponsorship from Sumago Infotech.
Traffic signal control management based on integrating GIS and WSN technologykrushna kotgire
This project is based on Geographic Information System (GIS). traffic signal can be controlled by using this method . We can avoid traffic jam, alternative path for user is genrated , no emergency vehicle is stuck in traffic.
This document presents a smart irrigation system that uses sensors to monitor soil moisture, temperature, and humidity wirelessly. It then sends the sensor data via GSM module to control watering. The system aims to reduce labor, conserve water, and allow real-time monitoring for better crop yields. Key components include soil moisture, temperature, and PIR sensors; Arduino and Raspberry Pi microcontrollers; and a GSM module to send alerts. Together, this smart irrigation system optimizes water usage for sustainable agriculture.
This document discusses how wireless sensor networks (WSNs) can be used in smart city applications. It first defines WSNs as self-configured, infrastructure-less networks that use sensors to monitor conditions like temperature, sound, and pollution. It then discusses how WSNs can influence lifestyle by enabling applications in areas like healthcare, transportation, the environment and more. Finally, it discusses how WSNs are a primary strength for smart cities by allowing remote and cost-effective monitoring of infrastructure and resources across applications like smart water, smart grid, and smart transportation.
Water quality monitoring in a smart city based on IOTMayur Rahangdale
The document describes a water quality monitoring system for smart cities using IoT. The system uses sensors to measure parameters like pH and turbidity in water samples. The sensor data is sent to a smartphone application in real-time via an Arduino board, WiFi module, and Blynk software. The smartphone app displays the sensor readings and issues alerts if water quality thresholds are exceeded. The system allows low-cost, automatic, and remote water quality monitoring to help ensure a safe drinking water supply.
This document describes an IOT liquid level monitoring system that uses ultrasonic sensors to detect liquid levels in four containers. It sends this data over WiFi to a web page using an AVR microcontroller, LCD screen, and WiFi modem. The web page displays a graphical representation of the liquid levels in the containers. When the liquid reaches a set limit, the system sounds a buzzer. This helps prevent overflow and wastage by remotely monitoring liquid levels.
This project uses soil moisture sensor and if the soil is dry, a mechanism to water the soil is set into motion. The whole circuit is controlled by the micro-controller based Arduino Uno Development Board.
This document describes a smart irrigation system that uses Internet of Things technology. It discusses the sensors used, including soil moisture sensors, temperature and humidity sensors, and relays. The document also covers the NodeMCU microcontroller, Blynk app for remote monitoring and control, and provides code examples. It notes that smart irrigation can help farmers more efficiently water crops based on soil conditions to save water and reduce costs compared to traditional irrigation methods.
This document describes a bus tracking application for students. The application uses GPS to track the real-time location of buses and send bus locations to students when requested. It also generates predicted arrival times at stops. The application was developed using Eclipse, Android SDK, and integrates Google Maps. It has modules for location information, maps, and bus/route details stored in a MySQL database.
Water Level indicator using Ultrasonic sensorsTough_taiga
This document describes an ultrasonic water level indicator project. The project aims to construct an electronic device that can automatically detect water level with high precision and control the water supply. It will automatically shut off the water when the reservoir is full. The circuit uses an ultrasonic sensor to detect the water level and a microcontroller to control a transistor that switches the water pump on and off. When the water level reaches the sensor, the circuit signals an alarm and shuts off the pump. The water level indicator has applications for monitoring water levels in places like hotels, factories, homes, and commercial buildings to prevent water wastage and shortages.
This document presents a proposal for a global wireless e-voting system using eye retina scanning for voter identification and authentication. The system would work by scanning a voter's retina, collecting their vote, encrypting this data along with the retina pattern, and transmitting the encrypted information via radio waves to a remote server for verification and vote tallying. The document outlines the key components of the proposed system, including the voting machine interface, retina scanner, radio transmission hardware, and remote server for authentication and vote storage. It also discusses security measures, limitations, and possibilities for enhancements like supporting mobile voting.
Iot based water quality monitoring systemBinayakreddy
As per increase in water pollution there is need of controlling pollution in water is finished by monitoring water quality.
Our system consists of various sensors which will compute the standard values of water in real time for effective action and is accurate and only less manpower required.
This document contains details about an individual named K.Satham Durai who aims to detect floods and alert nearby residents using fuzzy logic. It includes the objective to prevent loss of life and valuables, a block diagram of the system involving fuzzification, defuzzification, humidity and water level sensors, and a GSM module. Triangular and centroid methods are used for fuzzification and defuzzification. Rules are defined in a table to determine if a flood will occur based on humidity and water level. Sample inputs and outputs are also provided, with the conclusion that a fuzzy logic based system can effectively detect floods and issue alerts.
complete presentation on Smart Irrigation system using thingspeak technology is mainly helpful for the farmer to monitor the crop fields. Thingspeak is a platform, we can login with our matlab credentials.this system highly used in Mushroom cultivation because Mushroom cultivation is complete done in a perticuler Room, so this system will monitor the room Humidity, temperature, light and AirQuality. the hole process is we can monitor from any where in the world with help of Thingspeak platform.
IRJET- Flood Alerting System through Water Level MeterIRJET Journal
This document describes a flood alerting system that uses sensors to measure water levels in rivers and lakes. A micro-model is designed using a programmable electronic board connected to electrical resistances placed at different heights in a water container. When the water level reaches a resistance, the sensor transmits the information via WiFi to computers and smartphones so users can see the water level. The system aims to provide timely information to residents in low-lying areas about changes in water levels and predict safe water levels to save lives during floods. Experimental tests of the micro-model produced acceptable results.
This presentation provides an overview of a flood and rainfall prediction system. The system aims to increase awareness and reduce loss by allowing users to search rainfall ranges and flood histories in different areas. It uses machine learning models like artificial neural networks trained on historical rainfall and flood data to provide real-time flood predictions and early warnings. The system has features like fast performance, hazard mapping, and update capabilities. It faces challenges in data collection, model selection, and accuracy improvement with limited data.
The document describes a proposed advanced flood detection system based on sensor technology and machine learning algorithms. The system would use sensors to collect data on water levels and other environmental factors. This data would be processed using an Arduino and classified using a random forest machine learning algorithm to detect flooding. If flooding is detected based on threshold values, alerts would be sent to users through a cloud-based IoT platform to warn of the flood risk in real-time. The system is intended to provide low-cost flood monitoring and warnings.
IRJET- A Survey Paper on Dam ManagementIRJET Journal
This document discusses various approaches to dam management through the use of sensors and IoT technologies. It provides an overview of 16 research papers related to using sensors to monitor water levels, detect cracks and corrosion, control dam gates automatically, and provide early flood detection. The goal of the discussed research is to improve dam safety and water management by automating monitoring and control functions to minimize failures and optimize water distribution. IoT technologies allow data from sensors to be transmitted remotely for analysis and timely decision making by authorities. The surveyed approaches aim to enhance dam safety and efficiency through automated monitoring and control systems.
IRJET- A Real Time Solution to Flood Monitoring System using IoT and Wireless...IRJET Journal
This document describes a proposed real-time flood monitoring system using IoT and wireless sensor networks. The system would use sensors to monitor water levels, rainfall, temperature, humidity, and pressure to detect potential floods. If thresholds are reached, alerts would be sent via an Android app and website. The sensors would send data to a server and database via WiFi. The app and website would allow users to view sensor readings and maps of safe locations to evacuate to. The goal is to inform people of upcoming floods and direct them to safety.
Crop Prediction using IoT & Machine Learning AlgorithmIRJET Journal
This document describes a proposed system for crop prediction using IoT sensors and machine learning algorithms. Soil moisture, temperature, humidity, light, and rainfall data would be collected from sensors and sent to a server using an Arduino, NodeMCU, and IoT technology. The data would be stored in a MongoDB database and analyzed using machine learning algorithms like decision trees and random forests. The models would be trained to predict the optimal crop to plant based on the environmental conditions. A GUI would display the predicted crop recommendations to farmers based on real-time sensor readings or historical area data, helping farmers increase crop yields through informed decision making. The system aims to improve agricultural output and profits using IoT, machine learning, and predictive analytics
Village agriculture is very important in Bangladesh. In emerging nations like our own, agriculture has a significant impact on national GDP. Basically, because of our current circumstances, the monsoons, which are agriculture's primary source of water, are insufficient. The irrigation system is used in agriculture as a solution to this issue. In this technique, the agricultural field will receive water depending on the type of soil. In agriculture, there are two factors to consider: the soil's moisture content and its fertility. There are already a variety of irrigation options available to lessen the demand for rain. An electrical power on/off schedule controls this kind of method. The use of IOT to create a smart irrigation system is covered in this article. Our method uses hydropumps to regulate multiple pumps at once, which saves time and energy. This system will have a significant impact on the national economy if we implement it.
This document presents a preliminary study on developing a Wide Area Protection Monitoring System (WAPMS) that would automatically collect and analyze data from protection devices. The proposed system would gather information through various communication protocols, analyze the data to determine fault types and locations, and generate reports with diagnoses for operators. This would provide operators a comprehensive overview of the power system's behavior during faults to help make better decisions. The system is currently being tested in Colombia and future work involves predictive analytics to identify potential protection device failures.
Policing of the Environment by using an Integrated systemIRJET Journal
The document describes a system for monitoring environmental conditions using sensors and the Internet of Things (IoT). The system uses sensors to measure temperature, humidity, atmospheric pressure, light intensity, and noise levels. The sensor data is sent to an Arduino microcontroller and displayed on an LCD screen. It is also sent via WiFi to the cloud using an ESP8266 module and made available online. The system allows continuous, remote monitoring of environmental parameters to police or assess the environment.
Smart Water Meter System for Detecting Sudden Water LeakageAneekBanerjee4
This article deals with a proposal of a smart water meter for monitoring water consumption and for accidental leakage detection. The hardware part of the smart water meter consists of a mini-computer and a pulse water meter. Application logic is then in the hands of the original software that evaluates water consumption patterns. If a water leak is detected, the smart water meter uses a ball valve to close the inlet. The meter also has a self-learning mode that can recommend set limits within the reference period. A separate application interface is designed for communication between the meter and the user .Various computer simulations were used to test and initiate different water consumption scenarios.
IRJET - Automatic Plant Watering System using NodeMCUIRJET Journal
1) The document describes an automatic plant watering system that uses sensors and NodeMCU to monitor environmental conditions and water plants automatically.
2) The system collects data on temperature, humidity, and soil moisture and sends it to an Android application and the cloud to allow monitoring from anywhere.
3) It aims to make gardening easier by automating watering based on sensor readings so plants get the right amount of water when needed.
IRJET- Integrated Automatic Flood Warning and Alert System using IoTIRJET Journal
The document proposes an integrated automatic flood warning and alert system using IoT that monitors water levels, humidity, temperature and alerts people via SMS, public announcements and a centralized website. The system uses sensors connected to Arduino boards to monitor dams and rivers, and triggers alerts via SMS, sirens and displays if water levels rise above thresholds. All sensor data is logged to a central database accessible via a website to provide information to authorities and the public.
IRJET- Smart Weather Monitoring and Real Time Alert System using IoTIRJET Journal
This document proposes a smart weather monitoring system using IoT that measures various weather parameters like temperature, humidity, wind speed, etc. using sensors. The sensors send real-time data to a web page for access from anywhere. An app also sends alerts about sudden weather changes. While existing systems have limitations like high costs, maintenance needs and delayed warnings, the proposed system is compact, portable, and cheaper due to its solar power and sensor costs. It analyzes sensor data using an API and Raspberry Pi to predict weather accurately. This smart monitoring system could benefit various industries.
iaetsd A novel approach towards automatic water conservation systemIaetsd Iaetsd
This document proposes an automatic water conservation system using LabVIEW software and a data acquisition (DAQ) card. By interfacing the DAQ card to a PC and controlling water flow, water conservation and theft detection can be achieved. Flow meters placed at the water source and consumer end would monitor exact water usage. The DAQ card at the water source would control water tariffs paid via GSM. When implemented, this system could help conserve water resources and prevent theft by monitoring usage.
IRJET- IoT based Flow Analyzing and Alerting SystemIRJET Journal
This document describes an IoT-based system for continuously measuring and analyzing water flow from a dam. The system uses flow sensors placed at multiple points along a river to measure flow rate, velocity, time taken, and distance covered. A Raspberry Pi processes the sensor data and stores it on the cloud. If the flow exceeds a threshold, an alert is sent. The system provides real-time water flow data and analysis in a tabular format to help monitor for flooding. It is a low-cost, efficient method for continuous water flow measurement and alerting.
Intelligent flood disaster warning on the fly: developing IoT-based managemen...journalBEEI
The number of natural disasters occurring yearly is increasing at an alarming rate which has caused a great concern over the well-being of human lives and economy sustenance. The rainfall pattern has also been affected and this has caused immense amount of flood cases in recent times. Flood disasters are damaging to economy and human lives. Yearly, millions of people are affected by floods in Asia alone. This has brought the attention of the government to develop a flood forecasting method to reduce flood casualties. In this article, a flood mitigation method will be evaluated which incorporates a miniaturized flow, water level sensor and pressure gauge. The data from the two sensors are used to predict flood status using a 2-class neural network. Real-time monitoring of the data from the sensor into Thingspeak channel were possible with the use of NodeMCU ESP8266. Furthermore, Microsoft’s Azure Machine Learning (AzureML) has built-in 2-class neural network which was used to predict flood status according to predefine rule. The prediction model has been published as Web services through AzureML service and it enables prediction as new data are available. The experimental result showed that using 3 hidden layers has the highest accuracy of 98.9% and precision of 100% when 2-class neural network
is used.
IRJET- IoT based Flood Detection and Alert SystemIRJET Journal
This document describes an IoT-based flood detection and alert system that uses sensors to detect rising water levels and rainfall. The system includes a float sensor and rain sensor connected to an Arduino controller to monitor water levels and rainfall. If flooding is detected, the system sends alert messages via GSM module to notify authorities. Sensor data is also sent to a webpage using a Wi-Fi module so the flood conditions can be monitored online. The system aims to provide early warnings of flooding to help reduce property damage and save lives.
This document describes a water level monitoring and flood alert system designed to monitor water levels, store that data in a database, and send SMS alerts before floods. The system uses sensors to measure water levels, sends that data to a centralized server via client systems like Raspberry Pi boards. The server stores the water level data in a database and can send SMS alerts to registered phone numbers if water levels rise above a critical threshold. The system was tested over 10 hours and successfully collected, stored, and transmitted water level data, and could send alerts within the needed time frame to warn of potential floods.
IRJET- Cloud based Sewerage Monitoring and Predictive Maintenance using M...IRJET Journal
This document describes a proposed cloud-based system for monitoring sewerage infrastructure and enabling predictive maintenance through machine learning. The system uses an array of sensors attached to manhole covers to monitor factors like gas levels, temperature, pressure and water quality in real-time. This sensor data is transmitted wirelessly to a cloud server. Machine learning algorithms like principal component analysis and decision trees are applied to the sensor data to identify patterns and predict potential issues before they occur, facilitating proactive maintenance of sewer systems. The system aims to provide a low-cost and scalable solution for improving sewer infrastructure management.
Online music portal management system project report.pdfKamal Acharya
The iMMS is a unique application that is synchronizing both user
experience and copyrights while providing services like online music
management, legal downloads, artists’ management. There are several
other applications available in the market that either provides some
specific services or large scale integrated solutions. Our product differs
from the rest in a way that we give more power to the users remaining
within the copyrights circle.
A vernier caliper is a precision instrument used to measure dimensions with high accuracy. It can measure internal and external dimensions, as well as depths.
Here is a detailed description of its parts and how to use it.
Exploring Deep Learning Models for Image Recognition: A Comparative Reviewsipij
Image recognition, which comes under Artificial Intelligence (AI) is a critical aspect of computer vision,
enabling computers or other computing devices to identify and categorize objects within images. Among
numerous fields of life, food processing is an important area, in which image processing plays a vital role,
both for producers and consumers. This study focuses on the binary classification of strawberries, where
images are sorted into one of two categories. We Utilized a dataset of strawberry images for this study; we
aim to determine the effectiveness of different models in identifying whether an image contains
strawberries. This research has practical applications in fields such as agriculture and quality control. We
compared various popular deep learning models, including MobileNetV2, Convolutional Neural Networks
(CNN), and DenseNet121, for binary classification of strawberry images. The accuracy achieved by
MobileNetV2 is 96.7%, CNN is 99.8%, and DenseNet121 is 93.6%. Through rigorous testing and analysis,
our results demonstrate that CNN outperforms the other models in this task. In the future, the deep
learning models can be evaluated on a richer and larger number of images (datasets) for better/improved
results.
Conservation of Taksar through Economic RegenerationPriyankaKarn3
This was our 9th Sem Design Studio Project, introduced as Conservation of Taksar Bazar, Bhojpur, an ancient city famous for Taksar- Making Coins. Taksar Bazaar has a civilization of Newars shifted from Patan, with huge socio-economic and cultural significance having a settlement of about 300 years. But in the present scenario, Taksar Bazar has lost its charm and importance, due to various reasons like, migration, unemployment, shift of economic activities to Bhojpur and many more. The scenario was so pityful that when we went to make inventories, take survey and study the site, the people and the context, we barely found any youth of our age! Many houses were vacant, the earthquake devasted and ruined heritages.
Conservation of those heritages, ancient marvels,a nd history was in dire need, so we proposed the Conservation of Taksar through economic regeneration because the lack of economy was the main reason for the people to leave the settlement and the reason for the overall declination.
An Internet Protocol address (IP address) is a logical numeric address that is assigned to every single computer, printer, switch, router, tablets, smartphones or any other device that is part of a TCP/IP-based network.
Types of IP address-
Dynamic means "constantly changing “ .dynamic IP addresses aren't more powerful, but they can change.
Static means staying the same. Static. Stand. Stable. Yes, static IP addresses don't change.
Most IP addresses assigned today by Internet Service Providers are dynamic IP addresses. It's more cost effective for the ISP and you.
Encontro anual da comunidade Splunk, onde discutimos todas as novidades apresentadas na conferência anual da Spunk, a .conf24 realizada em junho deste ano em Las Vegas.
Neste vídeo, trago os pontos chave do encontro, como:
- AI Assistant para uso junto com a SPL
- SPL2 para uso em Data Pipelines
- Ingest Processor
- Enterprise Security 8.0 (Maior atualização deste seu release)
- Federated Analytics
- Integração com Cisco XDR e Cisto Talos
- E muito mais.
Deixo ainda, alguns links com relatórios e conteúdo interessantes que podem ajudar no esclarecimento dos produtos e funções.
https://www.splunk.com/en_us/campaigns/the-hidden-costs-of-downtime.html
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-leading-observability-practice.pdf
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-modern-security-program.pdf
Nosso grupo oficial da Splunk:
https://usergroups.splunk.com/sao-paulo-splunk-user-group/
Unblocking The Main Thread - Solving ANRs and Frozen FramesSinan KOZAK
In the realm of Android development, the main thread is our stage, but too often, it becomes a battleground where performance issues arise, leading to ANRS, frozen frames, and sluggish Uls. As we strive for excellence in user experience, understanding and optimizing the main thread becomes essential to prevent these common perforrmance bottlenecks. We have strategies and best practices for keeping the main thread uncluttered. We'll examine the root causes of performance issues and techniques for monitoring and improving main thread health as wel as app performance. In this talk, participants will walk away with practical knowledge on enhancing app performance by mastering the main thread. We'll share proven approaches to eliminate real-life ANRS and frozen frames to build apps that deliver butter smooth experience.
1. SOCIAL BENEFICIAL PROJECT: SMART DAM
[Team zombies]
Team Details
Participant
Name
CT /DT
Number
Role (Team
Leader / Member)
Bachelors Discipline
Expected Year
of Passing
Gender
KRISHNENDU
DATTA
CT20162
048187
Team Leader Electrical Engineering 2020 M
SUBHENDU
GHORAI
CT20162
050714
Team Member Mechanical Engineering 2020 M
SUTANU
MONDAL
CT20162
050739
Team Member Mechanical Engineering 2020
M
SANJIB
BETAL
CT20162
050735
Team Member
Computer Science and
Engineering
2020 M
Page 1
2. SOCIAL
1. Problem Statement
After analyzing various reports on dam incidents, dam failure, flood occurrence, dam
alerts and irrigation issues due to drought we identified a high-priority call for real time
dam water level monitoring and prior alerting and control system which ensures the
public safety and smart utilization of reservoir water.
2. Use Case Overview
The proposal is titled “SMART DAM WATER MONITORING AND
CONTROLLING” and the objective of the project is to make the existing system smart
by adding connectivity, Artificial intelligence (AI), IOT, cloud and dashboard.
3. Use Case Description
A dam is nothing but a barrier constructed to hold back water and raise its level, forming
a reservoir used to generate electricity or as water supply for various activities such as in
irrigation.
In present scenario most dams are manually monitored and data are sent via traditional
modes, manual observation and transmission results in a time loss between the data
observed in dam site and decision taking level. This sometimes causes loss of worthwhile
real time data.
During floods the dam is subjected to heavy volume of water, in such alarming situation
manual operation becomes very risky and any human error can put the lives of thousands
of people in danger.
One of the major problems is that opening and closing of floodgate is manually operated
and there is no intelligent estimation of required volume of water to be released.
Water being an important resource for living, it needs to be conserved and preserved.
Therefore its distribution and usage is of utmost consideration.
Page 2
3. The three major stakeholders involved in this system are dam authorities, researchers
and the common people. These are the concerned people considered in our solution.
3.1 Current system
Current system has no inclination towards the real time data available to dam authorities,
common people and the researchers. There is no proper monitoring and controlling
procedures. Let’s consider the issues of the three main stakeholders as discussed in the
previous section.
DAM AUTHORITIES
1. Dam monitoring is done through traditional surveillance techniques
and becomes excessively risky during bad weather.
2. Doesn’t have real-time view of different parameters therefore there
is a time lag in providing the data observed in dam site to the
decision makers.
3. During both flood and draught situations, decision to open or close
the water gate is a censorious action that needs to be undertaken as
soon as possible, late decision will not only cause flood
downstream but will also damage the structure.
Researchers
1. Researchers want observed data to be readily available for research
purpose as well as monitor the authentic time changes in various
parameters.
2. Dam parameters’ data collection is mostly unavailable in present
systems.
Common people/Farmers
1. Unenlightened about the parameters like rainfall, Dam water level
and gate status.
2. Uncertainty about water for crops, sudden rise of backwater and
sometimes flood.
Page 3
4. 3.2 Proposed solution
Proposal is to make the complete system smart. Considering the issues listed fixing them
the best way possible is considered. In short following is done for each of the
stakeholders.
DAM AUTHORITIES
1. A dashboard is provided with all vital parameters sensed from
different sensors and analytics of these parameters along with
weather forecasted from various sources.
2. Real time monitoring with the aid of IOT and AI removes the time
lag between data observation and decision making.
3. Flood Gate opening and closing time is estimated with the help of
Intelligent Decision support system (IDSS) based on hydrological
parameters like water level, rain fall and gate position.
Researchers
1. With the help of cloud and IOT the various dam parameters are
readily available for research purpose.
2. Researchers can monitor the authentic time changes in various
parameters.
Common people/Farmers
1. Installation of water alarm systems in the downstream region of
dams to warn the authorities and to alert the population for ensuring
the evacuation of the flood prone area.
The water alarm system consists of sirens that can be activated
directly with the aid of IOT.
2. Hydrological and operational data are used to estimate opening and
closing of water gate that will ensure optimum supply of water.
4 Architecture
As discussed, the solution to our problem area is considered at three sections, i.e.,
dam authority, researcher and the common people/farmers. This way we create a synergy
between the stakeholders of the system.
Page 4
5. The architecture of the proposed solution is as per the figure given bellow;
Above architecture describes the system. The various components involved in the
system are:
• Ultrasonic Sensor
• Raspberry Pi
• Wi-Fi module
• Alarm system (siren)
• Dashboard
Integrate ultrasonic sensor and raspberry pi to collect the dam parameter (specifically
water level of the reservoir). This data along with the weather forecast from different
sources (like AccuWeather and meteorological department) are made accessible by
pushing the data to a cloud system. These two data (water level and weather forecast)
constitutes the hydrological data. Hydrological data along with operational data (data
based on experience and previous action) serve as an input to Intelligent Decision Support
System (IDSS). IDSS is a combination of DSS and artificial intelligence (AI). The
Page 5
Weather
forecast from
various
sources
Raspberry pi
Ultrasonic sensors
Dashboard and
central control unit
Alarm system
6. intelligent decision support model is based on Neural Network (NN), a mathematical
computational model that imitates the biological neuron capability. The theoretical
foundation and logic of NN has been discussed in [3] and [4]. The model consists of three
major stages:
o Data extraction
o Water level forecasting
o Water release decision modules
Page 6
Reservoir
Hydrological
Data
Operational
Data
Data MiningData Mining
Water Level
Forecasting
Model
Water Release
Decision Model
Water Release
Decision Model
Lock-
Gate
Opening
Lock-
Gate
Opening
Rainfall, Water
level
Experience and
Previous Action
7. Backpropagation algorithm will be used for learning and decision making of neural
network. Backpropagation algorithm looks for the minimum value of the error function in
weight space using a technique called the delta rule or gradient descent. The weights that
minimize the error function are then considered to be a solution to the learning problem
[9].
Backpropagation Algorithm:
initialize network weights (often small random values)
do
for each training example named ex
prediction = neural-net-output(network, ex) // forward pass
actual = teacher-output(ex)
compute error (prediction - actual) at the output units
compute {displaystyle Delta w_{h}} for all weights from hidden layer to output
layer // backward pass
compute {displaystyle Delta w_{i}} for all weights from input layer to hidden layer
// backward pass continued
update network weights // input layer not modified by error estimate
until all examples classified correctly or another stopping criterion satisfied
return the network
Page 7
8. The result based on NN model is sent to cloud and put to use under two different
situations.
Normal or regular situation:
The decision and time estimation of opening and closing the water gate is
provided to the dam authority via dashboard linked to cloud system. These data
will help the dam water gate operator to take a rational decision.
Critical or alarming situation:
A raspberry pi linked to the cloud system will trigger the alarm system (siren)
connected to it and thus informing the population residing in the flood prone area
about the emergency situation so that the region can be evacuated as soon as
possible.
5 Productization
The main purpose of our system is to assist the concerned dam authority with real-time
dam parameter and analytics using intelligent decision support system (IDSS) based on
Neural Network which has an accuracy rate of 96%. In practice, the water gate opening is
based on some operating rules; these rules do not consider the dynamic nature of
hydrology system. Therefore it is vital to use non-structural approach such as forecasting
to cope up with the event frequency and trigger alert to the authority when the situation is
severe. The proposed system is very flexible and easy to install. The system is divided
into six modules:
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CloudCloud
Flood
alert
Flood
alert
Raspberry piRaspberry pi
Alert messages for flood
using Buzzer
9. • Readings from sensors to raspberry pi.
• Data from Raspberry pi to cloud system.
• Weather forecasts from different sources to the cloud system.
• Processing of these data along with operational data (experience and
previous action) using Intelligent Decision Support System (IDSS).
• Analytics from IDSS to Dashboard via cloud system.
• Alarm system in case of emergency.
The above modules are integrated to form the smart system.
6 Tools and Environment
The following tools and environment will be used at various stages of our proposed
system.
6.1 Simulation & Testing
MATLAB Will be used for simulating the system. Test data for simulation will be
generated using MarkSim DSSAT weather file generator [5].
6.2 Cloud
We will be using ThingSpeak, an open-source Internet of Things (IOT)
application and API to store and retrieve data from things using the HTTP
protocol over the Internet or via a Local Area Network.
6.3 Physical
The following hardware, sensor and software component will be used in our
proposed system:
Raspberry Pi: It is a small computer which can be programmed. In our
project we have used Raspberry Pi 3 model B. It is the latest product in the
Raspberry Pi 3 range. Specification has been mention in [6].
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10. Ultrasonic Sensor: In our project we have used ultrasonic sensor (HC-
SR04) to determine the water level. It uses sonar to determine the water
level. Specification has been mention in [7].
PyCharm: It is an integrated development environment (IDE) used
in computer programming, specifically for the Python language. We used
this platform to implement the Neural Network model.
6.4 Interface
Dashboard will be used for human interface. Dashboard can be easily created
using Bootstrap, Mysql and PHP.
7 References
[1] https://nptel.ac.in/courses/IIT-MADRAS/Hydraulics/pdfs/Unit41/41_2.pdf
[2] https://www.damsafety.in/ecm-includes/PDFs/DRIP_II_Presentation/Dam%20Safety
%20in%20India.pdf
[3] https://cdn.preterhuman.net/texts/science_and_technology/artificial_intelligence/Neur
al%20Networks%20-%20A%20Comprehensive%20Foundation%20-%20Simon
%20Haykin.pdf
[4] https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html
[5] http://gismap.ciat.cgiar.org/MarkSimGCM/
[6] https://www.raspberrypi.org/products/raspberry-pi-3-model-b/
[7] https://www.tutorialspoint.com/arduino/arduino_ultrasonic_sensor.htm
[8] https://en.wikipedia.org/wiki/Backpropagation#/media/File:ArtificialNeuronModel_e
nglish.png
[9] https://www.edureka.co/blog/backpropagation/
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