VISVESVARAYA TECHNOLOGICAL UNIVERSITY

JnanaSangama, Machhe, Belgaum, Karnataka 590018

Project Report On Development of Under Water ROV for Drowned Human Body Detection Submitted in partial fulfillment of the requirements for the award of degree Bachelor Of Engineering In Electronics & Communication Engineering

Submitted By Prasanna kumar D (1NH15EC724) Dilip Kumar R (1NH16EC401) Mohan Kumar V (1NH16EC413)

Under the guidance of Mr.Naveen H Assistant Professor, ECE Dept, NHCE

Department of Electronics and Communication

CERTIFICATE

This is to certify that the project work entitled “Development of Under Water ROV for Drowned Human Body Detection” is a bonifide work carried out by student PRASANNA KUMAR D (1NH15EC724), DILIP KUMAR R (1NH16EC401) & MOHAN KUMAR V (1NH16EC413) submitted in partial fulfillment for the award of Bachelor of Engineering degree in VIII semester of the Visvesvaraya Technological University, Belagavi during the academic year 2018-19. It is certified that all the corrections and suggestions indicated for Internal Assessment have been incorporated in the report deposited in the Department library.

GUIDE HOD PRINCIPAL

Mr.NAVEEN.H Dr. SANJEEV SHARMA Dr. MANJUNATHA

EXAMINER’S SIGNATURE

1. ………………………..

2. ………………………..

ACKNOWLEDGMENT The satisfaction that accompanies the successful completion of task would be incomplete without mention of the people who made it possible, whose constant guidance and encouragement crown all efforts with success. We express my sincere gratitude to Mr. Naveen H, Assistant Professor in Department of Electronics and Communication Engineering, New Horizon College of Engineering, for providing guidance and encouragement.

Department of Electronics and Communication for his constant support and guidance without which this project would not have seen the light of the day. Gracious gratitude to all the faculty of the department of ECE for their valuable advice and encouragement.

PRASANNA KUMAR D DILIP KUMAR R MOHAN KUMAR

CONTENTS

1. INTRODUCTION 2. MOTIVATION 3. BLOCK DIAGRAM 4. ALGORITHM 5. FLOWCHART 6. HARDWARE AND SOFTWARE SPECIFICATION 7. RESULTS AND FUTURE SCOPE

INTRODUCTION A remotely operated underwater vehicle(ROV) is a tethered underwater mobile device. ROVs are unoccupied , highly maneuverable and operated by a crew either aboard a vessel, floating platform or on proximate land. They are linked to a host ship by a neutrally buoyant tether or when in use under rough conditions or in deep water along with TMS.

ROV DEPLOYED BY INDIAN NAVY TO EXPLORE THE COAST OF INDIAN OCEAN WORLD’S FIRST EVER ROV PEGASUS(FRANCE)

Dimitri Rebikoff (1921-1997) and Ada Rebikoff (1913-2011) were amongst the great pioneers of diving, and underwater photography in particular.Dimitri Rebikoff developed the first underwater electronic flash, stereophoto and film cameras, the world´s first underwater scooter, the Torpille, the Pegasus and the first remotely operated vehicle (ROV). His contribution to the development of underwater photography was ground-braking.

NATO SUBMARINE RESCUE SYSTEM

The NATO Submarine Rescue System (NSRS) is a tri-national project to develop an international submarine rescue system. The system provides a rescue capability primarily to the partner nations of France, Norway and the UK but also to NATOand allied nations and to any submarine equipped with a suitable mating surface around its hatches.

The NSRS entered service in 2008, replacing the UK's previous rescue system, the LR5. The complete system is fully air transportable in a variety of suitable aircraft (C17/C5/An124/A400M). It is capable of launch and recovery in a significant wave height of up to 5 meter(sea state 6) and can reach any distressed submarine (DISSUB) in 72-96 hours from the alert, dependent upon location. It has limited capability in ice-covered seas. On receipt of a 'SUBSUNK' alert that a submarine is in difficulties, the submarine operator will initiate the NSRS call-out procedure. The intervention system, which is centred upon an off-the-shelf remotely operated vehicle(ROV) will mobilise to the scene about 24 hours in advance of the full rescue system. Once on-site it will locate the distressed submarine (DISSUB), establish communications, conduct damage assessment and prepare the DISSUB for rescue operations.

. DISSUB(DISTRESSED SUBMARINE)

This is a brief introduction of the ROVs of the past and their types varies based on the requirement(application)for which it is used for instance -identification of drowned humans,bodies or it can be used to spot another submarine which was not locatable due to natural disaster

Classification of ROV Submersible ROVs are normally classified into categories based on their size, weight, ability or power. Some common ratings are:

Micro - typically Micro-class ROVs are very small in size and weight. Today's Micro-Class ROVs can weigh less than 3 kg. These ROVs are used as an alternative to a diver, specifically in places where a diver might not be able to physically enter such as a sewer, pipeline or small cavity.

Mini - typically Mini-Class ROVs weigh in around 15 kg. Mini-Class ROVs are also used as a diver alternative. One person may be able to transport the complete ROV system out with them on a small boat, deploy it and complete the job without outside help. Some Micro and Mini classes are referred to as "eyeball"-class to differentiate them from ROVs that may be able to perform intervention tasks. General - typically less than 5 HP (propulsion); occasionally small three finger manipulators grippers have been installed, such as on the very early RCV 225. These ROVs may be able to carry a sonar unit and are usually used on light

TYPES OF ROVs

Open or Box Frame ROVs: This is the most familiar of the ROV configurations -consisting of an open frame where all the operational sensors, thrusters, and mechanical components are enclosed. These are useful for free- swimming in light currents (less than 4 knots based upon manufacturer specifications). These are not suitable for towed applications due to their very poor hydrodynamic design. Most Work-Class and Heavy Work-Class ROVs are based upon this configuration.

Torpedo Shaped ROVs :This is a common configuration for data gathering or inspection class ROVs. The torpedo shape offers low hydrodynamic resistance, but comes with significant control limitations. The torpedo shape requires high speed (which is why this shape is used for military munitions) to remain positionally and attitudinally stable, but this type is highly vulnerable at high speed. At slow speeds (0-4 knots) suffers from numerous instabilities, such as tether induced roll and pitch, current induced roll, pitch, and yaw. It has limited control surfaces at the tail or stern, which easily cause over compensation instabilities. These are frequently referred to as "Tow Fish", since they are more often used as a towed ROV.Vehicles like the Perry Tritech Voyager (right) are very capable inspection systems using the state-of- the-art in fiber optic telemetry and control systems. ROVs like the Deep Sea Systems International MaxROVER offer increased power andmoderate work capabilities to depths of 9,842 feet (3,000 meters) at a fraction of the cost of electro-hydraulic systems.

Electric vehicles have gained popularity with the military and science markets due primarily to their quiet operation. In addition, the work requirements for military and science are, in most cases, not as complex when compared to ROVs used for oil and gas operations. The future should see a dramatic increase in the work capability of such all-electric systems.

Literature survey:A particle filter (PF)-based robust navigation with fault diagnosis (FD) is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switching-mode hidden Markov model by Roger Skjetne .AnActuator Failure Tolerant Control Scheme for an Underwater Remotely Operated Vehicle by Maria LetiziaCorradini, In the paper an actuator fault–tolerant control scheme, composed of the usual modules performing detection, isolation, accommodation, designed for a class of nonlinear systems, and then applied toan underwater remotely operated vehicle (ROV) used for inspection purposes

Tracking objects in underwater multibeam sonar images by Tina Ruiz, in this work an obstacle detection and tracking algorithm applied to multibeamforwardlookingsonar images. It is used by an obstacle avoidance system to be fitted in a remotely operated underwater vehicle (ROV). The real -time data flow from the sonar output is represented as an image and pre-processed (smoothing filters, region- based segmentation and feature extraction) by the system to identify possible obstacles

A total 3, 90,884 accidental deaths were reported in the country during the year 2011. A total of 6, 94,390 cases of Un-Natural Accidents have caused 3, 67,194deaths and rendered 5, 06,348 people injured during 2011.The major un-natural causes of accidental deaths were Road Accidents(37.3%),

Railway Accidents and Rail- Road Accidents (7.6%), Poisoning (8.0%),Drowning (8.1%), Sudden Deaths (7.3%) and Fire Accidents (6.7%).29708 deaths have occurred during the year 2011 due to drowning (boat)

ROV Implementation

Our main device consists of three separate sectors: 1) Physical structure 2) Top controller and Bottom controller 3) Software Implementation A. Physical Structure Frame Design and Construction The purpose of the frame is to support the water-proof enclosure, the thruster motors, and any trimming weights. The principle design goal for the frame, taking into account thruster and enclosure positioning and support, was to ensure there was maximum water flow through the open frame, to therefore minimize drag. B. Top Controller and Bottom Controller Top Controller The primary purpose of the top controller is to act as the operator control interface. From the operator’s point-of-view, they need to be able to control the position of the ROV in the water on any one of four axes, as easily as possible, and receive timely feedback from the ROV of its position and the nature of the environment it is in.

Efficient feature extraction, encoding and classification for action recognition Local video features provide state-of-the-art performancefor action recognition. While the accuracy of action recognition has been continuously improved over the recent years, the low speed of feature extraction and subsequent recognition prevents current methods from scaling up to real-size problems. We address this issue and first develop highly efficient video features using motion information in video compression. We next explore feature encoding by Fisher vectors and demonstrate accurate action recognition using fast linear classifiers. Our method improves the speed of video feature extraction, feature encoding and action classification by two orders of magnitude at the cost of minor reduction in recognition accuracy. We validate our approach and compare it to the state of the art on four recent action recognition datasets.

The amount of video has increased dramatically over recent years and continues to grow. Striking indications of this development include 6000 years of video uploaded to YouTube yearlyand millions of surveillance cameras installed only in the UK. According to Cisco, video is expected to dominate Internet traffic by 91% in 2014.The access to information in such gigantic quantities of video data requires accurate and efficient methods for automatic video analysis. Much work has been recently devoted to automatic video understanding and recognition of human actions in particular [16, 8, 22, 31, 32, 35]. While the

recognition accuracy has been continuously improved, current methods remain limited to relatively small datasets due to the low speed of video processing, often ranging in the order of 1-2 frames per second. This stands in a sharp contrast with the needs of large-scale video indexing and retrieval in modern video archives. Fast video recognition is also required by client applications.

The main goal of this work is efficient action recognition. We follow the common bag-of-features action recognition pipeline and explore the speed and memory trade- offs of its main steps, namely, feature extraction ,feature encoding and classification. Given their success for action recognition, we represent video using motion-based HOF and MBH local descriptors. Motion estimation at dense grid, however, is a time-consuming process that limits the speed of feature extraction. In this work we avoid motion estimation and design fast descriptors using motion information from video compression. In contrast to the dense optical flow (OF), video compression provides sparse motion vectors only (we call it MPEG flow). As one contribution of this paper, we show that the use of sparse MPEG flow instead of the dense OF improves the speed of feature extraction by two orders of magnitude and implies only minor reduction in classification performance.

Efficient video features

Dense Trajectory (DT) features together with MBH and HOF descriptors achieve state-of-the-art accuracy in action recognition at the cost of high computational requirements. The analysis in indicates that most of the running time (61%) is spent on the computation of optical flow, while the second most expensive operation (36%) is aggregation of dense flow measurements into histogram descriptors (discarding the ”save features to disk” part). In this paper we alleviate the expense of both of these steps by (i) reusing motion estimates available from video compression and (ii) constructing descriptors from very sparse motion measurements. In this section we first analyze the quality of motion vectors available in compressed video representations and then describe our efficient video descriptor.

Motion fields from video compression

Consequent video frames are highly redundant with most of the changes between frames typically originating from the object or camera motion. As the storage of sparse motion vectors is much more efficient compared the storage of pixel values, video compression schemes heavily rely on motion estimation and encode coarse motion information in compressed video representations such as MPEG. This motion

field can be accessed at the time of video decompression without additional costMotion estimation by video encoders is designed to optimize video compression size and may not necessarily correspond to the true motion in the video. To verify the quality of the motion field obtained from video compression (here called MPEG flow), we compare it with the ground truth flow as well as with the output of optical flow methods by Lucas and Kanade andFarneback . We choose these two methods since they are deployed in existing implementations of local motion descriptors and which we use in this work for comparison.

Descriptor encoding

The purpose of descriptor encoding is to transform collections of local image or video descriptors fxi : : : xNginto fixed-size vector representations. In this paper we investigate three different descriptor encoding schemes and propose their computational improvements as described below.

Histogram encoding

Histogram encoding is a common method for representing video by local descriptors. First, for each descriptor type (HOG, HOF, MBHx, MBHy) a vocabulary of K visual words is constructed using K-means. Then each descriptoris assigned to one of the visual words and the visualword indices are accumulated in a histogram. We follow and use “space-time pyramid” which allows to capture the rough spatial and temporal layout of action elements. We split videos into six spatio-temporal grids(x _ y _ t: 1x1x1, 2x2x1, 1x3x1, 1x1x2, 2x2x2, 1x3x2, a total of 24 cells). In total we have C = 96 channels = 4 descriptor types _ 24 cells, that is one channel per a pair of descriptor type and grid cell. Each cell accumulates its own histogram which is then l1-normalized, thus the total histogram representation is of size C _ K. We also employ space-time pyramids for the Fisher vector and VLAD encoding methods described respectively. For visual word assignment we experimented with using brute-force nearest neighbours and with using the kd-trees from the FLANN library . The motivation for using kd-trees is the significant improvement in processing speed over the brute-force algorithm ). The main parameters for the kd-trees method are the number of trees and the number of tests made during the descent over trees.

SCOPE/OBJECTIVE OF THE PROJECT: The scope of the project is to design and construct an underwater, remotely-operated vehicle (ROV), fitted with a 4-axis positioning system, a video transmission system, and a 2-axis (pitch and roll) control system to assist imaging and positional stability. The many varied aspects of this project present quite a number of challenges and learning objectives: * Design and construction of an electronic operator interface * Design and construction of an electronic DC motor drive system * Design and construction of a water-proof enclosure mounted on frame * Research, design and implementation of a level measurement system *Research, design and implementation of a self-stabilizing control system This ROV project ultimately represents an overlap of interests: control systems, underwater exploration, and electronics.

The project includes the design and development of the PVC frame and water-proof enclosure, design and development of an ARM Cortex-M3 microcontroller-based electronic circuit for the operator interface, and another ARM Cortex-M3 microcontroller-based electronic circuit that controls the seven DC motors fitted with propellers.

METHODOLOGY:We propose a thorough water imaging equipment that can scan the water front in defined areas and generates images of the water bed indicating the location of drowned bodies. The system would have a display as well a local coordinate system to show the presence of human bodies and their positions. The system will be based on sonar imaging technology that can beam sonar signals which scans the water front in defined areas and automatically generates the signals.

It consists of Top Controller Board and Bottom Controller Board

TOP CONTROLLER BOARD:

Top controller consists of joystick,display,buzzer,LEDs and power supply. Joystick is used to control the movement of ROV. It also can manipulate many operations of the vehicle. Buzzer is an indicator as well as LEDs. LEDs also lightup the vehicle under water. Power supply maintains the constant supply of energy. Display available for the constant track of the vehicle in case of any calamities.

BOTTOM CONTROLLER BOARD:

It is consisting of vertical and horizontal thrusters,data logging system and a video camera. Data logging system stores bits of data and sends it to the bottom board when required. Vertical thrusters are used for the vertical motion(UP and DOWN),Horizontal thrusters are used for the horizontal motion(LEFT and RIGHT).

PC is another option for the complete tracking of the vehicle and operate it carefully Both boards are connected through Ethernet cable(10m)

PRIMARY AND SECONDARY GOALS:

Primary Goal 1: Build an underwater vehicle fitted with thrusters for horizontal and vertical positioning. Primary Goal 2: Build microcontroller-based electronic circuitry for operating the thrusters Primary Goal 3: Build remote operator providing basic interface to the vehicle. Primary Goal 4: Test the vehicle and identify its dynamics characteristics. Primary Goal 5: Design and implement an automatic control system for pitch and roll of the vehicle. Secondary Goal 1: Test robustness of the control system. Secondary Goal 2: Consider (if needed) any improvements to the control system Secondary Goal 3: Install a video camera and lights on the vehicle.

Application of the project :

*. Industry *. Disaster Management *. Societal * Education / Academic * Can be used to detect leakage in underwater gas pipelines. * Can be used to detect drowned dead bodies. * Can be used in fisheries. * The oil and gas industry uses AUVs to make detailed maps of the seafloor. * A typical military mission for an AUV is to map an area to determine if there are any mines, or to monitor a protected area for new unidentified objects

Applications of ROV explained in detail

*ROVs in Military Application

ROVs have been used by several navies for decades, primarily for mine hunting and mine breaking. AN/SLQ-48 Mine Neutralization Vehicle In October 2008 the U.S. Navy began to replace its manned rescue systems, based on the MYSTIC and support craft, with a modular system, the SRDRS, based on a tethered, unmanned ROV called a pressurized rescue module (PRM). This followed years of tests and exercises with submarines from the fleets of several nations. The US NAVY also uses an ROV called AN/SLQ-48 Mine Neutralization Vehicle (MNV) for mine warfare. It can go 1000 yards away from the ship due to a connecting cable, and can reach 2000 feet deep. The mission packages available for the MNV are known as MP1, MP2, and MP3.

The MP1 is a cable cutter to surface the moored mine for recovery exploitation or Explosive Ordnance Disposal (EOD). The MP2 is a bomblet of 75 lb polymer bond explosion PBXN-103 high explosive for neutralizing bottom/ground mines.

*ROVs in Broadcast purposes As cameras and sensors have evolved and vehicles have become more agile and simple-to-pilot ROVs have become popular particularly with documentary filmmakers due to their ability to access deep, dangerous, and confined areas unattainable by divers. There is no limit to how long an ROV can be submerged and capturing footage which allows for previously unseen perspectives to be gained. ROVs have been used in the filming of several documentaries including Nat Geo's Shark Men and The Dark Secrets of the Lusitania and the BBC Wildlife Special Spy in the Huddle

*ROVs in Astronomical field

ROVs have been used by several navies for decades, primarily for mine hunting and mine breaking. AN/SLQ-48 Mine Neutralization Vehicle In October 2008 the U.S. Navy began to replace its manned rescue systems, based on the DSRV and support craft, with a modular system, the SRDRS, based on a tethered, unmanned ROV called a pressurized rescue module (PRM). This followed years of tests and exercises with submarines from the fleets of several nations. The US NAVY also uses an ROV called AN/SLQ-48 Mine Neutralization Vehicle (MNV) for mine warfare. It can go 1000 yards away from the ship due to a connecting cable, and can reach 2000 feet deep. The mission packages available for the MNV are known as MP1, MP2, and MP3.

The MP1 is a cable cutter to surface the moored mine for recovery exploitation or Explosive Ordnance Disposal (EOD). The MP2 is a bomblet of 75 lb PBXN-103 high explosive for neutralizing bottom/ground mine

*ROVs in Educational Outreach

The Operated Underwater Vehicle (ROV) educational program is an educational tool and kit that allows elementary, middle, and high-school students to construct a simple, remotely operated underwater vehicle, from polyvinyl chloride (PVC) pipe and other readily made materials. The SeaPerch program teaches students basic skills in ship and submarine design and encourages students to explore naval architecture and marine and ocean engineering concepts. SeaPerch is sponsored by the Office of Naval Research, as part of the National Naval Responsibility for Naval Engineering (NNRNE), and the program is managed by the Society of Naval Architects and Marine Engineers Another innovative use of ROV technology was during the Mardi Gras Shipwreck Project. The "Mardi Gras Shipwreck" sank some 200 years ago about 35 miles off the coast of Louisiana in the Gulf of Mexico in 4,000 feet (1220 meters) of water. The shipwreck, whose real identity remains a mystery, lay forgotten at the bottom of the sea until it was discovered in 2002 by an oilfield inspection crew working for the Okeanos Gas Gathering Company (OGGC). In May 2007, an expedition, led by Texas A&M University and funded by OGGC under an agreement with the Minerals Management Service (now BOEM), was launched to undertake the deepest scientific archaeological excavation ever attempted at that time to study the site on the seafloor and recover artifacts for eventual public display in the Louisiana State Museum. As part of the educational outreach Nautilus Productions in partnership with BOEM, Texas A&M University, the Florida Public Archaeology Network and Veolia Environmental produced a one-hour HD documentary about the project, short videos for public viewing and provided video updates during the expedition. Video footage from the ROV was an integral part of this outreach and used extensively in the Mystery Mardi Gras Shipwreck documentary.

COMPONENT SPECIFICATIONS *PVC PIPES *DC MOTORS *RECHARGEABLE BATTERIES *CAT5 CABLE *SPONGES *JOYSTICK CONTROL *VIDEO CAMERA *ULTRASONIC SENSOR *LED LIGHTINGS

PVC PIPES: PVC Pipes are used to form the external structure of ROV. It is inserted with smaller ironrods so as to bring in the equilibrium of ROV under the water and enhance smooth motion.It can be used as per the design and measurement of rov.

DC MOTOR:DC motors convert the electrical energy into mechanical energy There are 4 DC BRUSHLESS MOTORS used in our design for motion of ROV. *UPWARD AND DOWNWARD

*LEFT AND RIGHT MOVEMENT1

DC Motor is used for generating higher torque for motion of rov. A DC motor is any of a class of rotary electrical machines that converts direct current electrical energy into mechanical energy. The most common types rely on the forces produced by magnetic fields. Nearly all types of DC motors have some internal mechanism, either electromechanical or electronic, to periodically change the direction of current flow in part of the motor. DC motors were the first form of motor widely used, as they could be powered from existing direct-current lighting power distribution systems. A DC motor's speed can be controlled over a wide range, using either a variable supply voltage or by changing the strength of current in its field windings. Small DC motors are used in tools, toys, and appliances. The universal motor can operate on direct current but is a lightweight brushed motor used for portable powertools and appliances. Larger DC motors are currently used in propulsion of electric vehicles, elevator and hoists, and in drives for steel rolling mills. The advent of power electronics has made replacement of DC motors withACMotors possible in many

RECHARGEABLE BATTERY:We use a 12V battery for constant supply of power since its long service life. Rechargable,recycling and no memory effect. Sealed maintance free with a long service life.

CAT5 CABLE:Category 5 cable is used for efficient performance of upto 100 MBps.It also prevents voltage loss during transmission of the signal.

Category 5 cable, commonly referred to as Cat 5, is twisted pair cable for computer network. Since 2001, the variant commonly in use is the Category 5especification (Cat 5e). The cable standard providesperformance of up to 100 MHz and is suitable for most varieties of Ethernet over twisted pair up to 1000 BASE-T(Gigabit Ethernet). Cat 5 is also used to carry other signals such as telephony and video.

This cable is commonly connected using punch down blocks an connectors Most Category 5 cables are unshielded, relying on the balanced line twisted pair design and signalling for noise rejection. The specification for category 5 cable was defined in ANSI/TIA/EIA-568-A, with clarification in TSB-95. These documents specify performance characteristics and test requirements for frequencies up to 100 MHz

The cable is available in both stranded and solid conductor forms. The stranded form is more flexible and withstands more bending without breaking. Patch cables are stranded. Permanent wiring used structured cabling is solid-core. The category and type of cable can be identified by the printing on the jacket.

LED A light-emitting diode (LED) is a semiconductor light source that emits light when current flows through it. Electrons in the semiconductor recombine with electron holes, releasing energy in the form of photons. This effect is called electroluminescence. The colour of the light (corresponding to the energy of the photons) is determined by the energy required for electrons to cross the band gap of the semiconductor. White light is obtained by using multiple semiconductors or a layer of light-emitting phosphor on the semiconductor device .Appearing as practical electronic components in 1962, the earliest LEDs emitted low-intensity infrared light. Infrared LEDs are used in remote-control circuits, such as those used with a wide variety of consumer electronics. The first visible-light LEDs were of low intensity and limited to red.

VIDEO CAMERA:Special camera is used for capturing real time video under water.This video can be further betteredby using segmentation and feature extration process.

SPONGES: Sponges are used on top part of the rov helps it to float and balance the equilibrium

ULTRASONIC SENSOR: Underwater sensor is used mainly for determing the distance of the object from the rov.

This helps us to avoid any collusions and enhance proper movement.

Working principle is based on SONAR Single waterproof transducer of JSN-SR04T had been used to determine the distance of an object based on operation of the classic pulse echo detection method underwater. In this experiment, the system was tested by placing the housing which consisted of Arduino UNO, Bluetooth module of HC-06, ultrasonic sensor and LEDs at the top of the box and the transducer was immersed in the water. The system which had been tested for detection in vertical form was found to be capable of reporting through the use of coloured LEDs as indicator to the relative proximity of object distance underwater form the sensor. As a conclusion, the system can detect the presence of an object underwater within the range of ultrasonic sensor and display the measured distance onto the mobile phone and the real time graph had been successfully generated.

Sound navigation ranging is a technique that uses sound propagation(usually underwater,as in submarine navigation)to navigate,communicate with or detect objects on or under the surface of the water,such as vessels.

Sonar may be used as a means of acoustic location and of measurement of the echo characteristics of “targets” in the water. Sonar may also be used in air for robot navigation,and SODAR(an upward-looking in-air sonar) is used for atmospheric investigations

ACTIVE SONAR : Active sonar uses a sound transmitter and a receiver. When the two are in the same place it is monostatic operation. When the transmitter and receiver are separated it is bistatic operation. When more transmitters (or more receivers) are used, again spatially separated, it is multistatic operation. Most sonars are used monostatically with the same array often being used for transmission and reception. Active sonobuoy fields may be operated multistatically. Active sonar creates a pulse of sound, often called a "ping", and then listens for reflections (echo) of the pulse. This pulse of sound is generally created electronically using a sonar projector consisting of a signal generator, power amplifier and electro-acoustic transducer/array. A beamformer is usually employed to concentrate the acoustic power into a beam, which may be swept to cover the required search angles. Generally, the electro-acoustic transducers are of the Tonpilz type and their design may be optimised to achieve maximum efficiency over the widest bandwidth, in order to optimise performance of the overall system. Occasionally, the acoustic pulse may be created by other means, e.g. chemically using explosives, airguns or plasma sound sources.

PASSIVE SONAR: Passive sonar listens without transmitting. It is often employed in military settings, although it is also used in science applications, e.g., detecting fish for presence/absence studies in various aquatic environments - see also passive acoustics and passive radar. In the very broadest usage, this term can encompass virtually any analytical technique involving remotely generated sound, though it is usually restricted to techniques applied in an aquatic environment.

Identifying sound sources Passive sonar has a wide variety of techniques for identifying the source of a detected sound. For example, U.S. vessels usually operate 60 Hz alternating current power systems. If transformers or generators are mounted without proper vibration insulation from the hull or become flooded, the 60 Hz sound from the windings can be emitted from the submarine or ship. This can help to identify its nationality, as all European submarines and nearly every other nation's submarine have 50 Hz power systems. Intermittent sound sources (such as a wrench being dropped), called "transients," may also be detectable to passive sonar. Until fairly recently, an experienced, trained operator identified signals, but now computers may do this. Passive sonar systems may have large sonic databases, but the sonar operator usually finally classifies the signals manually. A computer system frequently uses these databases to identify classes of ships, actions (i.e. the speed of a ship, or the type of weapon released), and even particular ships. Publications classification of sounds are provided by and continually updated by the USOffice of Naval Intelligence

Noise limitations Passive sonar on vehicles is usually severely limited because of noise generated by the vehicle. For this reason, many submarines operate nuclear reactors that can be cooled without pumps, using silent convection, or fuel cells or batteries, which can also run silently. Vehicles' propellers are also designed and precisely machined to emit minimal noise. High-speed propellers often create tiny bubbles in the water, and this cavitation has a distinct sound. The sonar hydrophones may be towed behind the ship or submarine in order to reduce the effect of noise generated by the watercraft itself. Towed units also combat the thermocline, as the unit may be towed above or below the thermocline. The display of most passive sonars used to be a two-dimensional waterfall display. The horizontal direction of the display is bearing. The vertical is frequency, or sometimes time. Another display technique is to colour-code frequency-time information for bearing. More recent displays are generated by the computers, and mimic radar-type plan position indicator displays.

MATLAB CODE FOR FEATURE EXTRACTION AND SEGMENTATION clc; clear all; close all; m=webcam; preview(m); framecount=0; while framecount < 2 framepic = snapshot(m); figure; image(framepic); pause(5) RGB_img = imresize ((framepic), [512 512]); figure; subplot(221); imshow(RGB_img); title(‘Original input image’); [p q r] =size(RGB_img); subplot(222); imhist(ycbrr(:,:,1)); ycbcr(:,:,1) = imadjust (ycbcr(:,:,1),stretchlim (ycbcr(:,:,1), 0.01) ); RGB_enhanced = ycbcr2rgb(ycbcr); subplot(224); imhist (ycbcr(:,:,1)); title(‘Enhanced image Histogram’); subplot(223); imshow (RGB_enhanced); title(‘Enhanced Image’); end

Expected Outcome of the project :

1. The proposed system will be designed and developed as a prototype and will be used in demonstration of its capabilities as mentioned in the objectives. 2. Technology transfer can be taken up with interested companies in commercializing the products. Many of the tourist spots, restaurants and water parks can buy this product and can be used as safety equipment. 3. The developed product can be standardized and can be compulsorily made available for every village, taluk and districts. 4. Rescue teams and disaster management teams can use the developed system for search and rescue operations. The system developed could lead to business opportunities.

ROV TRACKING ANOTHER ROV

TO CAPTURE REAL TIME VIDEO