Abstract. 

The study of underwater conditions is a challenging task since the optical properties follow both laws of reflection and refraction. Also other factors such as flora and fauna of the underwater affect the lighting conditions to a great extent. While pertaining to optical processing of such images, degradation may take place due to various factors of environmental and device defects. Also the algorithm based on conventional nyquist algorithm can prove computationally intense and produce lower accuracy due to over hitting of samples. Compressive Sensing (CS) provides an alternative approach to overcome the problem of over hitting. The incoherent sampling combined with sparsity can boost the performance of underwater algorithms. In this paper, the proposed model is applied to underwater blurred image and the algorithm is tested for restoration using directional gradient priors. The contribution of the proposed algorithm can be listed as: a) Incoherent sampling reduces over hitting problem. b) Enhancement of sparsity coefficients for use in restoration algorithms. The proposed contribution in the application of underwater imaging is mainly because the compressive sensing have fewer random samples which yields better sparsity prior in the initial stage which make the solution to ill-posed problem highly convergent yielding high accuracy. Hence, we propose a novel directional sparse bayesian learning used in CS which leads to higher resolution enhancement of lower resolution imagery captured in underwater conditions.

Abstract. 

Underwater imaging is becoming popular due a large number of applications employing it. In this paper, we are presenting an algorithm for estimating the size of an object from an underwater image when provided with the distance from the camera to the object. This algorithm consists of 4 steps: calibration of the camera to estimate its parameters; processing of the captured images to enhance visual perception; selection of the object of interest and its boundaries; and finally size estimation. The results of the experiments are detailed and analysed.

Abstract. 

Development of offshore open sea cage culture is a new way of providing employment and good revenue for fishermen transferring from fish capture to aquaculture. The open sea fish cage culture system is designed to reduce the deep sea (burden of going long way into sea) fish catching for fisher community by increasing the yield of fish growth at offshore areas near to their convenient places with reduced resources and manpower. Today cage culture with automatic and remote control operation have more attention for researchers and commercial producers due to the nature of burden less and low labor intensive. In this paper, we have developed and tested remote controlled data acquisition system (DAQ) for floating cage system for its submergence and floating operation using pumped buoyancy mechanism using DAQ via SMS by user. The user can control cage submergence depth, velocity by timing sequence and floating operation from land using GSM (Global system for mobile) communication technology.

Abstract. 

Marine Sensor Systems group at National Institute of Ocean Technology (NIOT) indigenously developed a Buried Object Detection Sonar (BODS) and carried out a number of successful sea trials. Recently a modular version of the sonar (mBODS) is realized and successfully tested in sea. In order to cater the real time data requirements of the sonar, an Ethernet based remotely configurable and operable, sonar signal generator and multi channel simultaneous sampling receiver system, operating in 2-24 kHz frequency range is developed. This paper reports design aspects of the custom built signal generator and receiver system developed.

Abstract. 

Image enhancement in sonar images enhances the region of interest in the image by improving the intensity levels of each pixels. This improves the visual appearance of images and helps in the extraction of spatial features of importance for object identification. Speckle removal is a pre-processing step required in sonar images for applications like segmentation and registration. Despeckling of sonar images prior to the enhancement, results in a strong enhancement. The paper proposes the sonar image despeckling followed by the image enhancement using fractional masks.

Abstract. 

Identification and classification of underwater noise sources is a demanding task owing to the variable and complicated nature of underwater communication channels. Nevertheless, the detection and classification of underwater targets of interest concealed and masked by heavy ocean noise is very important, particularly in strategic sectors. Individual targets of interest are identified from hydrophone captured acoustic mixture, through their characteristic signatures that are patterned by feature recognition algorithms. In this paper, a support vector machine (SVM) based target classifier is used to distinguish between targets of 4 acoustic classes. The paper focuses on improving the performance of the SVM based classifier by tuning the parameters of the classifier algorithm. The optimal parameters which give the best performance can be found from the search space using meta–heuristic algorithms and the paper attempts using stochastic fractal search (SFS) to automatically select the optimal parameters and kernel of the SVM based underwater target classifier.

Abstract. 

The complex acoustic ambience of the ocean makes it extremely difficult to build a target recognition system that could effectively identify sonar targets when faced with complex interrelationships such as changing environments, multiple targets and non-linearities in the signal. This paper explores the categorization ability as well as novelty detection capability of an underwater target classifier based on sparse representation, trained with a feature vector in the form of DEMON spectra extracted from ship emanations. The recognition accuracy has been evaluated on various target classes and an overall success rate of 88.23% has been obtained.

Abstract. 

Underwater camera system was developed as a means of imaging and recording underwater region using GoPro cameras. It is designed to be operated in two modes: a manual mode, where user can control the camera functions from the surface, and an autonomous mode, where the camera system may be interfaced with an AUV and operate according to a mission file. The autonomous mode of operation includes interfacing of the camera system with GSM/GPRS modem, and preview of media captured can be uploaded to online servers using MQTT or FTP protocol.

Abstract. 

This paper mainly describes efficient way of real-time data acquisition, handling, logging and post processing of the acquired system parameters for remotely operable underwater system using Laboratory Virtual Instrument Engineering Workbench (LabVIEW). It also discusses about the DAQ programming techniques, redundancy in communication, power and data logging in-case of main system fails to overcome the real-time challenges involved in the data collection and handling between the sea surface platform and sub-sea systems and avoiding the loss of vital data/information on experiment and environmental parameters that are the deliverables of the experiment / sea trial. The parallel coding methods like pipelining, multi-threading, task parallelism were designed and used for real-time process. Furthermore, an adequate signal processing analysis is performed on acquired data to investigate the desired measurements of important parameters for the remotely operable underwater systems. The lab test and sea trial test results were confirms the performance of the developed real-time data acquisition and handling system with the advantage of effective programming and redundant techniques , easy-to-use and high efficiency.

Abstract. 

This paper briefs about the design, implementation and testing of electronic hardware and software for a shallow water Autonomous Profiling Drifter. The system is equipped with Variable Buoyancy Engine (VBE), CTD sensor and satellite data transmitter. It performs buoyancy change for profiling, data logging and data communication. Embedded system controls the entire float operation in sequenced and time based manner, electronic hardware and software is designed in a way to keep the power consumption minimum to increase the life time of the system in sea. Initial performance of the system is assessed by simulating the sea water column in laboratory.

Abstract. 

A better understanding and acute knowledge of the spatial and temporal variability of thermal stratification of the upper-ocean layers is fundamental for designing of any precise and accurate ocean temperature measurement system. NIOT has developed a new generation sea surface temperature (SST) sensor adapting a negative temperature coefficient (NTC) type thermistor sensor with RS232 digital output in its indigenous development of drifting buoys with Indian satellite (INSAT) communication (Pradyu). Fast thermal responding, ultra-precision interchangeable thermistors of series 46000 has been incorporated in drifting buoys to measure surface and subsurface thermal variation at mixed layer water depth in oceans. In this implementation, the 46000 series thermistor generates an electrical signal corresponding to ocean temperature fluctuations, which is conditioned by an analog circuit board, and digitized and recorded to a custom data acquisition and formatted for onward transmission. The Steinhart–Hart equation and coefficients is applied on each sampling to null down the error components involved in temperature measurements corresponding nonlinear behaviour of NTC element. The results of the sea surface and subsurface temperature data collected in Arabian Sea during April 2016 along with Bay of Bengal SST data sets are briefly presented in this article.

Abstract. 

Object counting is a challenging task in image processing using computer vision algorithms. It has application in various industries, Research Laboratories, Agriculture, Science research including Aqua culture etc. In this paper, we propose an efficient Fish Counting Algorithm (FCA) for the fish cultured in the fish cage system deployed at dynamic environment in open sea. The traditional method makes use of experienced divers to manually do the counting after the harvest whereas automatic counting system reduces the manual intervention and helps in live stock estimation for every day/week etc to ascertain not only the growth of fish during its life span but also its security & surveillance purposes due to its remote location from the shore. The image analysis and counting is performed based on the image segmentation, Binary Large Object (BLOB) detection method and classified using Support Vector Machine (SVM) algorithm. The image features are extracted from the multiple images taken by the camera deployed in the fish cages. The validation of automatic fish counting algorithm is made comparing with manual count measurement and deviation are addressed.

Abstract. 

Research in the field of underwater wireless sensor networks is steering up due its wide range of applicability in the domains like military, marine geology and industrial automation. As a communication system, efficient network protocols are essential for the smooth functioning of UWSN. Many of the routing protocols used in terrestrial Wireless Sensor Networks (WSN) are not suitable for routing in UWSN due to the difficulty in obtaining the location information of underwater nodes. Many protocols like Depth Based Routing (DBR) proposed for UWSN does not require the three dimensional location information. However, the rate of collision and delay is high in DBR. This paper proposes a path addressed routing scheme using DBR to improve energy efficiency and latency without compromising the packet delivery rate. This improvement is achieved by controlling the number of broadcasts made by the nodes. Using simulations it is proved that this simple but efficient protocol can make DBR better in terms of energy efficiency and delay.

Abstract. 

This paper discusses a novel approach towards Mission Planning for an Autonomous Underwater Vehicle (AUV), using QGIS. The focus of this work has been on creating tools which is based on scientific data and flexible enough to the user without engineering background while planning the mission. The tools provide a simple method to generate a trajectory in GPS coordinates Latitude and Longitude as well as in Universal Transverse Mercator (UTM) coordinates as per the users requirements. The mission planning tool uses effectively multi-layer features of GIS to have background data in order to plan the mission. The Mission planning utility also provides a warning depending on the contour map at the background depending on the planned mission, it also enables to generate keyhole markup language (KML) file which is used to track the AUV online. This paper explains about the details of the mission planning using QT, C and Python languages and software flow/algorithm is also discussed. We also discuss how to add plugins programmed in C/python to meet special needs without running a separate process.

Abstract. 

There is a critical need for long-term, sustained global ocean observations which will help us gain insight in understanding global weather patterns. It has become imperative to track rapidly evolving global climate by studying the upper ocean where ocean-atmospheric interaction is prominent. Towed undulators provide a good platform for continuous data sampling without having to stop the ship. This motivated the development of C-Profiler which has profiling towfish capable of collecting fine scale conductivity, temperature and depth data profiles up to a depth of 100m from a vessel moving at slow speeds with spatial resolution of around 2 km while underway. The first prototype towfish was designed and manufactured at NIOT and has undergone preliminary testing at sea. The system overview with detailed description of its components along with the observations from the field trial is presented in this paper.

Abstract. 

This paper describes the realization of a low cost modem for underwater vehicles, sensor networks and biological monitoring systems. This work is focused on the design and implementation of a modem using readily available components. FSK modulator and HBridge driver are designed and realized with the help of an ARM microcontroller. The demodulator/receiver is realized using PLL and another ARM processor. By studying the characteristics of the piezoelectric transducer, 74 kHz and 82.5 kHz are used for realizing FSK modulator. A power supply for driving the piezoelectric transducer around a low loss boost converter is also developed.