rapid observations - national institute of ocean technology · 2018. 9. 26. · oyrgh journal of...

Copyright Journal of Ocean Technology 2018

Venkatesan, Ramesh, Kesavakumar, Arul Muthiah, Ramasundaram, and Jossia discuss ocean observational platforms, challenges, new technologies, and spin-offs from conventional observation to surveillance and innovative rapid-mode of data collection.

Rapid Observations

Who should read this paper?Scientists, engineers, oceanographers and authorities who work in the fields of ocean observation, meteorology, weather advisories, and coastal security agencies will benefit from reading this paper. Why is it important?This paper focuses on the development of ocean moored data buoy systems for local applications and the challenges that may be encountered. Readers will gain a better understanding of the data buoy components and development of cost effective data acquisition systems, system programming software, system qualification tests, and calibration needs. Information is also provided on effectively utilizing the system during cyclones by observing the vital metocean parameters in high sampling rates using rapid-mode data transmission. It provides a greater understanding on the recent technologies and developments in coastal ocean observation, ocean surveillance, and visualization of the ocean environment directly to the desktop as well as on the various factors to consider when selecting instruments and sensors for offshore marine platforms. About the authorsR. Venkatesan is a Doctorate from the Indian Institute of Science Bangalore. His area of interest is ocean observation methods as well as ocean policy and management. Recently he was recognized with the Certificate of Merit by the World Meteorological Organization and UNESCO IOC for his outstanding services in global ocean data collection. He also received the prestigious MTS Lockheed Martin Award and the National Geoscience Award from the Honourable President of India. Presently, Dr. Venkatesan heads the Ocean Observation Group at the National Institute of Ocean Technology. He is also Vice Chairman-Asia of the Data Buoy Cooperation Panel and Chair of the International Tsunameter Partnership. He worked as Regional Coordinator of South Asian Seas program of UNEP, SACEP, Sri Lanka.

K. Ramesh obtained his M.Tech. in Ocean Technology from the Indian Institute of Technology Madras. His area of expertise is design of offshore data acquisition systems, calibration and interfacing of metocean sensors,

52 The Journal of Ocean Technology, Vol. 13, No. 1, 2018

R. Venkatesan

K. Ramesh

B. Kesavakumar

Copyright Journal of Ocean Technology 2018

and offshore communication systems. He has participated in many cruises for maintenance of the data buoy and tsunami buoy systems.

B. Kesavakumar holds a Bachelor of Electrical Engineering. He is responsible for testing and integration of the Indian data buoy system and tsunami buoy system. He is involved in the deployment of the Indian Arctic moorings and also involved in optimization of the buoy power system. He was awarded the National Geoscience Award by the Honourable President of India.

M. Arul Muthiah obtained his post-graduation in Electronics Engineering from National Institute of Technology, Thiruchirapalli, India. He received the National Geoscience Award from the Honourable President of India for his significant contribution in the installation of the Indian Arctic mooring. His area of expertise includes design, development, installation, and maintenance of offshore autonomous data acquisition / collection platforms especially in instrumentation and communication systems. He has also participated in various cruises on board research vessels for the installation of the Indian data buoy and tsunami buoy systems.

S. Ramasundaram is a post-graduate from the University of Madras, India. His area of expertise is computer science. He has been associated with NIOT’s Ocean Observational Program since its inception and was responsible for setting up the Satellite Data Reception Centre, creating software that suits science and technology oriented interdisciplinary environments. In addition, he has participated in several field cruises, deployed buoys, and has significantly contributed in the development of the surveillance system. He has been awarded a Certificate of Merit by the Ministry of Earth Sciences for his outstanding contributions.

K. Jossia Joseph is a Doctorate from Cochin University of Science and Technology. She is a physical oceanographer with a focus on ocean wave dynamics and numerical wave modelling. She is also interested in measurement techniques, data processing and data management of metocean parameters collected using moored data buoys.

The Journal of Ocean Technology, Vol. 13, No. 1, 2018 53

M. Arul Muthiah

S. Ramasundaram

K. Jossia Joseph

54 The Journal of Ocean Technology, Vol. 13, No. 1, 2018 Copyright Journal of Ocean Technology 2018

COASTAL OBSERVATION BY MOORED BUOY SYSTEM IN INDIAN REGION

R. Venkatesan, K. Ramesh, B. Kesavakumar, M. Arul Muthiah, S. Ramasundaram, and K. Jossia JosephNational Institute of Ocean Technology, Pallikaranai, Chennai, India

ABSTRACT

Oceans play a major role on global weather and climate patterns. However, the coastal zones are more susceptible to hazards as global ocean climate changes and utilization of coastal resources increases. Thus, coastal observation has to support the societal economy of the country by protecting coasts and the people. Indian coastal ocean observational networks consist of moored buoys, drifters, current meters, wave rider buoys, Argo floats, tide gauges, coastal radars, and acoustic Doppler current profilers (ADCP). This paper discusses the cost effective moored buoy system established in India with General Packet Radio Service (GPRS) communication and intelligent power management system for a coastal ocean observation network. These moored buoys have capacities of rapid-mode real-time observation of metocean parameters during cyclone and real-time video transmission called Surveillance System (SS). These moored buoys are used for calibration and validation (CAL-VAL) of satellite remote sensing and to analyze the coral reefs.

KEYWORDS

Moored buoy; Data acquisition system; Real-time data; Surveillance system

The Journal of Ocean Technology, Vol. 13, No. 1, 2018 55Copyright Journal of Ocean Technology 2018

INTRODUCTION

The application of a long-term, real-time coastal observation network supports the immediate needs for coastal decision making and provides the historical data needed to understand the natural variability. Coastal observation and forecasting systems support numerous activities in the coastal environment such as safe and efficient navigation and marine operations, efficient oil and hazardous material spill trajectory predication and clean up, mitigating coastal hazards, military operations, search and rescue, prediction of harmful algal blooms, hypoxic conditions, water quality phenomena and scientific research, etc. [Glenn et al., 2000]. Safety and efficiency of marine operations, effective control and mitigation of the effects of natural hazards, detect and predict the effects of global climate change on coastal ecosystems, and sustain living marine resources are the main goals of the coastal module of the Global Ocean Observing System (GOOS) [UNESCO, 2003]. For better understanding of these modules, the coastal ocean observation network with mixed platforms such as moorings, profiling floats, gliders, tide gauge, drifter, and remote sensing by land based systems are needed to provide the broad spectrum of data and information. The essential components of these observations are sensing the parameters, acquisition of data with dissemination, and finally assimilation and analysis based on scientific understanding. The design and implementation of the coastal modules may differ among the regions and stakeholders depending on their requirements. At the same time, GOOS has common requirements; thus, the collaboration between

the common global and regional networks will have beneficial effects on the whole design and management of GOOS [UNESCO, 2005]. Quintrell et al. [2015] discussed the importance of regional partnerships in coastal ocean observation.

In India, the ocean observation system has been implemented and operated by the Ministry of Earth Sciences (MoES) with the prime objective of providing quality data to the user community in real-time by implementing the observational platforms such as moored buoys, drifters, current meters, wave rider buoys, Argo floats, tide gauges, coastal radars, and acoustic Doppler current profilers (ADCP) in different parts of the Indian Ocean. These data cater to research needs as well as a wide range of operational services including tsunami early warning; they are also useful for ocean atmospheric modelling and validation of satellite data. ADCP mooring in the coastal region provides data for better understanding the seasonal cycle of the East India Coastal Current (EICC) and West India Coastal Current (WICC), which generally exchange the heat and salt between the Arabian Sea (concentration basin) and Bay of Bengal (dilution basin), which helps to maintain the large scale hydrological balance [Amol et al., 2014]. Drifter buoys are well suited for coastal application as they provide data sets to understand the mixed layer, nearshore currents and beach erosion. A cost effective GPRS communication-based drifter buoy developed in India works with two-way communications for data downloading and system programming and a mobile app displays the drifter track and current speed and direction [Srinivasan et al., 2016]. Argo floats play an important role in


oceanography by providing data to study the three dimensional evolution of thermohaline structure; a complete description of ocean current, ocean and coupled forecast models; satellite data validation; and prediction of weather and climate. Since 2001, India began to deploy the Argo floats. The first Argo float was deployed in the Arabian Sea [Ravichandran et al., 2004]. High frequency (HF) radar installed on the Indian coast provides data on surface currents and high wave activity within its measuring limits. Since the high frequency radar is less likely to be disrupted on the passage of cyclones, it provided valuable data during Cyclone Phailin (2013) and the data are comparable with the moored buoy [Manu et al., 2015]. HF radar and tide gauge are important tools to aid tsunami observation and warning. The weak 2012 Indonesia tsunamis were detected successfully by HF radar in spite of a narrow shallow water shelf offshore from the radar systems [Lipa et al., 2012]. Acoustic based tide gauges were developed in India and are being installed in coastal regions [Pathak and Ramadass, 2002]. Mooring arrays provide vital information about mixed layer dynamics, surface current, air-sea heat, and freshwater fluxes [Venkatesan et al., 2013].

National Institute of Ocean Technology (NIOT) Chennai is an organization operated under MoES, Government of India. NIOT has successfully developed moored data buoy system, tsunami buoys, autonomous underwater profiling drifter (AUPD), drifter and tide gauges (Table 1). One of the major programs in the ocean observation program in India is the moored buoy systems, which have been deployed and maintained in the Arabian

Sea and Bay of Bengal. These buoy systems are capable of collecting data up to 76 parameters and transmitting the information in real-time through satellites [Venkatesan et al., 2013]. Currently, the moored buoys network has been augmented to a 19 buoy network, out of which four have been deployed in coastal regions. As recommended by GOOS [UNESCO, 2003], coastal ocean observation systems have been established and maintained by India as shown in Figure 1. This paper discusses the cost effective system for a coastal ocean observation network established in India with Indian Data Acquisition System (IDAS), GPRS communication, and intelligent power management system. This network consists of moored buoys which have capacities of rapid-mode real-time observation of metocean parameters during cyclone and real-time video transmission.

Table 1: Details of the observational platforms deployed and maintained by India.

Type of Platform Commissioned

Argo floats 291

Drifters 103

Moored buoy 19

Tide gauges 34

Coastal radars 10

Current meter array 11

Acoustic Doppler current profiler (ADCP)

21

Tsunami buoys 9

Wave rider buoy 16

The Journal of Ocean Technology, Vol. 13, No. 1, 2018 57Copyright Journal of Ocean Technology 201857 The Journal of Ocean Technology, Vol. 13, No. 1, 2018

Figure 1: Location (top) and architecture (bottom) of coastal observations maintained in India [Indian National Centre for Ocean Information Services, n.d.].


COASTAL OCEAN MOORED BUOY SYSTEM

The coastal buoy is comprised of a polyurethane, foam-filled, fibre reinforced, plastic hull which is moored to the seabed using an eco-friendly reinforced concrete weight in an inverse catenary configuration (Figure 2). OrcaFlex software is used to design the mooring and the estimated mean time of failure of this mooring is 6.3 to 11.1 years [Venkatesan et al., 2015a]. The watertight instrument housing is encased by plastic hulls, contains energy storage batteries with power management unit and a data acquisition system

(DAS), which are connected with the external sensors to measure the metocean parameters such as wind speed and direction, air temperature, humidity and pressure, precipitation, solar radiation, wave, sea water temperature, conductivity, and current. The sensors that measure the meteorological parameters are mounted on the mast at a height of 3 m above the mean sea level as recommended by the World Meteorological Organization (WMO) [Meindl, 1996].

The power management system is comprised of four 20 watt solar panels that charge the 200Ah lead acid batteries and additionally supported

Figure 2: Architecture of the moored coastal buoy.


with LiSoCl2 primary batteries configured to meet the IEC 61508 Safety Integrity Level (SIL 4) [Venkatesan et al., 2015b].

Except the sensors, all the buoy components are indigenized. The heart of the buoy system is the Indian Data Acquisition System (IDAS) designed with a ATMEL AT32UC3A3256 microcontroller that monitors and executes the main tasks such as the sampling interval, synchronization by means of a real-time clock, data acquisition from the sensors, information backup, and data transmission. The block diagram of the electronics components in the moored buoy system is shown in Figure 3. The main components of the buoy system are the sensors, power system, IDAS and the telemetry. The system has interface to 16 analog and 16 digital sensors. The IDAS system has four main modules that perform all the major functions of IDAS: Controller module, Power relay module, Memory module, and Backplane module.

The data acquisition is carried out in time intervals defined/programmed by the user

prior to the deployment, which can be every one to three hours in one hour increments. When the time interval set by the user is reached, the microcontroller first applies the control signal to the voltage regulators to feed the power to the needed circuits by means of which it indicates that a new burst of measurements will start. Then the microcontroller starts reading all the sensors in a sequence as defined in the program configuration. The sensors with digital output are directly read and, for the one with analogical output, an analog to digital convertor (ADC) is used to convert the reading. Upon completion of the data acquisition, the buoy then transmits data through GSM using GPRS service and backs up the data in the memory [Vengatesan et al., 2013]. Once the measurements, parameter updating, and transmissions are done, the control signal for the voltage regulators is turned off and the microcontroller is set to deep sleep mode until the next cycle begins. In case the data transmission fails, the data will be saved to a

Figure 3: Block diagram of the buoy electronics.


flash memory capable of saving up to 24 datasets (three days with eight datasets per day) and will be transmitted to shore, once good signal strength is sensed. The three-hour proof test interval (PTI) implemented in the moored buoy to shore station ensures that the data telemetry system meets SIL4 [Venkatesan et al., 2015c]. All the data stored in the memory can be accessed by the serial port of a personal computer with the help of software specially designed for data downloading. As recommended by GOOS [UNESCO, 2003], the data set is being disseminated in GTS file format for the global community through Indian National Centre for Ocean Information Services (INCOIS). Pattabhi et al. [2012] discussed the development of open-source architecture for real-time data reception for the coastal observation network followed in India.

The IDAS can be operated in two different modes: Monitor mode and Autonomous mode. In the Monitor mode, the total functionality and its operation of instruments can be tested prior

to the deployment. Functionality test includes ensuring the parameters captured by the sensor are within the range, data transmission, data storage/recovery in memory, programming the system, etc., which is generally termed as self-test/debug mode in software. The Autonomous mode is the typical buoy’s operation state since, before taking it to the field, it is programmed with all the variable sampling and transmission intervals, and it is set to stand by until triggered up by a real-time clock in order to carry out its tasks autonomously.

ProgrammingThe programming consists of system configuration software which carries out tasks such as sampling acquisition, data backup in memory, and the instruments’ general temporization. This program is totally transparent to the user. The system configuration software, developed in VC++ language, allows users to program the IDAS with user selectable sampling frequency, acquisition interval, and transmission interval (Figure 4). It also allows for checking the

Figure 4: Graphical User Interface (GUI) for system configuration.


adequate operation of the sensors when the instrument is set to the monitor mode in the self-test option and, in addition, it manages the data reception and decoding.

System Qualification TestsThe IDAS was subjected to various tests following the standards in order to qualify the system for operation in marine conditions over a long time period. These include the insulation and isolation resistance test, ingress protection test (IP67), vibration tests (based on MIL-STD-810E-514.4), and shock test (MIL-STD-810E-516.4) (Figure 5). As the systems have to withstand large temperature variation in open ocean, the salt and fog test (MIL-STD-810E-509.3) and climate tests were also performed as per QM333 standards such as dry heat test, cold test, rapid temperature cycle test, damp heat steady state test, and damp heat cyclic state test. In addition to this, the IDAS was also subjected to EMI and EMC test as per IEC 61000 standards.

CalibrationThe sensors used in the buoy systems are imported from globally reputed firms and are refurbished and calibrated at regular intervals of time for consistent operation and high degree of quality data. The instrumentation calibration procedures and accuracy estimates of the moored buoy sensors follow the best practices published by the National Oceanic and Atmospheric Administration (NOAA)/Pacific Marine Environmental Laboratory (PMEL) [Lake et al., 2003]. Analog to Digital Channels are calibrated with different voltage ranges as shown in Table 2 using standard computer controlled DC source and digital multimeter (Figure 6). The custom made software is programmed to do the pre- and post-cruise calibrations in auto mode.

RAPID-MODE REAL-TIME OBSERVATION DURING CYCLONE

The moored data buoy network in Indian seas

Figure 5: Vibration test platform with IDAS.

Table 2: Analog to digital channel calibrations and voltage ranges.

Channel Range Resolution No. of Points

Air humidity 0.1 – 1.5V 0.05V 29

Air temperature 0.1 – 1.5V 0.05V 29

Precision Infrared Radiometer PIR 0.2 – 1.5mV 0.025mV 53

Precision Spectral Pyranometer PSP 1 – 10mV 0.020mV 41

Rainfall 0.3 – 1V 0.050V 10

Wind speed 0.04 – 1mA 0.05mV 20

Wind direction 0.2V – 2.2V 0.1V 21

PIR case and dome temperature 0.27 – 2.5V 0.025V 80

Figure 6: IDAS-ADC calibration setup.



is established with a primary objective of capturing the oceanic response during cyclone passage and thereby support wave models and better prediction of the track, intensity and landfall of cyclones [Mcphaden et al., 2009; Sirisha et al., 2015]. For better understanding

of ocean responses as well as the prediction of the track of a cyclone, the ocean has to be observed in higher sampling rates with real-time data transmission during a cyclone. For that, NIOT has developed an algorithm in which the buoy could make rapid-mode

Figure 7: Data frequency (top), time series data (bottom 1. air pressure 2. wind speed, 3. sea surface temperature) during Cyclone Roanu.


transmission during the passage of a cyclone in the moored buoy location. The analysis, based on data observed during past cyclones, revealed that the quickest response is evident in air pressure and in wind speed in which the measurement and processing are also easy compared to that of waves and currents. Air pressure is identified as a primary parameter in detecting a cyclone and a sudden drop in air pressure is also utilized in detection.

The algorithm was implemented in moored data buoys and successfully recorded high frequency data sets during a cyclone passage. The coastal buoy CB06, deployed off Chennai, transmitted the data in rapid mode during Cyclone Roanu (May 2016) and Cyclone Vardah (December 2016). Figure 7 shows the data collected during Cyclone Roanu.

SURVEILLANCE SYSTEM

Buoy systems have been used as an observational platform at sea for years with the mandate to obtain meteorological and oceanographic data. Primarily, satellite communications have been used for transmitting the observed data from these unmanned autonomous buoys at sea to shore based reception systems. 3G/4G is the next generation of technology that has revolutionized the telecommunication industry. Apart from increase in speed of the communication, the objective of this technology is to provide various value added services like video calling, live streaming, mobile Internet access, IPTV, etc. These services are possible because this spectrum provides the necessary bandwidth and signal from towers that are radial in nature; it is also

available at sea up to ~14 km along the coast. This technology brought out the surveillance system (SS) in the Indian buoy program and the developed system was deployed off Goa (15◦2309 73◦4574E) in 2014. This approach provides real-time meteorological and oceanographic data, along with real-time images and high definition videos both above and below the surface surrounding the buoy system using 3G telemetry and GPRS. High resolution cameras (1.3 megapixel) are capable of taking nighttime videos and pictures as well, with an IR range of up to 30 m (Figure 8). This system records and transmits the images every alternate 15 minutes, and the dedicated authorities are able to view the live videos and pictures during this period. Such efforts are expected to reduce vandalism in the future. The visual data near the buoy system can be used to compare the data from the sensors for real-time visualization. Further, the visual data can be used for surveillance applications.

Underwater imaging helps in identifying marine creatures and in studying the behavioural patterns of marine organisms [Fukuba et al., 2015]. The presence of camera systems in the moored buoy system is also used for estimating the amount of white caps on the sea surface [Bakhoday-Paskyabi et al., 2016]. The visuals captured from the cameras will be subjected to a image processing engine located at the Mission Control Centre of National Institute of Ocean Technology for auto detecting scenes of interest such as the horizon, ship movements, and the presence of humans near the buoy system [Fefilatyev et al., 2010]. Buoys equipped with the surveillance system


will be of great use in assessing and monitoring floating oil spills close to the vicinity of the buoy system. Although the most reliable technique is visual observations from aircraft, ice, internal waves, kelp beds, natural organics, pollen, plankton blooms, cloud shadows, jellyfish, algae [Fawcett et al., 2006] and guano washing off rocks have all falsely been reported as oil spill by aerial surveyors.

In reality, the appearance and colour of an oil sheen varies with the amount of available sunlight, sea surface state, and viewing angles. Glare due to very low sun angles and sunlight directly overhead can make observations particularly difficult due to poor contrast between an oil sheen and water. The on-scene weather is another important factor that includes visibility, surface wind speed and direction, and sea state. As buoys are equipped with visual observational capabilities in addition to the meteorological and oceanographic sensors, it will be convenient to visualize, and identify any

spill’s progress with the wind drift and surface currents data (Figure 9).

Added to the above, the SS is also augmented with an automatic identification system (AIS), which is fitted on vessels to broadcast messages about its position, speed, course, cargo, destination, etc. using maritime VHF band. The messages broadcast by vessels passing approximately within a 24 nautical mile radius of the buoy location can be received on the buoy system. These secondary data sets about passing ships will be an indispensable informational aid for surveillance and traffic management. They are collected and stored in passive manner. Pools of data sets are available in these SS based floating platforms.

CAL-VAL AND CORAL REEF

Validation of remotely sensed data products is one of the objectives of coastal observation; in this respect, the Indian Space Application Centre (SAC) Ahmedabad and NIOT jointly

Figure 8: Schematic diagram of IMSS.


deployed a pair of buoy systems (Figure 10) with MET and OPTICAL sensors at Kavaratti in Lakshadweep Island in the Arabian Sea for the calibration and validation of the OCM-2 satellite. This buoy consists of fully automated hyperspectral radiometers, flurometer, and metrological sensors. Shukla et al. [2013] presented the utilization of this in-situ data to derive OCM-2 vicarious gain coefficients and validation of OCM-2 geophysical products.

Coral reefs play an important role by protecting shoreline of around 150,000 km in more than 100 countries and territories; they act as a wave observer and reduce the damage from tsunami, erosion, and storms thus protecting human infrastructure and coastal ecosystems. Coral reefs are formed through the accumulation of calcium-carbonate skeletons over very long periods of time (centuries or more). Most of the coral exist in

tropical waters. One-eighth of the global population live within 100 km of reefs and derive some benefits from them. The Atlantic Ocean, the Indian Ocean, the Middle East, the Pacific Ocean, Southeast Asia, and Australia are found to be large reef-building areas. Andaman and Nicobar Islands harbour more than 400 species of scleractinian coral along the continental shelf [Mondal et al., 2014]. A study by Lix et al. [2016] using the coastal buoy deployed in the Andaman Sea revealed that, during the strong El Nino years of 1997-1998 and 2009-2010, the sea surface temperature was more elevated and mass bleaching events were seen only then.

CHALLENGE

Biofouling, vandalism, and deployment using boats are the main challenges in coastal mooring. Biofouling effects on marine

Figure 9: Picture capture in surveillance system – algal bloom (left) and oil spill (right).

Figure 10: Picture of the CAL-VAL buoy deployed in Lakshadweep Island.


instrumentation are numerous. Hydrodynamic screening, reduction of thermal exchanges, and modifications of interfacial properties are so crucial for any transducers that may be affected by fouling over the sensor. Thus, biofouling is one of the limiting factors in providing an accurate measurement from the ocean [Lehaitre et al., 2008]. Conductivity sensors placed in coastal water/surface layer are more prone for drift due to biofouling as compared to the deep ocean/layers. Hence frequent cleaning of sensors deployed in coastal waters may improve the performance of a sensor. Venkatesan et al. [2017] studied biofouling in moored buoys and developed an antifouling method such as copper guard, copper tape, and zinc gel that reduces the settlement and growth of biofouling organisms by 59%. High intervention of human activity in coastal areas leads to potential vandalism of a moored buoy system. Thus many efforts were expended to create consciousness among fishermen about the buoy systems by organizing awareness programs, which resulted in significantly reduced vandalism.

CONCLUSION

Threats to the coastal communities include natural disasters such as tsunami, hurricanes and coastal storms, as well as longer term risks such as coastal erosion and sea level rise. A natural calamity cannot be stopped; however, precautions can be taken to reduce the effects by making reliable coastal protection systems. For that, we need a better understanding of coastal characteristics by making a consistent coastal observational network. Advancements in science and technology allowed new platforms to include a wide spectrum of data

sets in temporal and spatial scales that help the coastal community and government agencies deal with coastal threats and develop reliable coastal protection systems. In this perspective, India has established the coastal observation network as suggested by GOOS with various advanced observational platforms. In this paper, we presented the development of the cost effective moored buoy system, its essential components, system qualification standard tests, and calibration. For effective prediction and understanding of the intensity of a cyclone, higher ocean observation sampling rates are necessary. For the first time, the rapid-mode real-time metocean data transmission from the moored buoy during a cyclone has been demonstrated in this region. With the advancement of the telecommunication industry, it is feasible to provide the high data rate with value-added service of live video streaming using GSM technology within the signal coverage area. This technology provides the thought process to bring out a visualization of the ocean environment onto a desktop. Along with in-situ observation and national security, this technology brings value added service. It was felt that such a system would have helped during the 2008 Mumbai terror attack. For such an application, the benefits reaped would outweigh the cost involved.

ACKNOWLEDGMENTS

The authors thank the Ministry of Earth Sciences, Government of India, for funding the Ocean Observation network program and the members of the National Expert Committee for advancing this program. Directors of NIOT-Chennai, NCAOR-Goa, and INCOIS-Hyderabad are thanked for providing the


facilities and logistical support. We also thank the staff of the Ocean Observation Systems group, Vessel Management Cell of the NIOT, and ship crew for their excellent help and support on board. Our extended thanks to the Society for Applied Microwave Electronic Engineering and Research Chennai and the Electronics Test and Development Centre for providing the facilities to carryout system qualification testing.

REFERENCES

Amol, P.; Shankar, D.; Fernando, V.; Mukherjee, A.; Aparna, S.G.; Fernandes, R.; Michael, G.S.; Khalap, S.T.; Satelkar, N.P.; Agarvadekar, Y.; Gaonkar, M.G.; Tari, A.P.; Kankonkar, A.; and Vernekar, S.P. [2014]. Observed intraseasonal and seasonal variability of the West India coastal current on the continental slope. Journal of Earth System Science, Vol. 123, No. 5, pp. 1045-1074.Bakhoday-Paskyabi, M.; Reuder, J.; and Flügge, M. [2016]. Automated measurements of whitecaps on the ocean surface from a buoy-mounted camera. Methods in Oceanography, Vol. 17, pp. 14-31.Fawcett, A.; Bernard, S.; Pitcher, G.C.; Probyn, T.A.; and du Randt, A. [2006]. Real-time monitoring of harmful algal blooms in the southern Benguela. African Journal of Marine Science, Vol. 28, No. 2, pp. 257-260.Fefilatyev, S.; Goldgof, D.; and Lembke, C. [2010]. Tracking ships from fast moving camera through image registration. Proceedings: International Conference on Pattern Recognition.Fukuba, T.; Miwa, T.; Watanabe, S.; Mochioka,

N.; Yamada, Y.; Miller. M.J.; Okazaki, M.; Kodama, T.; Kurogi, H.; Chow, S.; and Tsukamoto, K. [2015]. A new drifting underwater camera system for observing spawning Japanese eels in the epipelagic zone along the West Mariana Ridge. Fisheries Science, Vol. 81, No. 2, pp. 235- 246.Glenn, S.M.; Dickey, T.D.; Parker, B.; and Boicourt, W. [2000]. Long-term real-time coastal ocean observation networks. Coastal Global: Ocean Observing System, Vol. 13, No. 1, pp. 24-34.Indian National Centre for Ocean Information Services. [n.d]. Ocean observation network. Retrieved from www.incois.gov.in/portal/ OON.jsp.Lake, B.J.; Noor, M.S.; Freitag, P.H.; and McPhaden, M.J. [2003]. Calibration procedure and instrumental accuracy – estimates of ATLAS air temperature and relative humidity measurements. NOAA technical memorandum, OAR PMEL.Lehaitre, M.; Delauney L.; and Compère, C. [2008]. Biofouling and underwater measurements. In: Real-time coastal observing systems for marine ecosystem dynamics and harmful algal blooms: theory, instrumentation and modelling, Edition: Oceanographic Methodology series. UNESCO publishing, Chapter: 12, Editors: Babin, M.; Roesler, C.S.; and Cullen, J.J. pp.463-493.Lipa, B.; Barrick, D.; Diposaptono, S.; Isaacson, J.; Jena, B.K.; Nyden, B.; Rajesh, K.; and Kumar, T.S. [2012]. High frequency (HF) radar detection of the weak 2012 Indonesian tsunamis. Remote Sensing, Vol. 4, pp. 2944-2956.Lix, J.K.; Venkatesan, R.; Grinson, G.; Rao,


R.R.; Jineesh, V.K.; Arul, M.M.; Vengatesan, G.; Ramasundaram, S.; Sundar, R.; and Atmanand, M.A. [2016]. Differential bleaching of corals based on El Niño type and intensity in the Andaman Sea, southeast Bay of Bengal. Environmental Monitoring Assessment, Vol. 188, No. 3, pp. 175. Manu, J.; Jena, B.K.; and Sivakholundu, K.M. [2015]. Surface current and wave measurement during Cyclone Phailin by high frequency radars along the Indian coast. Current Science, Vol. 108, No. 3, pp. 405-409.Mcphaden, M.J.; Foltz, G.R.; Lee, T.; Murty, V.S.N.; Ravichandran, M.; Vecchi, G.A.; Vialard, J.; Wiggert, J.D.; and Yu, L. [2009]. Atmosphere interactions during Cyclone Nargis. Eos, Vol. 90, No. 7, pp. 53-60.Meindl, A. [1996]. Guide to moored buoys and other ocean data acquisition systems. DBCP Technical document 8, Intergovernmental Oceanographic Commission of UNESCO.Mondal, T.; Raghunathan, C.; and Venkataraman, K. [2014]. Coral bleaching in Andaman Sea – an indicator for climate change in Andaman and Nicobar Islands. Indian Journal of Geo-Marine Sciences, Vol.43, No. 10, pp. 1945-1948.Pathak, A.G. and Ramadass, G.A. [2002]. Device for measuring liquid level preferably measuring tide level in sea. Patents, US 6360599 B1.Pattabhi, R.R.E.; Venkat Shesu, R.; and Udaya Bhaskar, T.V.S. [2012]. Coastal ocean observing network – open source architecture for data management and web- based data services. International Archives

of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4, pp. 19-22.Quintrell, J.; Luettich, R.; Baltes, B.; Kirkpatrick, B.; Stumpf, R.P.; Schwab, D.J.; Read, J.; Kohut, J.; Manderson, J.; McCammon, M.; Callender, R.; Tomlinson, M.; Kirkpatrick, G.J.; Kerkering, H.; and Anderson, E.J. [2015]. The importance of federal and regional partnerships in coastal observing. In: Coastal Ocean Observing Systems, pp. 26-39. Elsevier Inc. DOI: 10.1016/B978-0-12-802022- 7.00003-1.Ravichandran, M.; Vinayachandran, P.N.; Sudheer, J.; and Radhakrishnan, K. [2004]. Results from first ARGO float deployed by India. Current Science, Vol. 86, No 5, pp. 651-659.Shukla, A.K.; Babu, K.N.; Prajapati, R.P.; Suthar, N.M.; Ajai, S.A.; Saifee, A.M.; Satashia, S.N.; Arul Muthiah, M.; and Venkatesan, R. [2013]. An ocean CAL-VAL site at Kavaratti in Lakshadweep for vicarious calibration of OCM-2 and validation of geophysical products – development and operationalization. Marine Geodesy, Vol. 36, No. 2, pp. 203- 218.Sirisha, P.; Remya, P.G.; Balakrishnan Nair, T.M.; and Venkateswara, R.B. [2015] Numerical simulation and observations of very severe cyclone generated surface wave fields in the north Indian ocean. Journal of Earth System Science, Vol. 124, No. 8, pp. 1639-1651.Srinivasan, R.; Zacharia, S.; Kankara, R.S.; and Sudhakar, T. [2016]. Design and performance of GPRS communication based drifting buoy for measurement of


upper layer current in coastal area. Journal of Ocean Technology, Vol. 11, No. 2, pp. 69-75.UNESCO United Nations Educational, Scientific and Cultural Organization [2003]. The integrated, strategic design plan for the coastal ocean observations module of the Global Ocean Observing System. GOOS Report No.125.UNESCO United Nations Educational, Scientific and Cultural Organization [2005]. An implementation strategy for the coastal module of the Global Ocean Observing System. GOOS Report No. 148.Vengatesan, G.; Arul Muthiah, M.; Upadhyay, J.S.; Sundaravadivelu, N.; Sundar, R.; and Venkatesan, R. [2013]. Real time, low power, high data rate and cost effective transmission scheme for coastal buoy system. Proceedings: International Symposium on Ocean Electronics, SYMPOL 2013.Venkatesan, R.; Shamji, V.R.; Latha, G.; Mathew, S.; Rao, R.R.; Muthiah, A.; and Atmanand, M.A. [2013]. In situ ocean subsurface time-series measurements from OMNI buoy network in the Bay of Bengal. Current Science, Vol. 104, No. 9, pp. 1166- 1177.Venkatesan, R.; Vedachalam, N.; Murugesh, P.; Kaliyaperumal, P.; Kalaivanan, C.K.; Gnanadhas, T.; and Atmanand, M.A. [2015a]. Reliability analysis and integrity management of instrumented buoy moorings for monitoring the Indian seas. Society of Underwater Technology, Vol. 33, No. 2, pp. 115-126.Venkatesan, R.; Vedachalam, N.; Arul Muthiah, M.; Kesavakumar, B.; Sundar, R.; and Atmanand, M.A. [2015b]. Evolution of

reliable and cost-effective power systems for buoys used in monitoring Indian seas. Marine Technology Society Journal, Vol. 49, No. 1, pp. 71-87.Venkatesan, R.; Ramasundaram, S.; Sundar, R.; Vedachalam, N.; Lavanya, R.; and Atmanand, M.A. [2015c]. Reliability assessment of state-of-the-art real-time data reception and analysis system for the Indian Seas. Marine Technology Society Journal, Vol. 49, No. 3, pp. 127-134.Venkatesan, R.; Kadiyam, J.; Vedaprakash, L.; Senthilkumar, P.; and Lavanya, R. [2017]. Marine fouling on moored buoys and sensors in Northern Indian Ocean. Marine Technology Society, Vol. 5, No. 2, pp. 22-30.

rapid observations - national institute of ocean technology · 2018. 9. 26. · oyrgh journal of...

Documents