Claims:WE CLAIMS
1) Our invention marine environment monitoring using wireless sensor networks is a marine environment is a difficult area for research due to the instability of the marine environment. Monitoring system for marine \ oceanic environment and protection is becoming a need in now a day to avoid major losses to the marine world. It is possible to use data collection technologies, such as ultrasonic, radar, machine vision, infrared, laser, and other integrated technologies such as wireless sensor networks (WSN), underwater marine environment detectors and computer data processing. Modern technologies are helping to know the difficulties in monitoring, managing and protecting marine safety. The proposed system focuses on early detection of marine environment threats by measuring various parameters of targeted area including turbidity, acceleration, humidity, wind/air speed and temperature using WSNs involved to protect oceanic marine world. The invented technology is also including a underwater Wireless Sensor Networks (UWSNs) contain several components such as vehicles and sensors that are deployedin a specific acoustic area to perform collaborative monitoring and data collection tasks. These networks are used interactively between different nodes and ground-based stations. Presently, UWSNs face issues and challenges regarding limited bandwidth, high propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints. In the last few decades, research community provided different methodologies to overcome these issues and challenges; however, some of the mare still open for research due to variable characteristics of underwater environment.
2) According to claim1# the invention is to a marine environment monitoring using wireless sensor networks is a marine environment is a difficult area for research due to the instability of the marine environment.
3) According to claim1,2# the invention is to a system for marine \ oceanic environment and protection is becoming a need in now a day to avoid major losses to the marine world.
4) According to claim1,2# the invention is to a In the last few decades, research community provided different methodologies to overcome these issues and challenges; however, some of the mare still open for research due to variable characteristics of underwater environment.
5) According to claim1,2,4# the invention is to a underwater Wireless Sensor Networks (UWSNs) contain several components such as vehicles and sensors that are deployedin a specific acoustic area to perform collaborative monitoring and data collection tasks and also these networks are used interactively between different nodes and ground-based stations. Presently, UWSNs face issues and challenges regarding limited bandwidth, high propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints
6) According to claim1,2,3,7# the invention is to a data collection technology, such as ultrasonic, radar, machine vision, infrared, laser, and other integrated technologies such as wireless sensor networks (WSN).
7) According to claim1,2,4,7# the invention is to a underwater marine environment detectors and computer data processing. Modern technologies are helping to know the difficulties in monitoring, managing and protecting marine safety.
8) According to claim1,5,6,7# the invention is to on early detection of marine environment threats by measuring various parameters of targeted area including turbidity, acceleration, humidity, wind/air speed and temperature using WSNs involved to protect oceanic marine world.
9) According to claim1,5,7# the invention is to a Maximum underwater deployments rely on acoustics for enabling communication combined with special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication. Date: 8/3/21
VIRENDRA RAMESH KOLI (ASSISTANT PROFESSOR)

Dr. SATISH SAMPATRAO SALUNKHE (PROFESSOR)

NISHIT NARENDRA PATIL (DIRECTOR - SYSTEM & DELIVERY)

, Description:FIELD OF THE INVENTION
Our Invention is related to a Marine Environment Monitoring using Wireless Sensor Networks.
FIELD OF THE INVENTION
Our Invention is related to a Marine Environment Monitoring using Wireless Sensor Networks.
BACKGROUND OF THE INVENTION
In order to save the marine environment, we must learn and understand the complexity of marine life and be aware of ocean environment. A key element of marine life conservation is the availability of an effective and collaborative water sensing, reasoning, and communication platform. This makes it possible for sensitive and visual devices to exchange data and signals, to connect to form network, collaboratively and locally justify its observation environment and function.
A wireless sensor network (WSN) consists of several dedicated sensor nodes with sensing and computing capabilities, which can sense and monitor the physical parameters and transmit the collected data to a central location using wireless communication technologies. WSN has several features available that include its working in uncontrollable environments, topological constrains, and limited computational and energy resources. Generally, WSN uses more sensors to improve system reliability and error tolerance. WSNs have been widely used in a variety of application areas related to water monitoring, forestry monitoring, industrial surveillance, agricultural surveillance, military surveillance, smart transport, smart homes, animal behavior monitoring, and disaster prevention as explained. Wireless Sensor Networks can be used in the field of explosives detection to save lives in terrorist operations.
Wireless Sensor Networks (WSNs) are a growing and rapidly growing technology, and their growth is due to the new applications they offer. Their ability to be distributed and withstand harsh conditions, and the effectiveness of human intervention make them especially prepared to be deployed in areas that are easily accessible. Deployment WSNs to marine environments is currently a challenge. The impact of the marine environment on sensors, electrical and mechanical devices cannot be underestimated.

For that reason, new techniques are needed to achieve goals like addressing network building problems, floating sensors, security policies, security, durability, etc. Existing solutions are generally ad-hoc as their composition depends on a variety of factors, such as marine ecosystem characteristics, land transfer times, installation range, and temporary data collection solution. Because of all these different possible scenarios, the design must be analyzed in advance and should reduce the cost of shipping and maintenance of the network.
In order to design an efficient, robust and self-sustaining WSN system needs to address many important challenges such as autonomy, scalability, adaptability and simplicity, construction and deployment of a sustainable and spectacular WSN marine ecosystem. Also, selection of analysis tool is crucial in WSN as various simulation tools impacts the performance in various parameters like transmission speed, packet delay, error control, and energy efficiency and key features as highlighted in One should pay attention to the following challenges that are different from those of the world as discussed in references:
The develop rapidly of microelectric technique, sensor technology and the network communications technology and increasingly mature, make that a large amount of volumes of manufacturing are little, low in energy consumption, having multiple function intelligent microsensors such as perception, computing capability and communication capacity simultaneously becomes possibility. The environment of these intelligence sensor nodes of new generation (abbreviation intelligent node) around can perception, and data are carried out certain processing, can intercom mutually by wireless communication module simultaneously. Wireless sensor network is exactly the network that is got up and constituted by a large amount of intelligent node joint managements. It is the emerging hot research field that is intersected by multidisciplinary height, is considered to one of most important technology of 21 centuries.
Wireless sensor network is data-centered, and strong robustness, network have automatic configuration, automatically recognition node, the management and the characteristics of highly cooperating automatically. Since the existence of great deal

of nodes information, collected information more accurately, more reliable. Network can adapt to the topological structure frequent variations, disposes simply, and cost is lower. Thereby can be widely used in military affairs, environmental monitoring, traffic administration, health care, manufacturing industry, field such as provide rescue and relief for disasters and emergencies.
At present, outdoor environment monitoring project and patented product based on wireless sensor network occur, Univ California-Berkeley Intel laboratory and Atlantic Ocean institute have united in Da Yadao (Great Duck Island) deploy a multi¬level wireless sensor network system, are used for monitoring the life habit of petrel on the island. Based on the ALERT system of wireless sensor network, realize the outburst prediction and the warning of mountain torrents by sensor monitors rainfall, river water level and soil moisture. U.S. DARPA has started Sens IT (Sensor Information Technology) plan, polytope transducer, reprogrammable general processor and wireless communication technology are combined, set up the ubiquitous wireless sensor network of a cheapness, be used to monitor information such as optics, acoustics, vibrations, magnetic field, humidity, pollution, poisonous substance, be used for military affairs.
Technique of sending and receiving message under the utilization of sound propagation in underwater environment is known as acoustic communication. Underwater sensor networks have number of vehicles and sensors that deploy in a specific area to perform collaborative monitoring and data collection tasks. Traditionally for the monitoring of ocean bottom, oceanographic sensors are deployed for recording data at a fix location and recover the instruments at the completion of task. The major disadvantage of traditional approach is lack of interactive communication between different ends, recorded data can never get during any mission, and in case of any failure recorded data will be destroyed.
Underwater Sensor Networks support a wide variety of applications; for example, aquatic surveillance, river and sea pollution discovery, monitoring, oceanographic data compilation, and commercial exploit the aquatic environment. Underwater

Sensor Networks can be utilized in any scenario from underwater warfare to the monitoring of environmental conditions. Underwater Sensor Networks face constraints like limited bandwidth, high propagation delay, 3D topology, and power constraints. Radio and optical waves are not feasible for communication at each point of ocean. Under the entire limitations underwater sensor networks can only utilize acoustic signal that is a technique which is utilized by nature from the birth of ocean. Speed of sound is considered constant in underwater environment.
However, speed of sound is affected by temperature, depth, and salinity of underwater environment. These factors produce variations in speed of sound in underwater environment. Underwater acoustic channel frequencies spectrum, especially on mid-frequencies, is heavily shared by various acoustic users in underwater environment. Still acoustic spectrum is temporally and spatially underutilized in underwater environment. Variable characteristics of underwater environment have become a challenge for utilizing acoustic channel. For example, multipath propagation results in fading and phase fluctuations; Doppler Effect is observed due to the movement of both the sender and receiver nods. Speed of sound and underwater noise are other factors that influences the performance of acoustic channel.
Underwater sensor networks nodes are not static like ground-based sensor networks nodes. Instead, they move due to different activities and circumstances of underwater environment, usually 2-3m/sec with water currents. Sensed data is meaningful only when localization is involved. Another major issue that is affecting underwater sensor networks is energy saving. Because of nodes mobility, the majority of offered energy competent protocols become inappropriate for underwater sensor networks. Different protocols regarding land-based sensor networks are, for example, Directed Diffusion, Gradient, Rumor routing, TTDD, and SPIN. However, because of mobility and rapid change in network topology these existing grounds-based routing protocols cannot perform efficiently in underwater environment. Optimal packet size is depending on protocol characteristic like offered load and bit error rate. Poor packet size selection decreases the

performance of the network throughput efficiency, latency, and resource utilization and energy consumption in multi-hop underwater networks can be greatly improved by a using optimum packet size.
PRIOR ART SEARCH
[1] “Marine Monitoring & Early Warning Detection using Wireless Sensor Networks: Challenges” Retrieved from: International Journal of Engineering Technology Science and Research, ISSN 2394 – 3386 Volume 5, Issue 1 January 2018.
[2] “Wireless Sensor Networks in Marine Environment Monitoring” Retrieved from: IJARIIE-ISSN(O)-2395-4396 Vol-2 Issue-3 2016.
[3] “Wireless Sensor Networks: Introduction, Advantages, Applications and
Research Challenges” Retrived from http://ijtir.hctl.org, Volume 14, April 2015.
[4] “A survey in wireless sensor network for explosives detection”, Ali Jameel AL-Mousawi , Haider. K. AL-Hassani.
[5] “Recent Advances and Future Directions on Underwater Wireless
Communications”, Mohammad Furqan Ali, Dushantha Nalin K., Jayakody, Yury Alexandrovich Chursin, Soféine Affes, Sonkin Dmitry.
[6] A.J. Watt, M.R. Phillips, C.E-A. Campbell, I. Wells, S. Hole, ‘Wireless Sensor
Networks for monitoring underwater sediment transport’. Science of the Total Environment 667 (2019) 160–165.
[7] Perez, C.A.; Jimenez, M.; Soto, F.; Torres, R.; López, J.A.; Iborra, A. A system for monitoring marine environments based on Wireless Sensor Networks. In Proceedings of the IEEE Conference on OCEANS, Santander, Spain, 6–9 June 2011; pp. 1–6.
[8] Carlos A. Trasviña-Moreno, Rubén Blasco, Álvaro Marco ,Roberto Casas,
Armando Trasviña-Castro, ‘Unmanned Aerial Vehicle Based Wireless Sensor
Network for Marine-Coastal Environment Monitoring’.
www.mdpi.com/journal/sensors (2017)
[9] “A Low-Cost Sensor Buoy System for Monitoring Shallow Marine Environments” Retrieved from: https://www.mdpi.com/1424-8220/12/7/9613.

[10] Matthew Dunbabin, Alistair Grinham, James Udy, “An Autonomous Surface
Vehicle for Water Quality Monitoring”, Australasian Conference on Robotics and
Automation (ACRA). [11] “A Practical Marine Wireless Sensor Network Monitoring System Based on
LoRa and MQTT”, Ao Huang, Mengxing Huang, Zhentang Shao, Xu Zhang, Di Wu,
Chunjie Cao College of Information Science and Technology, Hainan University,
Haikou, China. [12] “Applications of Wireless Sensor Networks in Marine Environment
Monitoring: A Survey”, Guobao Xu, Weiming Shen, Xianbin Wang, Sensors
(Basel). 2014 Sep; 14(9): 16932–16954. [13] “Wireless sensor networks for oceanographic monitoring: A systematic
review”, Cristina Albaladejo, Pedro Sánchez, Andrés Iborra, Fulgencio Soto, Juan
A. López, Roque Torres, Sensors (Basel). 2010; 10(7): 6948–6968. [14] Anand Nayyar, Valentina Emilia Balas, “Analysis of Simulation Tools for
Underwater Sensor Networks (UWSNs)”, IEEE.
[15] T. Rajasekaran and S. Anandamurugan , “Challenges and Applications of Wireless Sensor Networks in Smart Farming—A Survey: Proceedings of ICBDCC18”, © Springer Nature Singapore Pte Ltd. 2019.
[16] Shruti Sridharan, “Water Quality Monitoring System Using Wireless Sensor
Network”, International Journal of Advanced Research in Electronics and
Communication Engineering (IJARECE), Volume 3, Issue 4, April 2014.
[17] Hamzeh Varshovi, Yousef Seifi Kavian, Karim Ansari-Asl, “Design and implementing wireless multimedia sensor network for movement detection using FPGA local co-processing”, Published online 08 January 2019. @Springer Science + Business Media, LLC, part of Springer Nature 2019.
[18] Jingbin Hao, “Image processing and transmission scheme based on generalized Gaussian mixture with opportunistic networking for wireless sensor networks”, Hao EURASIP Journal on Wireless Communications and Networking (2015) 2015:226.
[19] Tie Qiu , Zhao Zhao, Tong Zhang, Chen Chen, C. L. Philip Chen Fellow, “Underwater Internet of Things in Smart Ocean: System Architecture and Open

Issues”, IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 16, NO. 7,
JULY 2020.. [20] Aoife Hegarty, Guy Westbrook, Damien Glynn, Declan Murray, Edin Omerdic,
Daniel Toal, “A Low-Cost Remote Solar Energy Monitoring System for a Buoyed
IoT Ocean Observation Platform”, Conference: 2019 IEEE 5th World Forum on
Internet of Things (WF-IoT'19), April 2019. [21] Matthias Tuma, Valdemar Rørbech, Mark K. Prior, Christian Igel, “Integrated
Optimization of Long Range Underwater Signal Detection, Feature Extraction,
and Classification for Nuclear Treaty Monitoring ”, IEEE Transactions on
Geoscience and Remote Sensing 54(6):1-11, June 2016. [22] Khalid Mahmood Awan, Peer Azmat Shah , Khalid Iqbal, SairaGillani, Waqas Ahmad, Yunyoung Nam “Underwater Wireless Sensor Networks: A Review of Recent”, Wireless Communications and Mobile Computing Volume 2019.
[23] Emad Feldman, Faisal Karim Shaikh, Umair Mujtaba Qureshi “Underwater Sensor Network Applications: A Comprehensive Survey”,Article InformationVolume: 11 issue: 11,November 1, 2015.
[24] Jun-Hong Cui, Jiejun Kong, Mario Gerla, Shingle Zhou, “Challenges: Building Scalable and Distributed Underwater Wireless Sensor Networks (UWSNs) for Aquatic Applications” UCONN CSE Technical Report, September 2005.
[25] Liu Lanao Zhou Shingle Cui Jun‐Hong, “Prospects and problems of wireless communication for underwater sensor networks” Published on 31 July 2008. [26] Guying-ping, Yangban, HuRong-lin, “Analyzing the Performance of Channel in Underwater Wireless Sensor Networks (UWSN)” Procedia Engineering Volume 15, 2011.
[27Stefano Basagni, Chiara Petrioli, Roberto Petroccia, Milaca Stojanovic, “Optimized Packet Size Selection in Underwater Wireless Sensor Network Communications,” IEEE, 2012.
[28] S Basagni, C Petrioli, R Petroccia, “Choosing the packet size in multi-hop underwater networks,” IEEE, 2010

[29] Ian F. Akyildiz, DarioPompili, Tommaso Melodia, “Challenges for efficient
communication in underwater acoustic sensor networks”, Embedded sensor
networks and wireless computing, Volume 1 Issue 2, July 2004.
[30] E Harland, SAS Jones, T Clarke, “SEA 6 Technical report: Underwater ambient
noise,” March 2009.
[31] Kenneth A. Perrine; Karl F. Nieman; Terry L. Henderson; Keith H. Lent; Terry J.
Brudner; Brian L. Evans, “Doppler estimation and correction for shallow
underwater acoustic communications”, IEEE 2010.
[32] Zhang Xiao and Han Xiao, “Study on Doppler effects estimate in underwater
acoustic communication”, he Journal of the Acoustical Society of America 133, 3463
(2013)
OBJECTIVES OF THE INVENTION
1. The objective of the invention is to a marine environment monitoring using wireless sensor networks is a marine environment is a difficult area for research due to the instability of the marine environment.
2. The other objective of the invention is to a system for marine \ oceanic environment and protection is becoming a need in now a day to avoid major losses to the marine world.
3. The other objective of the invention is to a data collection technology, such as ultrasonic, radar, machine vision, infrared, laser, and other integrated technologies such as wireless sensor networks (WSN).
4. The other objective of the invention is to a underwater marine environment detectors and computer data processing. Modern technologies are helping to know the difficulties in monitoring, managing and protecting marine safety.
5. The other objective of the invention is to a early detection of marine environment threats by measuring various parameters of targeted area including turbidity, acceleration, humidity, wind/air speed and temperature using WSNs involved to protect oceanic marine world.
6. The other objective of the invention is to a Maximum underwater deployments rely on acoustics for enabling communication combined with

special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication
SUMMARY OF THE INVENTION High Water Resistance
The sensors of the marine monitoring system require high levels of water resistance.
Stronger Robustness
The marine monitoring system requires strong forces and needs to be robust, because the marine environment with waves, ocean currents, waves, storms, ships, etc., is aggressive and complex, and may impact in displacement of system.
High Energy Consumption
Energy consumption is high due to long range and constant communication which needs to be taken care of by using renewable energy resources.
Unstable Line-of-Sight
The oscillation of the radio antenna can cause a more unstable line-of-sight between transmitters and receivers.
Sensor Node Size and Placement.: Sensor node size and placement is one of the critical issues. The size of the sensor node must be small and ready to be deployed. The life span of WSN is largely dependent on the sensor implantation.
Transmission Range
Data transmission failure in WSN occurs due to ecological effects. In the event of data transmission, most of the wireless sensor communication technologies covers only short range. In most of the cases, Buoy-based coastal monitoring systems are suitable for monitoring and controlling the status of waters, as installation and

maintenance are simple to perform and not very costly. Moreover, the technology makes it possible to automate the instrumentation and sample-taking and variable adjustment of sampling frequency. The main advantage of marine measuring systems implemented on wireless sensor networks is the possibility of remotely accessing the information recorded in the buoy from a base station.
The Wireless Integrated Network Sensor Next Generation (WINS NG) sensors and nodes provide distributed network and Internet access to sensors, controls, and processors that are deeply embedded in equipment, facilities, and the environment. The WINS NG network is a new monitoring and control capability for applications in such sectors as transportation, manufacturing, health care, environmental monitoring, and safety and security. Wireless Integrated Network Sensors combine microsensor technology, low power signal processing, low power computation, and low power, low cost wireless (and/or wired) networking capability in a compact system. The WINS NG networks provide sensing, local control, and embedded intelligent systems in structures, materials, and environments.
The WINS NG networks provide a more efficient means of connecting the physical and computer worlds. Sensor nodes self-organize to form a network, and seamlessly link to the Internet or other external network via a gateway node, which can be of the same type or different from the sensor nodes. The sensor nodes can themselves be of the same type or a variety of types. Network resources such as databases are available to the sensor network and the remote user through the Internet or other external network.
The sensor nodes are constructed in a layered fashion, both with respect to signal processing and network protocols, to enable use of standard tools, ease real-time operating systems issues, promote adaptability to unknown environments, simplify reconfiguration, and enable lower-power, continuously vigilant operation. High reliability access to remote WINS NG nodes and networks enables remote interrogation and control of the sensor network; this reliability is achieved using a plurality of couplings, with automatic adjustment of the processing and communications to deal with failures of any of these couplings. Linkage to

databases enables extra resources to be brought to bear in analysis and archiving of events, and database methods can be used to control the entire network in a more transparent manner, to enable more efficient control and design.
The WINS NG technology incorporates low-energy circuitry and components to provide secure communication that is robust against deliberate and unintentional interference, by means for example of new algorithms and antenna designs. The network can further include distributed position location functionality that takes advantage of the communications and sensing components of the individual nodes, to simplify deployment and enable location of targets.
The sensor nodes can be of a variety of types, including very simple nodes that may, for example, serve as tags. These nodes can be constructed on flexible polymer substrates, a material that may be used for a wide variety of synergistic uses. This construction results in more compact and capable systems, providing sensors, actuators, photo-cells and structural properties. Compact antennas for such packages have been developed. The network includes both wireless and wired communications capability, using a common protocol and automatically choosing the more secure or lower power mode when it is available, providing more robust and long-lived operation in potentially hostile environments. The network enables a wide variety of users with different data rate and power requirements to coexist as, for example, in wired or wireless mode vehicular applications. The flexibility of the design opens a wide variety of applications.
In another aspect, the layering of the WINS nodes with respect to processing and signal processing facilitates the rapid design of new applications. Layering further facilitates self-organization of complete applications, from network connections through to interoperation with remote databases accessed through external networks such as the Internet. With this layering, the cost of deployment is radically reduced even while remote operation is enabled.
BRIEF DESCRIPTION OF THE DIAGRAM
Fig 1- Block Dig. Of Sensor Unit

Fig 2 - Block diagram of proposed system
FIG. 3 is a prior art Adaptive Wireless Arrays for Interactive Reconnaissance,
surveillance and target acquisition in Small unit operations (AWAIRS) sensor
network.
FIG. 4 is an example of a prior art sensor network using distributed signal
processing.
FIG. 5 is an example scenario for self-organization in a prior-art sensor network
such as AWAIRS.
Fig 2.1: Two-Dimensions Underwater Sensor Networks.
Figure 2.2Three-DimensionsUnderwater Sensor Networks
Fig 3.1 – UWSN Applications
DESCRIPTION OF THE INVENTION
The proposed system focuses on early detection of marine environment threats by measuring various parameters of targeted area including turbidity, acceleration, humidity, wind/air speed and temperature using WSNs involved to protect oceanic marine world. The invention is is no escaping fact that a huge amount of unexploited resources lies underwater which covers almost 70% of the Earth. Yet, the aquatic world has mainly been unaffected by the recent advances in the area of wireless sensor networks (WSNs) and their pervasive penetration in modern day research and industrial development. The current pace of research in the area of underwater sensor networks (UWSNs) is slow due to the difficulties arising in transferring the state-of-the-art WSNs to their underwater equivalent.
System Analysis
The aim of this project is to design and manage the Wireless Sensor Network (WSN) which helps to monitor the marine environment with the help of information received from sensors, in order to maintain the water source within the standard described and be able to take the necessary steps to restore the marine ecosystem. The proposed system can be mainly classified into three different units

Sensor Unit:
In the sensor unit, five types of sensors; Turbidity sensor for water turbidity /purity, Accelerometer for sensing acceleration, Humidity sensor detecting vapor volume of water in air, Air-Speed sensor for sensor /wind speed and direction of air, and temperature sensor are used.
All sensors use the battery in their operation. The sensor information is then converted into an electrical signal and transmitted to a microcontroller or microprocessor that can be accessed for further testing.
Wireless Sensor Node:
The wireless sensor node in the proposed system contains a sensory unit as mentioned above; a microcontroller with the functions of signal modification, data transfers, network management and transmitting radio frequency for long range communication.
Base Monitoring Station
The base station / reception station consists of receiving module that receives the data sent from the sensor nodes i.e. transmitting devices. Data obtained from transmitting areas is sent to a computer and the data obtained is displayed using a GUI built into the base monitoring station. The following figure 2 shows a general block diagram of the and below is the working of proposed system.
A. Firstly, all the sensors present in the sensor unit such as Turbidity, Humidity,
Air Speed, Accelerometer, Temperature sensors will sense the data from the
monitoring location.
B. Power supply for the sensor devices will be provided using batteries and to
make the device energy efficient solar panels are used.
C. Output data i.e. recorded data from the sensors will be transmitted after
processing using microcontrollers.
D. To increase the transmission range and to make system more accurate boat
circuit is used which will perform the re-transmission of signals in case
distance between transmitter and receiver is greater.

E. In other cases, boat circuit will be used to check if sensed values are correctly
being passed to monitoring station.
F. It can also be used to detect borders of surveillance are if required.
G. At monitoring station, the received data will be sent to user’s PC serially,
which can be accessed using user interface software created using VB6.
Use of solar panels and boat circuit make the proposed system energy efficient, accurate in terms of data transfer and reliable for long range communication and capable to work in harsh marine environments.
FIG. 3 is a prior art AWAIRS sensor network 300. The sensor nodes 302 of the AWAIRS network 300 include extensive signal processing in order to reduce communications. The sensor nodes 302 can include multiple processors of differing types, and can progress through several levels of signal processing in performing target detection and identification. The sensor nodes 302 can also include ranging devices for position location. Moreover, the sensor nodes 302 enable cooperative behaviors such as data fusion, beamforming, and cooperative communications. The network 300 is self-organizing, and will establish routing to minimize energy consumption. Multihop routing is supported. The network 300 does not require long-range links, but can include them, and may directly connect to a computer and user interface 306. Moreover, the sensor nodes 302 may interact with a number of user interfaces 306. Data aggregation may be included in a path from the remote sensors to an end destination.
FIG. 4 is an example of a prior art sensor network 400 using distributed signal processing. Source 1 emits a signal that is detected by sensors 1, 2, and 3. Sensor node 1 can become designated as a fusion center to which some combination of data and decisions are provided from sensor nodes 2 and 3. Sensor node 1 then relays the decision towards the end user using a specific protocol. Source 2 emits a signal that is detected by sensor node 4. Sensor node 4 performs all processing and relays the resulting decision towards the end user.
Sensor node 6 receives the signals emitted by both sensors 1 and 4. Sensor node 6 may pass both decisions or perform some further processing, such as

production of a summary activity report, before passing information towards the end user. The end user may request further information from any of the sensor nodes involved in processing data to produce a decision.
FIG. 5 is an example scenario for self-organization in a prior-art sensor network such as AWAIRS. In the limit of short hops, the transceiver power consumption for reception is nearly equal to that of transmission. This implies that the protocol should be designed so that radios are off as much of the time as possible, that is, the Media Access Controller (MAC) should include some variant of Time-Division Multiple Access (TDMA). This requires that the radios periodically exchange short messages to maintain local synchronism. It is not necessary for all nodes to have the same global clock, but the local variations from link to link should be small to minimize the guard times between slots, and enable cooperative signal processing functions such as fusion and beamforming. The messages can combine health-keeping information, maintenance of synchronization, and reservation requests for bandwidth for longer packets. The abundant bandwidth that results from the spatial reuse of frequencies and local processing ensures that relatively few conflicts will result in these requests, and so simple mechanisms can be used.
To build this TDMA schedule, the self-organization protocol combines synchronism and channel assignment functions. It supports node-to-node attachment, node-to-network attachment, and network-to-network attachment. The distributed protocol assigns progressively less of the TDMA frame to invitations and listening as the network becomes more connected. The result is contention-free channel assignments for the sensor nodes in a flat (peer-to-peer) network, where the channels consist of some combination of time and frequency assignments. Invitation slots are allocated even when the network is mature to allow for reconfiguration.
Upon construction of the set of links, the routing is then built. If the nodes are powered by batteries, the network will have a life-cycle which begins in a boot-up, proceeds through a phase of maximum functionality, decline, and finally failure. Every bit that is exchanged hastens the end of the network. Particular nodes may

be more heavily stressed by traffic than others (e.g., those in the vicinity of a gateway or other long-range link). Thus, routing protocols must to some extent be energy-aware, to sustain useful operation as long as possible. The minimum energy path is not necessarily the most desirable. Rather routes are ordinarily chosen to extend operation, although high priority messages may be routed for low latency, even if this exhausts precious network resources. The predictability of flow to and from a relatively small number of gateways enables infrequent construction of sets of paths to these data points, minimizing overhead.
Underwater network’s physical layer utilizes acoustic technology for communication. Limited bandwidth, capacity, and variable delays are characteristics of acoustic technology. Therefore, new data communication techniques and efficient protocols are required, for underwater acoustic networks. Designing the network topology requires significant devotion from designer, because underwater network performance is generally depending upon topology design. Network reliability should increase with efficient network topology and network reliability should also decrease with less efficient topology. Energy consumption of efficient network topology is highly less as compared to incorrect and less efficient topology design of underwater network. Underwater wireless Sensor can be categorized into following two types-(1) Underwater Sensor Networks in Two-Dimensions:
Deep ocean anchors are utilized for collection of sensor nodes in two-dimensional underwater sensor network architecture. Anchored underwater nodes use acoustic links to communicate with each other or underwater sinks. Underwater sinks are responsible to collect data from deep ocean sensors and provide it to offshore command stations, using surface stations. For this purpose, underwater sinks are provided in the company of horizontal and vertical acoustic transceivers. Purpose of horizontal transceivers is to communicate with sensor node, to collect data or provide them commands, as have been received by offshore command station, although vertical transceiver is used to send data to command station. Because ocean can be as deep as 10 km, vertical transceiver should contain enough range.

Surface sink that is equipped with acoustic transceivers has the capability to manage parallel communication, by means of multiple organized underwater sinks. Surface sink is also equipped through extensive range radio frequency transmitters, to communicate with offshore sinks.
Underwater Sensor Networks in Three Dimensions:
Activity required to present three-dimensional environments new architecture which is known as underwater three-dimensional networks is used. Sensor nodes float at different depth to monitor a specific activity in three-dimensional underwater networks. Traditional solution regarding underwater three-dimensional sensor networks is the use of surface buoys that provide ease in deploying such kind of network. But this solution is vulnerable to weather and tampering. Also, effortlessly can be discovered and disabled by enemies in the scenario of military operation. In underwater three-dimensional sensor networks architecture, ocean bottom is utilized to anchored sensor nodes. Depth of these nodes is controlled using wires which are attached with these anchors. Major challenge regarding such network is influenced by the current properties of the oceans.