3D Underwater Sensor Network Projects

3D Underwater Sensor Network Projects learn with the marine world that is below sea level. In light of this area, the underwater wireless sensor network is UWSN; as the name says, this network is made up of many types of sensors. Without a doubt, each sensor senses as per their function.

For what purpose this 3D-UWSN is there?

• Aquatic monitoring 
• Pipeline monitoring 
• AUV navigation 
• Disaster detection 
• Submarines movement 

   To begin with, the network composes of sensors, sink, and autonomous underwater vehicle (AUV) and etc. In general, the sensors sense the surrounding and transmit it to AUV and then to sink. In case if the AUV is not present, then the data from one sensor reach sink through multiple hops.  

Three Different Communication in 3D-UWSN 

• Inter-cluster communication 
• Intra-cluster communication 
• Anchor buoyant communication

   At this point, the common problem in this UWSN is the high consumption of energy, and it happens due to the below reasons. Further, the drain of energy in sensor nodes leads to reduce nodes’ lifetime.  

Critical Reasons for Drop-in Network lifetime

• The same sensors selected as relay frequently
• An excess number of retransmissions
• Hotspot problem 
• Collection of redundancy data with a larger size 
• Poor selection of a channel for transmission 
• Untrusted neighboring sensors nodes 

   Above all, the sensors have only the amount of energy within which it processes. So that in order to mitigate the energy consumption, the 3D Underwater Sensor Network Projects are here. 

How does the 3D reduce Energy in UWSN? Find the answers below. 

• Efficient deployment of sensors nodes 
• Accurate location prediction 
• Controllable topology changes 
• Clearly spots out the neighbor distance
• Exact detection of the line of sight signals

   To be clear, the AUV also reduces energy consumption, that is to say, AUV is not subject to the energy issue. Hence it revolves through a path at a certain sea level and gathers data from all the sensors and delivers it to the sink. 

3D-UWSN Processes that Improves network lifetime 

• Sensor Placement 
• The issue to solve: Not all the sensors are placed too closer
• Solution: Identify the optimum position for each sensor with respect to other
• Clustering 
• The issue to solve: Poor head selection and low, stable clusters
• Solution: Best cluster head selection
• Routing 
• The issue to solve: Longer hop counts, often breaking links 
• Solution: Select optimum and short routes 
• Sleep Scheduling 
• The issue to solve: Un-synchronized sleep states, longer timeslots for sleep  
• Solution: Adaptive sleep and wake-up slots as per the node characteristics
• Data Gathering
• Issue 1 to solve: Longer waiting time and redundant data 
• Solution 1: Use multiple AUVs 
• Issue 2 to solve: Longer delay due to fixed path
• Solution 2: Adaptive path based on data emergency

   On the one hand, the sensors in this type of network allow data exchange via Magneto-Inductive, Radiofrequency, acoustic, and optical. While in each, the range of data rate and coverage differs. In contrast, the AUV has more extensive coverage than the sensors. Thus it is able to collect data from a far sensor too using ultra-wideband communication. 

Five Finest Methods on 3D-UWSN Environment 

Data Gathering: Path planning of AUV in 3D-UWSN

• DENPSO
• EECPPA
• Greedy Path planning 
• Hierarchical DE method
• Q-learning algorithm 

Data Routing: Inter and Intracluster transmission in 3D-UWSN

• Dynamic FFRP
• Topology-Aware Reinforcement Learning
• Congruent Gravity Value
• Game-theoretic protocol
• Energy-efficient priority routing 

Cluster-based Routing in 3D-UWSN

• Multi-layer cluster with energy-based Routing
• UMOD-LEACH
• Hop constrained cluster routing
• Fuzzy c-means
• CRT2FLACO

Localization: Prediction of sensor location in 3D-UWSN

• Projective and ToA localization
• Belief propagation with cooperative 
• MDS-MAP algorithm 
• Doppler shift with modified GA 
• FA with Artificial Neural Network

Among all the above, localization is important that identifies the position using signals. From the signals, the time, angle, or other measures gives the exact position of a node. We provide Artificial Neural Network thesis topics on current trends. To this point, the 4D-UWSN is the growth in which the AUVs are remotely accessible.

   To this end, we are sure that you get enough points in this area. All of a sudden, you select your topic since soon it will become late even though we will not make things just like that. As soon as you come up with your area, we learn it and create new in it. So far, we run through all-new methods and hence select your zone once you see it.

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