Applications of Edge Computing - Revision history

Anasrin at 01:44, 25 April 2025

2025-04-25T01:44:53Z

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			'''Author: Saadhana Srinath'''

	==8.1 Introduction to UIoT and AUVs==		==8.1 Introduction to UIoT and AUVs==

Anasrin: /* 8.2 Edge Computing for AUVs: Benefits and Necessity */

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8.2 Edge Computing for AUVs: Benefits and Necessity

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 * Edge-Cloud Hybrid Architectures which provide real-time processing at edge for critical tasks and long-term analytics and model refinement is done in the cloud. This method allows flexibility by distributing the workload based on connectivity.
 * Neuromorphic Edge Processors: Chips that are inspired by the human brain that offer ultra-low-power AI at depth. This allows event-based processing for sensor inputs that aren’t as regular (for example: fault detecting sensors that are triggered only when there is a breach in a system).
 ==8.3 Challenges of Using Edge Computing with AUVs==

Anasrin: /* 8.5 Future Research Directions (Work in progress) */

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8.5 Future Research Directions (Work in progress)

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	: Inspired by marine life such as fish, octopuses, and jellyfish, bio-inspired underwater robots are being developed to operate more efficiently in complex terrains. When combined with edge computing, these robots would be able to adapt motion patterns in real-time to navigate turbulent currents, perform distributed sensing using soft, flexible sensor arrays and even execute silent, low-energy operations to avoid disturbing marine life. This would promise the advantage of stealth, mimicking natural organisms and their movements avoids detection and the disruption of the natural ecosystem. These robots could be used for delicate ecological monitoring, covert surveillance, and search-and-rescue missions in fragile environments where traditional AUVs may be too disruptive.		: Inspired by marine life such as fish, octopuses, and jellyfish, bio-inspired underwater robots are being developed to operate more efficiently in complex terrains. When combined with edge computing, these robots would be able to adapt motion patterns in real-time to navigate turbulent currents, perform distributed sensing using soft, flexible sensor arrays and even execute silent, low-energy operations to avoid disturbing marine life. This would promise the advantage of stealth, mimicking natural organisms and their movements avoids detection and the disruption of the natural ecosystem. These robots could be used for delicate ecological monitoring, covert surveillance, and search-and-rescue missions in fragile environments where traditional AUVs may be too disruptive.

	==8.5 Future Research Directions ~~(Work in progress)~~==		==8.5 Future Research Directions==

	There is still a lot of room for innovation and research as the relationship between edge computing and AUV technology develops. Even while existing solutions have shown that local processing is feasible and advantageous in underwater environments, there are still a lot of unanswered questions and a wide array of challenges meaning immense research potential. Here are some exciting future directions with a thought to make undersea operations more intelligent, robust, and energy-efficient.		There is still a lot of room for innovation and research as the relationship between edge computing and AUV technology develops. Even while existing solutions have shown that local processing is feasible and advantageous in underwater environments, there are still a lot of unanswered questions and a wide array of challenges meaning immense research potential. Here are some exciting future directions with a thought to make undersea operations more intelligent, robust, and energy-efficient.

Anasrin: /* 8.5 Future Research Directions (Work in progress) */

2025-04-25T01:26:23Z

8.5 Future Research Directions (Work in progress)

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	: - Improved structural integrity under high pressure		: - Improved structural integrity under high pressure
	: - Reduced biofouling		: - Reduced biofouling
	Research into nanocoatings and composite materials could increase the lifespan and reliability of AUVs.		: Research into nanocoatings and composite materials could increase the lifespan and reliability of AUVs.

	==References==		==References==

Anasrin: /* 8.5 Future Research Directions (Work in progress) */

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8.5 Future Research Directions (Work in progress)

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	==8.5 Future Research Directions (Work in progress)==		==8.5 Future Research Directions (Work in progress)==

			There is still a lot of room for innovation and research as the relationship between edge computing and AUV technology develops. Even while existing solutions have shown that local processing is feasible and advantageous in underwater environments, there are still a lot of unanswered questions and a wide array of challenges meaning immense research potential. Here are some exciting future directions with a thought to make undersea operations more intelligent, robust, and energy-efficient.

			*'''Energy Harvesting Mechanisms''' - With an aim to develop sustainable energy sources for AUVs and extend AUV operational time without the need for frequent battery replacements.
			: - Harnessing ocean thermal gradients
			: - Using microbial fuel cells
			: - Exploring kinetic energy from ocean currents

			*'''Advanced Materials for AUVs''' - This, as we have gone through in the previous sections, could solve a multitude of challenges that come with underwater conditions. Innovations in materials science can lead to:
			: - Enhanced corrosion resistance
			: - Improved structural integrity under high pressure
			: - Reduced biofouling
			Research into nanocoatings and composite materials could increase the lifespan and reliability of AUVs.

	==References==		==References==

Anasrin: /* 8.4.3 Other Emerging Technologies (Work in Progress) */

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8.4.3 Other Emerging Technologies (Work in Progress)

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	* Adaptability: Models improve as more AUVs contribute.		* Adaptability: Models improve as more AUVs contribute.

	===8.4.3 Other Emerging Technologies ~~(Work in Progress)~~===		===8.4.3 Other Emerging Technologies===

	As edge computing evolves further, its incorporation into underwater systems creates opportunities for crazy potential. Several state-of-the-art technologies are starting to use edge processing to improve autonomy, efficiency, and flexibility in underwater environments, going beyond traditional AUV operations and data dumping. Here are a few of such advancements.		As edge computing evolves further, its incorporation into underwater systems creates opportunities for crazy potential. Several state-of-the-art technologies are starting to use edge processing to improve autonomy, efficiency, and flexibility in underwater environments, going beyond traditional AUV operations and data dumping. Here are a few of such advancements.

Anasrin: /* 8.4.3 Other Emerging Technologies (Work in Progress) */

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8.4.3 Other Emerging Technologies (Work in Progress)

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	*'''Edge-Enabled Bio-Inspired Robotics'''		*'''Edge-Enabled Bio-Inspired Robotics'''
	Inspired by marine life such as fish, octopuses, and jellyfish, bio-inspired underwater robots are being developed to operate more efficiently in complex terrains. When combined with edge computing, these robots would be able to adapt motion patterns in real-time to navigate turbulent currents, perform distributed sensing using soft, flexible sensor arrays and even execute silent, low-energy operations to avoid disturbing marine life. This would promise the advantage of stealth, mimicking natural organisms and their movements avoids detection and the disruption of the natural ecosystem. These robots could be used for delicate ecological monitoring, covert surveillance, and search-and-rescue missions in fragile environments where traditional AUVs may be too disruptive.		: Inspired by marine life such as fish, octopuses, and jellyfish, bio-inspired underwater robots are being developed to operate more efficiently in complex terrains. When combined with edge computing, these robots would be able to adapt motion patterns in real-time to navigate turbulent currents, perform distributed sensing using soft, flexible sensor arrays and even execute silent, low-energy operations to avoid disturbing marine life. This would promise the advantage of stealth, mimicking natural organisms and their movements avoids detection and the disruption of the natural ecosystem. These robots could be used for delicate ecological monitoring, covert surveillance, and search-and-rescue missions in fragile environments where traditional AUVs may be too disruptive.

	==8.5 Future Research Directions (Work in progress)==		==8.5 Future Research Directions (Work in progress)==

Anasrin: /* 8.4.3 Other Emerging Technologies (Work in Progress) */

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8.4.3 Other Emerging Technologies (Work in Progress)

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	===8.4.3 Other Emerging Technologies (Work in Progress)===		===8.4.3 Other Emerging Technologies (Work in Progress)===

			As edge computing evolves further, its incorporation into underwater systems creates opportunities for crazy potential. Several state-of-the-art technologies are starting to use edge processing to improve autonomy, efficiency, and flexibility in underwater environments, going beyond traditional AUV operations and data dumping. Here are a few of such advancements.

			*'''Underwater Swarm Intelligence'''
			: Swarm intelligence is basically multiple AUVs working collaboratively to complete complex tasks. Particularly considering underwater environments, edge computing helps by enabling:
			:* Real-time data sharing among AUVs
			:* Distributed decision-making
			:* Adaptive mission planning

			It helps with efficiency and robustness of underwater operations, particularly in dynamic environments.

			*'''Underwater Augmented Reality (AR)'''
			: Integrating AR with edge computing is one of the most interesting tech that is currently being built. It offers better visualization of underwater structures leading to improved navigation for AUVs and real-time overlay of sensor data. This kind of tech would have heavy applications in tasks such as underwater construction, maintenance, and archaeological exploration.

			*'''Edge-Enabled Bio-Inspired Robotics'''
			Inspired by marine life such as fish, octopuses, and jellyfish, bio-inspired underwater robots are being developed to operate more efficiently in complex terrains. When combined with edge computing, these robots would be able to adapt motion patterns in real-time to navigate turbulent currents, perform distributed sensing using soft, flexible sensor arrays and even execute silent, low-energy operations to avoid disturbing marine life. This would promise the advantage of stealth, mimicking natural organisms and their movements avoids detection and the disruption of the natural ecosystem. These robots could be used for delicate ecological monitoring, covert surveillance, and search-and-rescue missions in fragile environments where traditional AUVs may be too disruptive.

	==8.5 Future Research Directions (Work in progress)==		==8.5 Future Research Directions (Work in progress)==

Anasrin: /* 8.3.4 Computational Constraints */

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8.3.4 Computational Constraints

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	* '''Memory Limitations'''		* '''Memory Limitations'''
	Most AUV edge systems have 4–16GB RAM vs. cloud servers' 100+GB. This is handled by a technique known as Tensor Slicing where large models are processed in chunks or by using MRAM caches which needs almost 10x lower power than SRAM for frequent data access.		: Most AUV edge systems have 4–16GB RAM vs. cloud servers' 100+GB. This is handled by a technique known as Tensor Slicing where large models are processed in chunks or by using MRAM caches which needs almost 10x lower power than SRAM for frequent data access.

	These constraints drive innovation in edge solutions, which we explore in Section 8.4 through state-of-the-art architectures like federated learning and hybrid systems.		These constraints drive innovation in edge solutions, which we explore in Section 8.4 through state-of-the-art architectures like federated learning and hybrid systems.

Anasrin: /* 8.3.3 Harsh Environments */

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8.3.3 Harsh Environments

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	:: 3. Self-Healing Epoxy resins are used to extend component lifespans threefold in saline environments by releasing corrosion inhibitors when damage occurs.		:: 3. Self-Healing Epoxy resins are used to extend component lifespans threefold in saline environments by releasing corrosion inhibitors when damage occurs.

	All of these techniques aim to enhance the durability of edge systems in harsh underwater conditions while maintaining operational efficiency.		Edge computing introduces critical thermal/mechanical challenges that require co-design of hardware and marine platforms. All of these techniques aim to enhance the durability of edge systems in harsh underwater conditions while maintaining operational efficiency. The optimal balance occurs at 2,000–4,000m depths using hybrid cooling strategies.

	===8.3.4 Computational Constraints===		===8.3.4 Computational Constraints===