indianocean.dev

#Indian Ocean Development Meta

#Indian Ocean | The third-largest ocean | Covering ca. 70.56 million square kilometers | Average depth 3,741 meters (12,274 feet) | Deepest point Java Trench 7,450 meters (24,442 feet)

#Photosynthesis

#Phytoplankton Production

#Marine Ecosystem

#Marine Food Web

#Tuna

#Shrimp

#Blue Whale

#Sei Whale

#Irrawaddy Dolphin

#Indian Ocean Humpback Dolphin

#Green Sea Turtle

#Dugong

#Sperm Whale

#FinWhale

#Lestherback

#Coral Reefs

#Seagrass Beds

#Mangrove Forests

#Coastal Forests

#Horn Of Africa

#Indo Burma

#Sundaland

#Spreading Ridges

#Carlsberg Ridge

#African Plate

#Indian Plate

#Antarctic Plate

#Australian Plate

#Seamount Chains

#Hotspots

#Extended Continental Shelf

#Open Ocean Up Welling

#Digital Twin of Indian Ocean

#1550nm LiDAR | Advantages: safety, range, and performance in various environmental conditions | Enhanced Eye Safety: absorbed more efficiently by cornea and lens of eye, preventing light from reaching sensitive retina | Longer Detection Range | Improved Performance in Adverse Weather Conditions such as as fog, rain, or dust | Reduced Interference from Sunlight and Other Light Sources | More expensive due to complexity and lower production volumes of their components

#ROS 2 | The second version of the Robot Operating System | Communication, compatibility with other operating systems | Authentication and encryption mechanisms | Works natively on Linux, Windows, and macOS | Fast RTPS based on DDS (Data Distribution Service) | Programming languages: C++, Python, Rust

#Dexterous robot | Manipulate objects with precision, adaptability, and efficiency | Dexterity involves fine motor control, coordination, ability to handle a wide range of tasks, often in unstructured environments | Key aspects of robot dexterity include grip, manipulation, tactile sensitivity, agility, and coordination | Robot dexterity is crucial in: manufacturing, healthcare, logistics | Dexterity enables automation in tasks that traditionally require human-like precision

#Agentic AI | Artificial intelligence systems with a degree of autonomy, enabling them to make decisions, take actions, and learn from experiences to achieve specific goals, often with minimal human intervention | Agentic AI systems are designed to operate independently, unlike traditional AI models that rely on predefined instructions or prompts | Reinforcement learning (RL) | Deep neural network (DNN) | Multi-agent system (MAS) | Goal-setting algorithm | Adaptive learning algorithm | Agentic agents focus on autonomy and real-time decision-making in complex scenarios | Ability to determine intent and outcome of processes | Planning and adapting to changes | Ability to self-refine and update instructions without outside intervention | Full autonomy requires creativity and ability to anticipate changing needs before they occur proactively | Agentic AI benefits Industry 4.0 facilities monitoring machinery in real time, predicting failures, scheduling maintenance, reducing downtime, and optimizing asset availability, enabling continuous process optimization, minimizing waste, and enhancing operational efficiency