New Autonomous Paradigms

Above Sky (AS) Above the sky provides consistent opportunities at many different altitudes around the planet earth.

Algorithm Determined Outcomes (ADO) Algorithms are engineered to deliver features and functionalities desired by customers. Once the algorithms are implemented, they are not visible, but their outcomes are known as algorithm determined outcomes.

Algorithm Engineering (AE) The algorithm engineering involves creation of invisible flow design, deep learning models and log management.

Autonomous Actions (AA) The actions taken by machines by processing data, algorithms, learning capabilities and contextual integrations.

Autonomous Lifecycle (AL) Autonomous lifecycle includes mechanism for creation, connection and cease the entities such as self-sustaining products and evolving ecosystems.

Autonomous Vehicles (AV) Autonomous vehicles operate on land, in sea and above sky leveraging autonomous architecture and solar energy. Contextual Integrations (CI) Contextual integrations occur with the context of self-sustaining products, evolving ecosystems and autonomous lifecycle.

Contextual Integrations (CI) The integrations created, used or maintained in three primary contexts include self-sustaining products, evolving ecosystems and autonomous lifecycle.

Data Driven Decisions (DDD) Data is used to explore multiple options and generate outcomes through scenario analysis. The outcomes then considered by management in larger context before making decisions.

Data Engineering (DE) Data Engineering is the most expansive layer that embodies creation and ingestion of data while maintaining both physical and digital synchronization.

Data Generation (DG) Data is generated from variety of sensors, events, analysis or reports. Data Harmonization (DH) An approach to determine and implement solution to harmonize the data by resolving issues that occur in twinization, search or data flow.

Data Twinization (DT) A process that ensures each piece of data has twin where physical data is converted to digital replica and digital data is converted to action in physical world.

Deep Learning Models (DLM) Deep learning models that can perform real time analysis, feed the future machine, trigger the issue resolution or alerts for change management.

Digital Signal (DS) The value created by digital systems and digital twins of physical systems are called digital signals.

Embedded Mechanics (EM) The mechanical systems that are embedded in autonomous systems.

Evolving Ecosystem (ES) Evolving ecosystem has dynamic capabilities where various companies, products, technologies can collaborate.

Flow Design (FD) Flow designs generate flow charts including decision making nodes and action blocks for physical hardware and digital software.

In Water (IW) In water autonomous vehicles are widely used for logistics as well as long cruise stays.

Inputs Forms Choices (IFC) Machine learning capabilities feed on multiple input forms. The choices of input forms include physical action, written paper or digital signal.

Log Management ( LM) Log management practice that registers the event and respective data.

Machine Learning Capabilities (MLC) The capability of machines to learn from the data driven decisions as well as algorithm determined outcomes.

Machine Learning Engineering (MLE) The machine learning capabilities that continuously cognize data as well as recognize algorithms components while automatically advancing both data engineering and algorithm engineering capabilities.

On Land (OL) On land autonomous vehicles use infrastructure like road network.

Physical Action (PA) The physical world consists of senses, sensors, mechanical as well as infrastructure.

Physical and Digital Synchronization (PDS) A process where the autonomous system ensures creation, modification or deletion so that every data point has both physical and digital twins.

Post Processing Analysis (PPA) After the process or operation is executed the data and algorithms need to go through structured process and provide inputs to all the disciplines in autonomous architecture.

Self-Sustaining Product (SSP) Self-sustaining product has autonomous capabilities to perform desired functions and include all layers of autonomous architecture.

Software Defined Integrations (SDI) The integrations that are invisible because software processing is built in.

Written Paper (WP) Written paper can be handwritten, printed or colorful. Paper has been the most matured mechanism of communication and sharing the learnings.