Arduino Tron AI-IoTBPM :: Arduino Drools-jBPM
Arduino Tron AI-IoTBPM
Internet of Things Artificial Intelligence
- An inference model provides a conclusion reached on the basis of evidence and reasoning.
In the Internet of Things (IoT), as more and more devices and pieces of software interconnect, a great necessity arises for the systems that allow complex situations to be detected in a simple collaborative way by people and devices and be able to react quickly upon detection of these situations.
Internet of Things (IoT) provides lots of telemetry and sensor data; however, the data points by themselves do not provide value unless they can be annualized and turned into actionable, contextualized information. Big data and data visualization techniques allow us to gain new insights by batch-processing and off-line analysis. Real-time sensor data analysis and decision-making are often done manually but to make it scalable, it is preferably automated. Artificial Intelligence (AI) provides us with the framework and tools to go beyond trivial real-time decision and automation use cases for IoT.
With AI-IoTBPM (Artificial Intelligence – Internet of Things) it is important to understand the difference and relationship between big data and real-time event reasoning, known as temporal reasoning. Big data analysis of sensor data retrieved from many IoTBPM devices provides statistical information on particular components and data points. Decision making will allow deciding whether there is a need for maintenance of one particular component. With temporal reasoning, IoT sensors provide information that Drools AI is acted on immediately. For example; in Drools AI-IoT, judging impact avoidance of a vehicle and making course adjustments is an example of AI temporal reasoning or a rational agent.
The AI-IoTBPM rational agent is a central concept in artificial intelligence. An agent is something that perceives its environment through sensors and acts upon that environment via actuators, servos or motors. For example, a robot may rely on cameras as sensors and act on its environment via motors.
A rational agent is an agent that acts, and that does ‘the right thing.’ The right thing depends on the performance criterion defined for an agent, but also on an agent’s prior knowledge of the environment, the sequence of observations the agent has made in the past and the choice of actions that an agent can perform. The AI BRMS Drools itself is the heart of the agent that computes, and reasons based on the available data and its knowledge of the IoT sensors on the environment.
AI IoT Ontology-IoT Artificial Intelligent Architecture
1. The branch of metaphysics dealing with the nature of being.
2. A set of concepts and categories in a subject area or domain that shows their properties and the relations between them.
Drools AI-IoTBPM – This orchestration of IoT Devices gives us the ability for action after our AI Decision in our physical-world.
AI-IoTBPM Internet of Things Drools Artificial Intelligence (AI) Drools and BPM (Business Process Management). Internet of Things Artificial Intelligence Conclusion – An inference model provides a conclusion reached on the basis of evidence and reasoning.
The AI-IoTBPM Rational Agent is a central concept in artificial intelligence that Executive Order Corp has developed in our IoTBPM platform that uses concepts of AI and applied those to the use case of Smarter decision making in IoT and BPM (Business Process Management).
Real-time sensor data analysis and decision-making are often done manually but to make it scalable, it is preferably automated. AI provides us with the framework and tools to go beyond trivial real-time decision and automation use cases for IoT.
Executive Order Corp. has developed both a CLOUD-based and a STREAM-based architecture that observes its environment via IoT defined sensors and acts on its environment through AI BRMS Drools-jBPM software, arriving at conclusions reached on the basis of evidence and reasoning.
Executive Order Corp. has developed an IoTBPM platform that uses concepts of AI and applied those to the use case of smarter decision making in IoT.
“If a machine thinks, then a machine can do.” – Steven Woodward
“It’s not you interacting with the machine; it’s the machine interacting with you.” – Steven Woodward