Today, the massive amount of data we collect often drives company decision-making processes. For example, in autonomous vehicles - such as those produced by Tesla and Google - so much information is collected each nanosecond for use in real-time decision making that these vehicles wouldn't be able to function without it. Autonomous vehicles continuously analyze several key data points even to do something as simple as changing lanes:
- Is there a car in front
- Is there a car in back
- Is there a car next to me
- Is there enough space in the next lane between the cars
Analysis has to occur at high speeds using sensory data - input from visual spectrum camera data, infrared camera data, distance sensors, LIDAR, radar and more. These sensors capture and feed data into a hardware-based decision-making engine. The decision engine uses Artificial Intelligence, Machine Learning, and algorithms that support other core approaches, to analyze sensor data and then continuously make the best decision.
This same data driven approach is used in conjunction with workflow automation by one of our customers. A leading traffic control solution provider uses sensor data and FlowWright to manage congested traffic in states around the world. FlowWright is the decision engine implemented to make traffic control and routing decisions: pre-defined traffic patterns are designed within FlowWright to execute based on decisions made, but all these decisions are made based on realtime data from deployed sensors.
Most devices today make decisions based on data without human input. A good example is the popular traffic app Waze: cell phone positions are sent anonymously to Google maps and Google then is able to highlight congested roads and highways on Waze and Google maps to help drivers find alternative routes. Without realtime and historic traffic data, applications such as Waze cannot make these decisions.
FlowWright is also used on dairy farms to fulfill feed rations for cows as a part of Sawtooth automation solutions. SawTooth makes use of FlowWright workflow processes to communicate with various devices through a Universal Distributed Controller (UDC). FlowWright sends commands to the UDC through a radio frequency integration layer, and also receives messages from the UDC through RF signals. FlowWright makes decisions based on incoming data messages. For example, based on the desired feed recipe, FlowWright will send a message to the UDC to pump 10 liters of Molasses, while the Molasses is being pumped, the UDC will be sending back data such as realtime volume and flow information. Because pumps and valves may not stop at exactly 10 liters, FlowWright makes adjustment to bring volume to the accurate amount and then workflow knows to move on to dispense the next material in the recipe based on process steps and decisions outlined in the dairy's workflow. Just as with autonomous cars and traffic control, making decisions based on realtime streaming data has applications in many/most industries.
Data is driving decisions....and can help your company. Want to learn more? Let's Talk.