I really like to make things efficient, effective and automated. My professional career has been about planning and scheduling, helping others make things run more efficient. I have created software tools to plan factories, schedule people, route trucks and planes and to make NASA robots and drones operate autonomous. In my last role as an employee I combined my knowledge in regression modeling, forecasting and optimization to price products of a large retail organisation based on billions of receipts. Today, one could say, I do something completely different. I don’t see it like that but I am helping organisations to connect devices to the internet. Let me try to explain why I think that makes sense for a planning and scheduling guy to run an IOT platform.

Gromit (red robot) in interaction with K9 and an astronaut in 2003 at the NASA Ames Roverscape

In planning and scheduling we match demand and supply. Something or someone needs resources typically with some time constraints. If you know exactly what you need to do we talk about scheduling and if you also need to determine what to do we talk about planning. Sometimes you just want a solution to make sure you can execute it. In other cases you want the best solution, you want the one that is most cost effective, robust, highest profit, lowest carbon footprint or whatever makes sense for you.

In all planning and scheduling problems you need to have rules, a goal and data. Of these three things, rules and the goal typically do not change that often but data can and will change. If you schedule a timetable for your buses in town the data does not change very often, maybe every quarter or so you make a new timetable based on new demand, roads and employees. If you plan and schedule an autonomous robot like a car, which continuously gets new data from its sensors, you plan every time you get new data that makes the previous plan inefficient or impossible to execute. This might involve planning and scheduling every 10 milliseconds. In both cases you need to solve a planning and scheduling puzzle but there is one big difference. In case of making a timetable you have a bit more time to solve the puzzle, in case of a robot you might have to plan an emergency stop because the robot is going to hit a pedestrian. Therefor in robotics we typically have multiple planning algorithms at the same time, reactive planner which determine what to do next and deliberative planners to make sure we reach the goals we have. The challenge is to keep them in sync.

To do robotics, which is a system that operates automatically to accomplish a goal, you need computing power, algorithms, a model, continuous updates of data and systems you can control to execute. This is where connecting devices to the internet becomes interesting. Whenever I was working in planning and scheduling for businesses we were solving problems for tomorrow and execution was done by people. I strongly believe that today we are bringing together trends that will enable us to run business processes autonomous. For this we need at least reliable continuous data  acquisition, it is for this reason I am now connecting devices to the internet. IOT not for the sake of connecting but to create the fuel for autonomous planning and scheduling.

MEUNGO provides the tools to connect devices, monitor and act on your data with a vision to robotize your processes.