Data Science for Truckers

Kirby Urner
Jul 28, 2018 · 5 min read

One might think the trucker population would be where the Global U was focussing its outreach, as here one has the PWS (personal workspace) writ large, the tractor cab.

https://flic.kr/p/26uB1Eh

High schoolers lag far behind in that some inherit a PWS as a family entitlement (a teenager gets her own room) but the school itself, unless a boarding school, a high priced one, is not expected to provide a secure work and study space on a per student basis. You might have roommates.

A PWS for solo work / study is what we usually call an “office” and those need to be earned according to many religions (ways of life). No entitlements need apply, unless, that is, you come from one of those families that owns lots of businesses. Some children expect to be endowed with a PWS their whole lives. Many more do not, as of the current dark ages.

Truckers already have an office, a lot like a skyscraper cubicle, except it’s not in a static matrix reached by elevator. The trucker’s office on wheels, with a dashboard and controls, is more like the pilot’s cockpit, also a PWS per GST’s understanding (GST stands for General Systems Theory, and competes with Economics to explain bread and butter issues).

True, if you’re driving solo, you can’t be reading lots of scholarly articles at the same time. Your eyeballs are needed elsewhere. However, the aural track (e.g. books on tape) has proved itself over and over to be of sufficient bandwidth to pump out a lot of curriculum.

Many old timer politicians in Washington, D.C. listened to cassette tapes in their youth, by Newt Gingrich and others, as a means of developing their careers. When they got together, they discovered already having enough ideology in common to effect political change. Having a shared technical language, ideological or not, is somewhat a prerequisite for establishing a professional culture. Truckers already have that too, even if they don’t share the same politics at every turn.

Drivers already know about routes, loads, how time and distance relate to fuel consumption, different ways of working, the importance of sleep and some exercise.

The long haul electric truck is still a thing of the future as of this writing, and according to many engineers is an oxymoron (a contradiction in terms).

Consider that your battery powered tractor drives only relatively short hauls, but then it’s easy, at a switching station, to grab a freshly charged cab. The tractors may need some hours to recharge, but a driver might pick up a fully charged one only minutes after dropping one off.

Are you then continuing to haul the same freight, when you hop to a next cab? Maybe, maybe not. The better routing algorithms give us the ability to implement new games. A shipping container after weeks at sea, may not contain any perishable goods that the low cost of shipping relates to making room for high rates on express, the same games we play now.

Scenario: You might pilot five different trucks in one day, hopping between switching stations, none more than a hundred miles apart, and taking a last load to its final destination. A ride service meets you there for a trip into town. Tomorrow, you’ll be back on a university campus, continuing with some lab studies. At the end of the week, you have a sequence of hops that will take you five hundred miles away. You’re a nomad, but not without favorite haunts. Sound good?

Let’s assume you’ve tuned in to a podcast version of this Medium article. Your plan is to learn about how the cloud works, in terms of containers (such as Docker and Kubernetes), moving data around, machine learning.

Amazon Web Services (AWS) is not unfamiliar to you. As a trucker, you already have a number of apps on your dashboard (and maybe on other devices), that keep you connected to the market.

https://flic.kr/p/6scpLi

Whether a freelancer or fleet driver, your business communications get routed through the cloud, putting and getting data regarding loads, trips, hops, those scheduled in the future, and those already in the rear view mirror.

On other tapes, we dove into Structured Query Language (SQL) which was expected to revolutionized the office (PWS) by giving secretaries better access to their secrets (company files).

Learning SQL did not require too much in the way of clerical skills, but the full language was not just about filing data, but about granting permissions. One creates users with stipulated restrictions on access.

Management saw itself as king of the hill in this regard, so it took awhile to pry SQL skills loose from the DBAs (database administrators) and spread them more evenly among the offices. These days, SQLite is a part of the standard Python library, downloadable for free at your next truck stop.

As a driver, you may sense some of these same restrictions on access bedevil you at work. The design of communications circuits inside organizations is part of what we call systems architecture. Systems designers need to learn about existing systems, and their successes failures, before reinventing every wheel.

A lot of what we’re learning in this course is why so many companies are short lived, even shorter lived than individual people. A lot of them get the communications part wrong and bottleneck in offices that prove irreplaceable once broken.

In a future podcast, our focus will be NoSQL, a complementary implementation of the “filing” concept that requires less structure among its records.

https://flic.kr/p/4HfejV

You might have heard of JSON. We have some interesting videos on that, available at your hotel room, for credit.

Once you have the basics of storage and retrieval, understand how data persists and moves around, you’ll be ready for our data harvesting and analysis components.

Apache Spark will be on your radar shortly, if it isn’t already.

That’s enough for one episode.

Data Science for Truckers is a Sister Cities Project, out of Portland, Oregon. If you’re reading this on Medium, you might want to link to some background articles on GST and the Global U, in case that’s unfamiliar material.

We’ll see you down the road!

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