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Thursday, 1.06.2023
eGovernment Forschung seit 2001 | eGovernment Research since 2001

The city as we know it is changing. Spurred by the pandemic, in which traffic was greatly reduced and outdoor spaces reclaimed, city councils are reimagining traditional concepts of urban planning. City planners are there by looking to design cities that are more sustainable and less congested, and they are utilizing artificial intelligence to assist. Enter the smart city.

By definition, a smart city is a technologically advanced urban area that uses sensors and other IoT devices to collect and analyze data, with the goal of optimizing certain aspects of the city. This can involve everything from identifying patterns in traffic congestion to controlling street lights based on night-time foot traffic.

But as smart cities pop up around the world, an interesting question remains: how will smart cities change logistics? Recent supply chain disruptions have led to widespread shortages of essential goods, but eventually smart cities may help to patch gaps in the chain.

In basic terms, a supply chain deals with the movement of products from A to B, and logistics are all about optimizing that flow. So, how will restructured smart cities affect this movement of goods? The answer lies in smart data.

Optimized deliveries

One area in which smart cities already excel is in reducing traffic congestion. Intelligent traffic control systems can provide real-time updates to drivers and advise individuals to follow the most efficient route. This can ensure no single route becomes too congested. Clearly, this is a benefit for the last mile of the supply chain.

There are already transportation policies in place that prioritize and deprioritize vehicles based on time of day. In downtown London, for instance, vehicles driving from 7 a.m. to 6 p.m. Monday through Friday are levied with a congestion tax.

In a smart city, the same concept could apply for e-commerce deliveries. Goods can be assigned specific movement times at periods of low-traffic congestion. At specified times in the day, freight vehicles will also be given priority over private vehicle traffic, and non-compliant vehicles could be fined.

What’s more, it’s likely that rideshare companies like Uber and Lyft will also get in on product distribution; they already do food deliveries, why not e-commerce order fulfillment? Since these ridesharing vehicles are already on the road, cities wouldn’t be adding many more vehicles to the street, even as the volume of e-commerce orders continues to skyrocket.

Currently, last-mile delivery accounts for 41% of total supply chain costs. The high price tag largely comes from goods being transported via inefficient routes to reach consumer doorsteps.


Currently, last-mile delivery accounts for 41% of total supply chain costs. The high price tag largely comes from goods being transported via inefficient routes to reach consumer doorsteps.

However, if manufacturers could bring the goods closer to consumers, the move would eliminate many last-mile costs. Therefore, we should expect a smart city to embrace more hyper-local fulfilment centers - aka micro-fulfillment centers.

Micro-fulfillment centers are smaller than traditional primary distribution centers, making it more practical to build a larger number of them closer to the consumer. They only hold enough stock for a few days, and what stock they do hold is largely based on AI predictions.

As a complement to these smaller but more widespread distribution centers, cities can also elect to construct smart lockers where consumers can pick up their goods, thus minimizing the environmental impact of last-mile delivery. Goods can be distributed straight from the micro-fulfillment center to centralized smart lockers, which theoretically should be located within a few miles of each other.

Consumers can pick up their goods from these lockers on the way to or from the office, or while they are out on other errands. The idea is to place smart lockers in high-traffic areas that commuters are likely to pass by naturally.

It’s about leveraging the commuter’s journey, and meeting people in exactly the right spot to reduce transport effort. The aim is to capitalize on the density of people at any given time during their daily activities.

The move toward predictive consumption

Smart cities deploy IoT sensors across the cityscape to gather data as part of a larger AI-based system. These systems can watch for floods, synchronize streetlights, provide real-time waiting times on public transport, monitor air pollution levels, and more.

In distribution, AI can collate this data to assist in the shift towards predictive consumption. The majority of stock will be based on current trends and data analytics. AI can gather information from the city and then determine what consumers are likely to order.

There will also be a large move towards recurring orders, in which consumers receive their orders on a regular basis: weekly, monthly, etc. AI can predict when consumers will run out of their chosen products and need to restock. Overall, this means the need for consumers to go to a physical brick and mortar store will be greatly diminished.

The overarching idea is to predict consumers’ needs and habits in order to boost efficiency and reduce time spent running errands or sitting in traffic: smart cities are all about optimizing the movement of products and people in the places they work, live, and play.

To accomplish such optimization, city infrastructure is being designed to capture a large volume of data; but it’s up to manufacturing and transportation companies to learn to put that data to use. That calls for a new type of supply chain that’s designed with AI in mind.


Autor(en)/Author(s): Tom Graham

Quelle/Source: The Fast Mode, 10.02.2023

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