Spatially Intelligent Warehouses

Mark Altaweel

Updated:

We don’t usually consider large warehouses, increasingly becoming important in our e-commerce driven consumerism, as having a high degree of autonomous, spatially managed systems that can understand spatio-temporal changes to warehouse inventory. Increasingly, however, as the Covid pandemic has showed, this is particularly important when supply chains become strained and sometimes critical products are in short supply.

To create an economy that does not over- or under-produce, intelligent, spatially aware warehousing management systems will need to be widely used.

Adopting Spatially Intelligent Warehouses

Technologies called warehouse spatial intelligence (WSI) have been developed and increasingly rolled out in warehouses over the course of the past year. With increased availability of wireless sensors, HD cameras, and cloud-based services, including 5G and internet of things (IoT) devices now becoming more available in parts of the world, we are seeing warehouses shift from pure barcode data capture systems to those that operate on coordinated sensors and artificial intelligence decision-making.  

USGS Core Research Center warehouse.. Photo: USGS, public domain

Software is also increasingly being integrated with other applications to allow automated spatial tracking and mapping of objects, including automated segmentation and object identification tools, that can help to track where shortages in inventory might develop.

In fact, such tools enable forecasting of shortages well before supplies end for given products, helping to send automated messages to suppliers to send products in advance. Previous applications leverage periodic and batch-level data analytics, which do not allow real-time information transfer when supplies change, whereas now warehouses are switching to real-time monitoring systems.



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Using Spatial Intelligence to Schedule Workers

Additionally, automated scheduling of workers can be done with WSI to provide needed labor as supplies and dispatch of inventory changes. These changes are also integrated with automated, robotic handling equipment that facilitate seamless interoperability between requesting, unloading, stocking, and dispatching supplies.[1]

 In the recent Covid pandemic, scheduling and operations could also incorporate social distancing and decision tools to help with proper staffing numbers in warehouses.

Supply Management and Spatial Intelligence

Researchers who study supply chains have also been developing other seamless systems that can better track and manage supplies in warehouses using a variety of sensors and not just over depending on RFID tags.

In a recent research paper, a goods quantity monitoring system (GPM) was proposed that can capture inventory using automated classification techniques and that can take information about known inventory to estimate more accurately total inventory supply.  A k-nearest neighbors algorithm helps to classify items that are near each other, helping to estimate items and classify them.[2] 

These and other changes to warehouses have been described as changes associated with Industry 4.0, where automation, spatial intelligence, and integration of software and hardware technologies, particularly IoT tools, are seen as key drivers for current industry. In fact, warehouses are integrated as part of product development, where automated, spatial intelligence is used to connect warehouses with factories directly so that products are not under- or over-produced.

We are only at the very beginning of Industry 4.0 and to speed up this change, managers and policy-makers are seen as having a key role in decisions that would be needed to speed-up the roll out of needed hardware and software so that factories and warehouses become more automated and intelligent in managing supplies. There are benefits to this as it would not only help to reduce waste, producing mainly what we need rather than over producing, but needed products can reach consumers more quickly. The use of spatial technologies will be critical at every step as part of logistical forecasting and modeling that can anticipate where supply and production are more greatly needed for given products and locations.[3]

We are still a long way from wide-scale adoption of intelligent warehouses, including its integration with Industry 4.0, although some countries are likely ahead of others. Nevertheless, the recent pandemic has shown that supplies can quickly run out for critical goods, such as masks and protective equipment, while over-production can have negative consequences for the environment and consumers. Intelligent, spatially systems monitoring warehouses should assist with creating more efficient warehouses that have are seen as key nodes in the consumer economy. Recent systems installed such as WSI technologies have demonstrated early success in managing supplies that can better reach consumers more quickly. Tacking advantage of other changes, such as wide-scale use of 5G and cloud computing, has also enabled this transformation. In future years, this could be more widely adopted by warehouses throughout many different countries. 

References

[1]    For more on spatially intelligent warehouses, see:  https://www.mhlnews.com/technology-automation/article/21151717/why-warehouses-are-becoming-spatially-intelligent.

[2]    For more on the intelligent warehouse goods quantifying monitoring system developed, see:  Xu, S., Xiao, F., Si, N., Sun, L., Wu, W., de Albuquerque, V.H.C., 2020. GQM: Autonomous goods quantity monitoring in IIoT based on battery-free RFID. Mechanical Systems and Signal Processing 136, 106411. https://doi.org/10.1016/j.ymssp.2019.106411.

[3]    For more on Industry 4.0 and its recent attempts to be developed in factories and warehouses, see:  Büchi, G., Cugno, M., Castagnoli, R., 2020. Smart factory performance and Industry 4.0. Technological Forecasting and Social Change 150, 119790. https://doi.org/10.1016/j.techfore.2019.119790

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About the author
Mark Altaweel
Mark Altaweel is a Reader in Near Eastern Archaeology at the Institute of Archaeology, University College London, having held previous appointments and joint appointments at the University of Chicago, University of Alaska, and Argonne National Laboratory. Mark has an undergraduate degree in Anthropology and Masters and PhD degrees from the University of Chicago’s Department of Near Eastern Languages and Civilizations.