The Logical Approach to Logistics: Mastering the Edge To Manage Things in Motion by Aaron Allsbrook
January 16, 2020
Whether understanding where assets or shipments are, Industrial IoT (IIoT) has been successfully tackling the opportunity to drive trillions of dollars in improvements according to industry observers. When we know where things are, we can more efficiently move them to new physical locations, in the case of asset management.
For example, in the construction industry, being able to redeploy expensive equipment from one job site to another means having to own less of that equipment, while also understanding the health of that equipment, making maintenance more predictable and cost-efficient.
In the shipping industry, package tracking has become the lifeblood of the new consumer retail experience (with the disruption caused by Amazon Prime) but also with the industry solutions, including ensuring wholesale shipments of cold case goods are compliant with regulation throughout their journey from the source to the retailer, and the delivery of pharmaceuticals which also require temperature control as well as security required by hospitals, pharmacies and the FDA generally.
Automation in the logistics world has moved the world forward dramatically over the last twenty years, but we may look back on how we instrument, measure and manage assets and inventory in motion in ten years, and wonder how we ever were able to do so without further innovations which edge computing is making possible, combined with networked systems.
With advanced IIoT solutions in place, enterprises and organization are digitally transforming their entire logistical operations, including triggers and alerts that indicate problems very early in the cycle, while also providing valuable data that can be leveraged to identify new ways to move things faster and more accurately.
With real-time visibility into their assets and inventory, they can move beyond cloud applications which have matured nicely and generate even more value from edge computing, without the requirement to wait for data to move to the cloud, by processing information closer to its source. While cloud computing will always play an important role in the architecture and networking associated with logistical systems, edge computing opens new opportunities for more granular control, and more instant coordination locally.
For asset management of a fleet of trucks, for example, being able to redirect those trucks (and drivers) within New York City, which is relatively small geographically, but congested and challenging to move about especially during workdays, can make a huge difference in “load balancing” on the busiest days, even when there is “gridlock alert.” When there is a big trade show happening and deliveries must be made within a small window, providing guidance beyond traditional GPS systems can make or break a successfully completed sale with the customers waiting to receive their goods. It can also reduce the costs of fuel and the costs of traffic fines associated with onerous delivery zone regulations. This use case may seem basic, but it is anything other than that when minutes matter and the latency associated with the cloud is made worse by congested WiFi and radio access networks (issues that will only partially be resolved by 5G, when 5G actually arrives).
Intelligent transport systems for trucking companies are becoming one of the most active participants who will ultimately connect to a smarter and more congested infrastructure that will become the “circulatory system” for smart cities, which are growing in leaps and bounds in 2020 and beyond. When combined with 5G wireless communications networks, the rise of automated systems, including augmented vehicles (with self-driven capabilities) and driverless vehicles as those mature.
In this world, coming soon, route planning and optimization will go well beyond the basics (traffic and weather) to finely tuned new laws based on noise pollution reduction, school zone safety, pedestrian safety, and the “no-drive zones” NYC is already putting in place, with tolls for vehicles entering certain areas at certain times, and larger fines when trucking companies disobey laws.
In these scenarios, edge computing will be the only way to support automation, and that edge computing will be made secure and affordable through IIoT solutions like those ClearBlade is expert in, including capturing, analyzing, reporting on, automating based on, and reporting on to support innovation in logistics and transportation.
Edge computing is still heterogeneous and takes an ecosystem. It ranges from simple sensors and embedded edge devices to smartphones and tablets but is becoming increasingly sophisticated with devices used in different scenarios with a variety of life spans, ranging from one year to 40 years (when sensors, actuators, and other technology endpoints are embedded in physical infrastructure).
While the use cases are very clear, and innovation is happening every day in the transportation and logistics sectors, given the economic upside of “understanding everything,” organizations including government agencies who control public highways, streets, sidewalks, buildings and transportation hubs have to overcome challenges as management becomes more complex.
A properly architected edge generally includes a computing device (sometimes called a “gateway”) that collects and analyzes data locally from any sensor registered to it, with that data flowing on a completely local, completely private network without having to touch the Internet or travel over expensive cellular connections.
By aggregating data from the different endpoints, the right edge solution can compute the data and support AI and machine learning-driven applications in near real-time, which the cloud is unable to support.
When tracking and analyzing freight and equipment across the planet, you need a common software platform that can run on the range of hardware components and protocols. For remote management and monitoring of goods and vehicles, ClearBlade integrates with wirelessly connected devices. A factory’s on-site IoT system can interface with the logistics solution react to real-time updates on the shipment of materials, provide accurate, real-time data on shipment locations at a warehouse, sorting facility and while en route. The “chain of custody” can be supported from the factory to the final location, with a record of the route and highly detailed information on temperature, humidity and more, locally and, where appropriate, enabling millions of endpoints to transmit data to the cloud for the centralized applications that don’t require automation but rather perform analysis across a distributed set.
ClearBlade is supporting innovation in transportation and logistics by making more sophisticated, edge computing solutions reliable, affordable and secure.