The trend of Smartification refers to the process of retrofitting or producing previously disconnected analog assets with sensor and wireless technologies, making them ‘smart’ and connected, bridging the analog-digital divide. Smartification enables users to collect a variety of sensor data for analysis, performance measurement, simulations, and data-based decisions.
A survey of 2,400 senior executives found that 93% of the companies surveyed plan to further increase investment in the area of data and analytics. In 2021, already 11.3 billion devices were used to collect data on behavioral patterns, operations, and the utilization of assets, machinery, and facilities. This number is certainly continuing to grow as more and more companies are also integrating analog assets and systems into the IT ecosystem to obtain a holistic view of all processes and key performance indicators. Retrofitting assets with sensors in particular is therefore becoming increasingly important for a comprehensive data-based view of operations and, as the cost of sensors falls, this option becomes more scalable.
The Smartification trend will have moderate impact on the logistics industry as it drives visibility and transparency for optimization and enables data-driven decision making. However, especially retrofitting equipment and assets as well as integration in IT systems takes time. Therefore a few more years will pass before we are likely to see the widespread adoption of smartification applications across industries.
The number of connected devices globally is anticipated to grow exponentially within the next decade, influencing the behavior and activity of humans both as workers and as consumers.
Relevance to the Future of Logistics
- Predictive Maintenance
- Internet of Behavior
- Facility Monitoring
- Asset Tracking & Localization
- Smart Cities
The availability of data is becoming more important to enable predictive maintenance. Above all, this is because companies need the ability to determine the condition of equipment and other assets in order to identify necessary repairs and maintenance at an early stage, reduce downtime and ensure stable operations. When companies in India participated in a 2020 study on smart manufacturing, they chose big data and predictive analytics as technologies they would most like to invest in over the next 1 or 2 years. It is therefore no surprise that more companies are developing retrofit solutions to implement predictive maintenance, especially for older assets that are more susceptible to repair and failure due to age.
A good example of devices that can be added to minimize downtime and unnecessary maintenance while streamlining and controlling operations comes from Waites. The company has developed sensors and nodes for monitoring machines such as conveyor belt motors that detect the slightest change in humidity and temperature and enable the system to provide early warning of anomalies. These relatively low-cost plug-and-play solutions can prevent entire facilities from failing due to defective conveyors, allowing repairs, maintenance, and service to be performed proactively rather than reactively.
In April 2022, about 63% of the world's population had access to the internet, and this percentage is rising. As a result, the amount of data about user behavior and preferences continues to grow. Companies are eager to analyze this growing amount of data on user behavior, preferences, and patterns, especially in B2C sectors, and are doing so by increasingly adopting Internet of Things (IoT) technologies and accelerating smartification of assets, products, and systems. This data collection and analysis is now part of the so-called Internet of Behavior (IoB) as it enables companies to understand information in a new way – from a psychological point of view – and ultimately use this to adapt products, services, and processes to suit user and customer needs.
For logistics operations, an interesting IoB use case is to add telematics capabilities to vehicles. A telematics system integrates cameras and sensors in a vehicle to track detailed information such as brake patterns, information about fuel use, driving speeds, and more. Companies like UK-based Hypermile are able to retrofit trucks with their driver-assistance systems and use data analysis, computer vision, and artificial intelligent (AI) to reduce vehicle fuel consumption. This is all very valuable to fleet owners – it can help with fleet management evaluation, assessment of individual driving patterns, overall route planning optimization, and even negotiating new contracts with, for example, a car insurance company based on real-world data.
Saving energy is not only an important item on the agenda of companies due to rising energy prices, but also due to the current climate crisis with regard to reducing CO2 emissions. However, in order to be able to save energy, companies must first be able to identify and quantify potential savings. Although collecting and effectively analyzing data gives tremendous advantages, particularly enabling companies to make informed decisions, only 26.5% of companies see themselves as data-driven organizations.
A prime example of retrofitted data collection is equipping warehouses and production facilities with sensors to measure and ultimately manage energy consumption. Companies like Singapore-based BeeBryte can measure, predict, and even independently adjust energy consumption-related functions (such as heating, ventilation, and air conditioning) in smart production facilities, warehouses, and commercial buildings. By analyzing this data decision makers are able to draw the right conclusions based on hard facts.
With buildings, both commercial and residential, accounting for 36% of global energy consumption in 2020 alone, it is clear how important and also potentially lucrative such retrofitted monitoring and control solutions are. In the future, smartification in the area of facility management and smart buildings will help companies monitor CO2 emissions, which will subsequently lead to economic benefits and overall improvement of the carbon footprint.
In logistics operations, the localization and tracking of assets such as pallets, forklifts, and containers can be a challenging task and therefore smartification of these types of asset is very valuable.
A use case example is DHL’s roll cages which have been equipped with smart tracker sensors from French telecommunication company Sigfox and manufacturer Alps Electric Europe since 2019. This solution provides transparency on roll cage use, improving distribution to ensure there are always enough cages at every location.
To improve sustainability, more and more companies are evaluating reusable packaging but effective reuse requires consistent and repeated circulation of these materials. DHL Express uses Bluetooth low-energy beacons for its reusable EasyGreen packaging, a solution which provides an accurate view of available packages in the warehouse and helps track empty packages after delivery, ensuring appropriate redistribution across the network.
As these examples show, smartification helps ensure no assets are lost and no avoidable costs are incurred, while also enabling efficient asset inventory planning.
Sensors for data acquisition and process improvement are already being used in many respects, both in private households and in industry, but entire cities and municipalities also want to use these technologies to develop into so-called smart cities.
The idea behind smart cities is digitalization of the metropolis in order to increase quality of life for citizens by collecting and using data. This can take a variety of forms, from smart waste management solutions that monitor the usage of public bins to traffic management through to intelligent traffic routing using smart traffic-light control.
Development towards smart cities naturally impacts logistics operations, especially for last-mile delivery. Singapore, for example, a pioneer in smart cities, creates datasets of real-time data on bus arrival timings, cab availability, traffic conditions, and car park availability and freely gives this information as open data. This can be used by logistics providers to facilitate last-mile delivery and to select and schedule ideal delivery times. In the future, smart city intelligent parking systems could assign logistics service providers the ideal parking zones and times to make swift deliveries and avoid disrupting traffic.
All in all, the use of data from smart cities can help logistics providers make last-mile delivery more efficient, effective, and ultimately more sustainable.
This trend should be ACTIVELY monitored, with imminent developments and applications.
As sensor technology advances and the cost and size of sensors shrink, more and more smartification use cases are emerging. This means newly produced assets are increasingly smart from the outset and there are more and more opportunities to digitize analog assets by retrofitting them with sensors. With the general trend towards more transparency and data harvesting, the relevance of the smartification trend will continue to increase in the future.
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- Ernst & Young (2021): Global Capital Confidence Barometer, 23rd edition
- Statista (2022): Number of Internet of Things (IoT) connected devices worldwide from 2019 to 2021, with forecasts from 2022 to 2030
- Ernst & Young (2020): Big data, predictive analytics ranked as the top investment priority in technology by manufacturing firms in India - EY survey
- Statista (2022): Global digital population as of April 2022
- Global Alliance for Buildings and Construction (2021): 2021 Global Status Report for Buildings and Construction