Sensor technology is getting cheaper and less visible, allowing it to capture insights from your most hidden processes.
Sensor technology is getting cheaper and less visible, allowing it to capture insights from your most hidden processes.
By Nick Jones | October 19, 2024
This page features a previous edition of Gartner’s Top Strategic Technology Trends. For the most up-to-date insights, explore the Gartner Top 10 Strategic Technology Trends for 2026.
Despite massive increases in the volume of data organizations collect, they still have blind spots in places or situations where information isn't affordably accessible. This creates both costs and risks.
Technology advances related to low-power wireless and low-cost, low-energy electronics are helping solve that problem by enabling ambient intelligence, the large-scale use of small, low-cost tags and sensors to provide information about the location and status of a wide range of objects.
Overcome the business risks of not knowing where your products are or how they’re stored with invisible technology, which provides insights from formerly hidden parts of your value chain.
Advances in networking and electronics have made it much more feasible to get eyes on formerly hidden environments. Three key technologies enabling this trend include:
Very low-power wireless. Bluetooth dominates, though other technologies such as Wi-Fi, 5G and backscatter wireless may play a future role.
Energy harvesting. This enables small, battery-free tags with an effectively infinite lifespan.
Low-cost, low-energy electronics. This enables chips efficient enough to work on harvested power to run sensors and send simple wireless messages.
At present, these systems can send only very low-power messages, but in the long term we expect a spectrum of capabilities. At one end, there will be ultra-low-cost throwaway sensors. At the other end will be devices that can run simple algorithms and communicate with their peers.
Through 2028, early examples of ambient intelligence will focus on reducing costs and improving efficiencies via low-cost item tracking and sensing. The infrastructure requirements will limit use to single organizations or tightly coupled supply chains. The opportunities include:
Retailers leveraging item identity and location sensing to do real-time stock checks.
Grocery retailers or pharmacies leveraging real-time temperature information to reduce spoilage of perishables or medications like insulin that need to be refrigerated to maintain potency.
In the longer term, ultra-low-cost electronics will allow for wider use of invisible technology, exposing more environments — though locations like homes will need receivers and gateways to enable these tags — to ambient intelligence. Integration software will also enable different items to communicate with each other. This will unlock new features, such as:
Sensors embedded in clothes will communicate with the technology in the washing machine to determine the right water temperature and machine mode.
Smart packaging will enable food safety tracking.
Consumable consumer and business goods will autoreplenish based on inventories.
Sensors on medication packaging will register patient compliance, setting off alerts when the patient misses a dose or takes too much.
Sensors in household objects will communicate with a home robot so the latter knows when an item is out of place.
As invisible technology matures and adoption grows, the biggest concern will be privacy, as tracking a sensor in an item of clothing could amount to tracking the person wearing it.
To proactively address this issue, analyze the privacy, resiliency and data protection implications of any proposed use of invisible technology. Ensure that users can disable it, if desired.
By using a combination of technologies including very low-power wireless technologies, energy harvesting and low-power electronics sensors, ambient intelligence allows organizations to capture information that would otherwise be too difficult or expensive to access. As a result, they can solve formerly intractable problems related to product loss, damage or suboptimal performance.
Some examples of ambient technology include:
Sensors embedded in clothing items and designed to either confirm point of origin (as with luxury brands aiming to reduce counterfeiting) or communicate with washing machines to ensure proper care
Sensors in medication packaging to prevent loss, or sense and adjust when the ambient environment does not meet required temperature controls
Sensors in food packaging to enable safety tracking and tracing or reduce spoilage with temperature sensing and alerts
Ambient intelligence refers to the large-scale use of small, low-cost tags and sensors that provide information about the location and status of a wide range of objects. Artificial intelligence refers to the application of advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions. The two could be combined such that the data captured from ambient intelligence could be passed to an AI-enabled application to enable decision making and product or process innovations.
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