{"id":8690,"date":"2026-03-27T13:28:00","date_gmt":"2026-03-27T18:28:00","guid":{"rendered":"https:\/\/www.mhisolutionsmag.com\/?p=8690"},"modified":"2026-03-30T07:19:45","modified_gmt":"2026-03-30T12:19:45","slug":"iot-sensors-and-edge","status":"publish","type":"post","link":"https:\/\/www.mhisolutionsmag.com\/index.php\/2026\/03\/27\/iot-sensors-and-edge\/","title":{"rendered":"IoT Sensors and Edge Computing Powering Real\u2011Time Supply Chain Visibility and Predictive Maintenance"},"content":{"rendered":"
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IoT sensors and edge computing are transforming supply chains by enabling real\u2011time insights, predictive maintenance and faster operational decisions. As these technologies mature and integrate with AI and standardized systems, companies can achieve greater visibility, efficiency and resilience across their operations.<\/h4>\n
BY SARA PEARSON SPECTER<\/span><\/div>\n
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I<\/span>N TODAY\u2019S ULTRA\u2011COMPETITIVE<\/strong> logistics landscape, data visibility alone isn\u2019t enough. Companies must act on insights in real time to prevent downtime, optimize operations and improve customer experiences. While supply chains have long collected data, traditional cloud\u2011centric architectures struggle to deliver the speed required for time\u2011sensitive decision\u2011making.<\/p>\n

Edge computing is emerging as a pivotal solution to these challenges. This capability shifts data processing closer to where it\u2019s generated\u2014on the warehouse floor, in transit vehicles or at distribution hubs\u2014rather than relying solely on centralized cloud services. While cloud platforms remain indispensable for long\u2011term analytics\u2014such as creating models or generating inferences that can be executed at the edge and for cross\u2011enterprise reporting\u2014they are not optimized for decision velocity. That is, the rapid interpretation and actioning of sensor data that keeps goods flowing, machines running and disruptions mitigated.<\/p>\n

In a recent Logistics Viewpoints<\/em> report, Jim Frazer, Vice President of Corporate Strategy at ARC Advisory Group, noted that logistics networks are generating ever\u2011larger volumes of data from Internet of Things (IoT)\u2011enabled devices, equipment, vehicles and facilities.<\/p>\n

“Traditional cloud\u2011centric architectures, which depend on centralized processing, may not meet speed and\/or reliability goals needed to support operational needs at scale,” he wrote. “Edge computing\u2026 has emerged as a method to address these challenges by reducing latency and improving resiliency.”<\/p>\n

By enabling local data pre\u2011processing, analytics and decision logic, edge architectures reduce dependence on upstream networks while enabling faster action and lower bandwidth consumption. When combined with IoT sensors that stream data on location, temperature, vibration and machine behavior, edge computing forms the digital nervous system, enabling greater visibility into operations and assets. That, in turn, yields smarter, more resilient supply chains.<\/p>\n

Underscoring the importance of edge computing, Gartner forecasts explosive growth as the technology moves from a niche to a foundational technology, with the market reaching $511 billion by 2033 across key sectors like manufacturing and retail. Its analysts anticipate a 30% increase in platform adoption by 2029. Much of this adoption will be driven by increasing integration of different forms of artificial intelligence (AI), including predictive, generative and agentic. Gartner anticipates that this shift will enable enterprises to transition away from single\u2011edge use cases and evolve toward integrated edge\u2011cloud deployments, focusing on real\u2011time intelligence and automation.<\/p>\n

However, in his report, Frazer cautioned that the shift to edge processing brings its own complexities. Logistics organizations must manage large fleets of distributed devices, secure edge assets against physical and cyberthreats, optimize AI models to run efficiently on edge hardware and navigate fragmented standards across vendors\u2014all while ensuring that real\u2011time insights sync reliably back to cloud systems for broader analytics.<\/p>\n

To unpack how companies are applying IoT and edge computing technologies today\u2014and how they\u2019ll be leveraged in the coming years\u2014MHI Solutions<\/em> spoke with industry experts from four MHI member companies:<\/p>\n