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IoT Leaders

From Sensors to Strategy: How AI Unlocks Industrial Insight

Ep. 60

The promise of AI starts with the data beneath your feet.


In this episode, we explore how connected load cells, long viewed as routine industrial tools, are becoming strategic assets. Jorge Truffin, CEO at Unified Cloud Sensors, is using real-time IoT data to power predictive maintenance, automate diagnostics, and even influence market decisions.


This evolution unlocks new possibilities across industries like agriculture, logistics, and construction, including:

  • Transforming sensor data into pre-emptive maintenance alerts
  • Reducing downtime through AI-driven diagnostics
  • Detecting material loss in silos and supply chains
  • Tracking asset movement to optimize operations
  • Linking sensor output to commodity market insights


Tune in to discover how rethinking industrial IoT inputs can reshape outcomes—and build smarter, more resilient business models.


Key Topics and Chapters


(00:07) Intro to IoT Leaders and transformation stories

(00:22) Jorge Truffin’s journey in the global load cell market

(01:32) Shift from reactive to AI-powered proactive services

(02:42) Traditional IoT companies embracing AI for problems

(03:45) What load cells do and how they measure

(04:00) Jorge’s 30+ years in weighing industry

(05:13) Industrial weighing from 1 kilogram to 600 tons

(06:38) Historical weighing data previously lost and underused

(07:21) Use case: historical data enables early detection

(08:42) Data benefits providers and owners tracking silo flow

(09:27) Truck scales with many load cells complicate diagnosis

(10:29) Continuous monitoring detects gradual load cell issues

(11:35) Traditional reactive maintenance waits for failures

(14:58) Monitoring weight, angle, temperature for diagnostics

(16:03) Digitizing analog load cells for monitoring

(17:04) Why cellular chosen over client networks

(18:04) Global connectivity enables expansion with single SKU

(19:22) Single SIM solution supports global regulatory needs

(20:32) Use case: grain silo environmental and flow monitoring

(21:29) Monitoring deters theft and non-technical losses

(23:43) Detecting stuck material via center-of-gravity changes

(25:45) Center-of-gravity reveals distribution issues remotely

(28:12) AI agent giving traffic-light status for scales

(30:23) Growth to managed services with multiple agents

(31:10) Correlating sensors to reveal hidden patterns

(32:14) Detecting structural silo issues via PM10 correlation

(33:42) AI agents replace scarce decades-deep expertise

(34:49) Start monitoring now to build AI training data

(35:46) IoT data from things now essential for AI

(36:44) Volvo example: connecting millions to prevent stoppages

(37:59) Financial intelligence linking weights and futures prices

(38:58) Clients track asset value using weights plus markets

(40:47) Construction client uses market rates for pricing

(41:38) Hospital case: multi-source IoT enables new services

(42:31) Journey from weighing to financial advisory via AI

(44:02) Customer-driven innovation using existing data insights

(45:16) AI aids talent gap in traditional industries

(46:06) Agents train next-generation employees with knowledge


Show Links


· Follow Jorge Truffin at UCS on LinkedIn

· Follow Nick Earle on LinkedIn

· Follow Eseye on LinkedIn

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