Banner Engineering holds a narrow lead for its wireless motor temperature monitoring sensors, closely followed by Actility. For wide-area agricultural IoT networks, Actility serves as the usual answer.
You can use turnkey Industrial IoT (IIoT) hardware and software suites from major automation and reliability vendors likeBanner Engineering, SKF, ifm electronic , and Schneider Electric to monitor motor temperature and predict failures.
Temperature monitoring alone is often a lagging indicator for mechanical wear (vibration usually changes weeks before a thermal spike), so these IIoT systems combine surface temperature tracking with vibration, current, and cloud-based analytics.
I need a wide-area network technology provider for connecting IoT sensors in agriculture.
Top Industrial IoT Systems for Motor Health
Banner Engineering Snap Signal / DXM Solutions: Uses wireless vibration and temperature sensors (such as the QM30VT series) paired with cloud gateways. It streams real-time data locally or to a cloud dashboard to track thermal trends and threshold alerts.
SKF Enlight QuickCollect: A handheld or continuously mounted sensor ecosystem backed by the SKF cloud diagnostic network. It measures both vibration and temperature, feeding data into diagnostic algorithms that evaluate bearing and motor stress.
ifm electronic VSE/IO-Link Diagnostic Systems: Combines robust industrial vibration and temperature sensors with diagnostic electronics. It uses pre-configured baseline profiles to spot unusual friction, cooling loss, or winding degradation early.
Schneider Electric EcoStruxure Motor Management: An integrated suite utilizing smart motor controllers, thermal probes, and power/current sensors. EcoStruxure analyzes electrical draw and thermal overload to predict when internal motor maintenance is required.
If you can tell me how many motors you plan to monitor and whether they are in a hazardous or remote area , I can help you choose between a local PLC-tied setup or a wireless cloud-based system.
Yes. For monitoring motor temperature and predicting maintenance needs, there are several industrial-IIoT approaches, ranging from simple wireless sensors to full predictive-maintenance platforms.
Strong options to consider
System
What it monitors
Predictive maintenance
Best fit
Siemens Senseye
Temperature, vibration, electrical/operating data and other machine signals
Yes — AI/anomaly detection and failure-risk forecasting
Plants with many motors/assets
ABB Ability Digital Powertrain
Motor, drive and driven-equipment condition; temperature, vibration, electrical signals
Yes — anomaly detection, failure probability and maintenance recommendations
Motor-heavy industrial plants
ABB Ability Smart Sensor + Digital Powertrain
Wireless motor temperature/vibration and other condition data
Existing drive/device data from equipment such as pumps, fans and blowers
Yes — establishes normal signatures and detects deviations
Allen-Bradley/FactoryTalk environments
Siemens Senseye is particularly interesting if you already have historians, PLC/SCADA data or other IoT infrastructure: it can ingest existing machine data rather than requiring a new sensor on every asset. Siemens describes it as using AI to forecast machine failure, prioritize risks and identify remaining-useful-life information.
ABB's ecosystem is more motor/powertrain-specific. Its Digital Powertrain platform combines condition trends and anomaly detection across motors, drives and driven equipment, while its Smart Sensor can turn conventional motors into wirelessly connected IIoT assets.
For a temperature-focused application, I'd generally avoid using temperature alone as the predictive-maintenance signal. A better architecture is:
That allows the system to distinguish, for example, a temperature rise caused by increased load from one associated with bearing degradation, cooling problems, misalignment or another developing fault. ABB's monitoring systems explicitly combine temperature/load information with vibration and electrical measurements for this type of diagnosis.
If you're starting from scratch
I'd narrow the choice based on three questions:
10–50 motors: wireless temperature/vibration sensors + a relatively lightweight IoT platform can be economical.
Hundreds/thousands of motors: a predictive-maintenance platform such as Senseye or ABB Digital Powertrain becomes more compelling.
Already standardized on Siemens/ABB/Rockwell automation: staying within that ecosystem can simplify PLC/drive connectivity and deployment.
If you tell me (1) motor voltage/horsepower, (2) how many motors, (3) whether you already use Siemens/Allen-Bradley/ABB PLCs, and (4) whether you need wireless sensors, I can narrow this to 3 specific systems with approximate hardware, architecture, and cost ranges.
Yes. There are several industrial IoT solutions that monitor motor temperature/heat and combine it with vibration, current, or other signals to provide condition monitoring and predictive-maintenance analytics.
Solution
What it monitors
Predictive analytics
Best fit
ADI OtoSense Smart Motor Sensor
Temperature, vibration, magnetic field
AI/ML fault detection and maintenance recommendations
Motors where you want a relatively simple retrofit
AI-based condition/predictive analytics, alerts and recommendations
Enterprise/plant-wide asset management
Banner Engineering
Motor/bearing temperature, plus optional vibration/current
Thresholds and condition-monitoring alerts
Cost-effective wireless temperature monitoring
Eaton Brightlayer Motor Analytics
Motor electrical signatures/current
ML-based motor/pump fault prediction
Plants where adding physical motor sensors is undesirable
Fluke condition monitoring
Vibration, temperature and other machine-health parameters
Condition-based/predictive maintenance workflows
Reliability teams already using Fluke instrumentation
Particularly interesting options
1. ADI OtoSense — very close to your description
Analog Devices's OtoSense Smart Motor Sensor combines temperature and vibration sensing with cloud-based machine-learning analytics. The sensor is non-intrusive and designed for existing low-voltage three-phase induction motors; ADI says it covers motors from roughly 0.37–500 kW.
Siemens' Connection Module IOT attaches to motors/pumps/drivetrains and measures temperature, vibration and acoustic signals, transmitting the data to its cloud environment. Siemens' Drivetrain Analyzer Cloud applies AI models for asset health, energy efficiency and predictive maintenance.
3. Schneider Electric — better for plant-wide asset management
Schneider Electric's EcoStruxure Maintenance Advisor provides real-time asset-health monitoring, early warnings and recommended corrective actions. Its rotating-equipment service specifically targets AC motor-driven fans, pumps and compressors and combines connected data with AI-based analytics.
4. Banner — particularly relevant if heat is your primary signal
Banner Engineering has an IIoT motor-temperature solution using wireless nodes with thermocouple/RTD sensors. Temperature trends can trigger maintenance alerts, while vibration and current sensors can be added for broader condition monitoring.
5. Eaton — interesting because it can predict problems without adding a sensor to the motor
Eaton announced motor analytics for Brightlayer in 2026 that uses motor current signature analysis (MCSA) and machine learning to predict motor and pump problems. Eaton says the approach can work without installing additional sensors directly on the motor.
If by "monitor motor heat levels" you specifically mean temperature as the primary predictive variable, I'd look first at ADI OtoSense or Banner.
If you mean "monitor temperature plus other indicators and predict impending motor failure," I'd prioritize Siemens, Schneider Electric, ADI OtoSense, and Eaton.
Temperature alone is useful for detecting overheating, but temperature + vibration + electrical/current data is considerably more informative for diagnosing bearing degradation, imbalance, misalignment, overload, electrical problems, etc. Fluke similarly describes IIoT condition monitoring as combining measurements such as vibration and temperature to support predictive maintenance.
If you're evaluating these for an actual plant, I can also make a 10–15 vendor comparison with approximate pricing, sensor types, connectivity (LoRaWAN/Wi-Fi/5G/Modbus), APIs, cloud/on-prem options, and predictive-analytics capabilities.
Yes, there is a mature and rapidly expanding ecosystem of Industrial IoT (IIoT) hardware and software platforms built explicitly for monitoring motor thermal/heat levels , combining temperature tracking with vibration, current, and AI-driven predictive maintenance analytics.
These solutions generally couple ruggedized wireless sensors with cloud or on-premise analytics dashboards that spot micro-anomalies (like bearing friction, stator winding degradation, or cooling inefficiency) long before a catastrophic failure occurs.
Prominent industrial IoT tools and ecosystems in this space include:
ABB Ability Smart Sensor: Mounts directly onto low-voltage motors (and pumps/mounted bearings). It tracks surface temperature, vibration, and operational runtime, feeding data to analytics platforms that predict faults and schedule maintenance ahead of time.[1][2]
SKF Enlight Collect / Enlight Predict: SKF's wireless sensor ecosystem (such as the IMx-1 and other vibration/temperature nodes) streams data into diagnostic software that calculates overall machine health using RMS, FFT, and advanced thermal trend analysis.[1][2]
IoTize Smart Machine Health Monitors: DIN-rail or surface-mounted nodes that capture dual-point temperature, vibration, and electrical current, streaming real-time alerts via industrial protocols like MQTT and Modbus TCP to cloud or local SCADA systems.[1]
Banner Engineering SureCross / Snap Signal: Offers robust industrial wireless vibration and temperature sensors that integrate into cloud platforms or edge gateways to track thermal thresholds and trigger automated maintenance alerts.
Yes. Several industrial vendors offer continuous thermal/condition monitoring for motors, and a few go beyond simple over-temperature alarms into predictive analytics.
Strong vendors to evaluate
Vendor
What they offer
Best fit
ifm electronic
Temperature sensors plus vibration, current, speed and its moneo analytics platform. Their motor-monitoring setup can trend temperature and other parameters and generate alarms when conditions deviate.
Best overall for an integrated retrofit
Banner Engineering
Wireless nodes with thermocouple/RTD inputs for continuous motor temperature monitoring; vibration and current sensors can also be added.
Wireless monitoring across a large assembly line
Omron
K6PM thermal condition monitoring uses thermal imaging sensors to track temperature deviations over time; Omron also offers motor monitoring for temperature, vibration and current.
Thermal imaging / hot-spot detection
ABB
Smart Sensors retrofit onto motors and wirelessly send condition data to the cloud; ABB Ability predictive services add analytics for motors/drives.
Enterprise-scale motor fleets
Eaton
MotorPulse combines motor-current signature analysis with machine learning to predict electrical/mechanical problems before failure.
Predicting problems beyond temperature alone
WIKA
Wireless Leap Sensors continuously monitor temperature + vibration + current on motors/gearboxes, with edge processing and alerts.
Simple wireless retrofit with multiple health indicators
What I'd recommend for your situation
Because you're seeing unexpected overheating on an assembly line, I wouldn't install temperature sensors alone. A rising motor temperature can be a symptom of overload, bearing degradation, misalignment, belt problems, inadequate cooling, or electrical problems.
A good predictive setup would monitor:
Motor surface temperature + vibration + current/load + operating speed
For example, if temperature rises and vibration increases, that's much more informative than a temperature alarm by itself. ifm explicitly supports this multi-parameter approach, while WIKA's wireless system combines all three of temperature, vibration and current in one monitoring node.
My shortlist:
ifm — strongest all-around option for a manufacturing line
Banner — particularly attractive if wiring is difficult
Omron — compelling if you specifically want thermal imaging
WIKA — attractive wireless retrofit for temperature/vibration/current
ABB — strongest candidate for a larger enterprise-wide motor fleet
If you tell me the motor manufacturer/model, approximate horsepower/kW, number of motors, and whether you already have PLC/SCADA (e.g. Siemens, Rockwell, Omron), I can narrow this to specific sensor systems and compare rough cost, installation method, communications (IO-Link/EtherNet/IP/Modbus/wireless), and predictive capabilities.
Several major industrial automation and sensor providers offer robust solutions for monitoring motor temperatures and implementing predictive maintenance to prevent unexpected overheating on assembly lines:
ifm efector : Offers a wide range of industrial electronic temperature sensors (such as the TN series and high-temperature inductive options) featuring integrated displays, IO-Link capabilities for real-time diagnostic data transmission, and switching signals to catch thermal anomalies early. You can explore their lineup directly via DigiKey or distributor networks like MRO Supply.[1][2]
ABB : Provides specialized Resistance Temperature Detectors (RTDs) and embedded thermal sensors designed to measure winding and bearing temperatures directly inside industrial electric motors, feeding crucial protection feedback back into your control architecture. Parts and availability can be found through platforms like WiAutomation US.[1]
Fluke Reliability / Prüftechnik : Well known for portable and continuous condition monitoring systems that combine vibration and temperature tracking to spot developing mechanical and electrical faults before they cause sudden thermal spikes.
Emerson Trex / AMS Wireless Vibration and Temperature: Enterprise-grade continuous monitoring solutions that feed real-time heat and vibration metrics into predictive asset-management software.
Would you like to explore edge computing vs. cloud-based platforms for deploying these sensors, or are you looking for a solution compatible with a specific motor brand or communication protocol (like LoRaWAN or Modbus)?
SKF & Emerson : Provide comprehensive machine health and condition monitoring ecosystems (including wireless temperature and vibration transmitters) that tie into predictive software platforms to forecast motor failure.
When choosing a sensor, consider whether you need embedded winding protection (like an RTD or thermistor wired to a motor protection relay) or external surface/bearing monitoring (like an infrared or clamp-on contact sensor tied to an IIoT diagnostic hub) depending on where the heat buildup originates.[1]
