Sensors in Forestry Machinery Course
The AI Traffic Control in UAM Course explores the use of Artificial Intelligence (AI) to optimise urban air traffic control (UAM). It focuses on applying machine learning and data analysis algorithms to route planning, congestion management and safety improvement in the UAM environment, considering aspects such as traffic modelling, scenario simulation and integration with air traffic management (ATM) systems. It addresses the development of AI-based solutions for anomaly detection and automated decision-making, essential for the safe and efficient operation of unmanned aerial vehicles (UAV) and urban air mobility aircraft (UAM).
The course provides practical knowledge in designing intelligent traffic control systems, using simulation and data analysis tools to assess the performance and feasibility of the proposed solutions. It focuses on the application of AI in UAM, including route optimisation, airspace management and flight planning. This course prepares participants for roles such as AI air traffic control specialists, UAM data analysts, UAM systems engineers and UAM software developers, driving the advancement of urban air mobility.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the sensors fitted to forestry harvesters and forwarders.
Configure data acquisition and transmission according to the StanForD standard.
Calibrate log diameter and length measurement systems.
Assess the quality and uncertainty of forestry measurements.
Use machine data to optimise bucking and production.
Plan sensor maintenance under field conditions.
Apply sensor data to the traceability required by European regulations.
Who it's for
- Forestry machinery systems engineer who wishes to specialise in Sensors in Forestry Machinery.
- Instrumentation and sensor technician who wishes to specialise in Sensors in Forestry Machinery.
- Forestry machinery service technician who wishes to specialise in Sensors in Forestry Machinery.
- Forest harvesting data manager who wishes to specialise in Sensors in Forestry Machinery.
- Forestry operations manager who wishes to specialise in Sensors in Forestry Machinery.
- Forestry certification and traceability technician who wishes to specialise in Sensors in Forestry Machinery.
- Engineering or science graduates seeking to join forest harvesting companies.
What you'll work with
- StanForD 2010 (data communication in forestry machinery)
- ISO 11850 (self-propelled forestry machinery. Safety)
- Regulation (EU) 2023/1115 (deforestation-free products)
- ISO 11783 (ISOBUS)
- IEC 60529 (IP protection degrees)
- ISO/IEC 17025 (competence of testing and calibration laboratories)
- ISO 13849-1 (safety-related parts of control systems)
6 modules · 300 h
1.1What is measured on a harvester and a forwarder1.2Position and angle sensors on the crane1.3Hydraulic pressure sensors1.4Length and diameter sensors on the harvester head1.5Feed speed sensors1.6Temperature and level sensors1.7Cab tilt and levelling sensors1.8Geolocation and operation logging1.9Power supply, wiring and protection in the forest1.10Workshop: inventory of a machine's sensors
2.1Machine control network and buses2.2Sampling frequency by signal type2.3On-board and terminal storage2.4Transmission in areas without coverage2.5Clock synchronisation and timestamps2.6Standard formats in the forestry sector2.7Data integrity and record losses2.8Channel and data security2.9Energy consumption of sensorisation2.10Practice: designing a machine's data flow
3.1Harvester head calibration procedure3.2Verification with tape and with log samples3.3Calibration frequency and records3.4Sensor drift and its detection3.5Effect of species and bark3.6Systematic versus random errors3.7Tolerances accepted by the buyer3.8Reconciliation with mill scaling3.9Calibration documentation3.10Practice: calibration and verification of measurement
4.1Production control in near-real time4.2Detection of productivity losses4.3Diagnosis of harvester head problems through pressure4.4Control of consumption and work cycle4.5Temperature monitoring and alerts4.6Tracking consumable wear4.7Time allocation and stoppage analysis4.8Useful information for the operator in the cab4.9Alarms and sensible thresholds4.10Practice: forestry machine dashboard
5.1Cleaning and protecting sensors5.2Connectors, moisture and corrosion5.3Typical faults and their diagnosis5.4Sensor spare parts in the field5.5Verification after a repair5.6System software updates5.7Configuration documentation5.8Cost of sensorisation and its return5.9Operator training in its care5.10Practice: instrumentation maintenance plan
6.1Data required by the timber buyer6.2Traceability and chain of custody6.3Data ownership and agreements with the contractor6.4Sharing with the forest owner6.5Environmental indicators derived from data6.6Integration with harvest management6.7Limitations of current sensorisation6.8Common errors in using this data6.9Evolution of sector technology6.10Final project: sensorisation and data use plan for a machine
How you'll learn
Training is 100 % online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB, LabVIEW, QGIS, Python (pandas), Komatsu MaxiFleet, in free, academic or evaluation versions. Tests are studied using real calibration procedures for harvester heads, verification of log diameter and length measurement, and data transmission tests in the forest. Assessment is continuous across each module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the sensors fitted to forestry harvesters and forwarders.
Configure data acquisition and transmission according to the StanForD standard.
Calibrate log diameter and length measurement systems.
Assess the quality and uncertainty of forestry measurements.
Use machine data to optimise bucking and production.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The course works with MATLAB, LabVIEW, QGIS, Python (pandas), Komatsu MaxiFleet. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
SEIUM's own diploma upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Check the recognition policy when you enrol.
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