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Postgraduate DiplomaCivil, Rail & Smart Cities Applications open

Postgraduate Diploma in IoT Monitoring and Environmental Quality Data

Online 800-hour Postgraduate Diploma in IoT Monitoring and Environmental Quality Data. 8 modules covering Directive (EU) 2024/2881 (ambient air quality), CEN/TS 17660-1 (assessment of low-cost gas sensors) and Node-RED. Dedicated tutor and open enrolment.

Duration800 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Describe the key pollutants and parameters of urban environmental quality.

02

Select environmental sensors according to their measuring principle and limitations.

03

Design IoT architectures for data capture, communication and storage.

04

Apply calibration and quality assurance procedures to low-cost sensors.

05

Build clean, traceable environmental data pipelines.

06

Develop analytical models and dashboards for decision-making.

07

Plan a complete environmental monitoring network for an urban area.

Profile

Who it's for

  • Environmental monitoring network engineer who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Environmental data scientist who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Air quality technician who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Developer of environmental IoT solutions who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Smart city platform manager who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Sensor calibration specialist who wants to specialise in IoT Monitoring and Environmental Quality Data.
  • Engineering or science graduates looking to enter local government.
Standards & tools

What you'll work with

  • Directive (EU) 2024/2881 (ambient air quality)
  • CEN/TS 17660-1 (assessment of low-cost gas sensors)
  • EN 16450 (automated particulate matter measuring systems)
  • Royal Decree 102/2011 (improvement of air quality)
  • EN 14211 (measurement of NO2 by chemiluminescence)
  • EN 14625 (measurement of ozone by UV photometry)
  • ISO/IEC 30141 (IoT reference architecture)
Syllabus

8 modules · 800 h

  1. 1.1Atmospheric pollutants: PM10, PM2.5, NO₂ and O₃
  2. 1.2Directive (EU) 2024/2881 on air quality
  3. 1.3WHO 2021 guideline values
  4. 1.4Air quality indices
  5. 1.5Environmental noise and the Lden indicator
  6. 1.6Water quality in rivers and urban networks
  7. 1.7Urban microclimate and heat island
  8. 1.8Emission sources: traffic, industry and heating
  9. 1.9Official reference networks
  10. 1.10Case study: air quality diagnosis of a city
  1. 2.1Electrochemical gas sensors
  2. 2.2Optical particle sensors
  3. 2.3NDIR CO₂ sensors
  4. 2.4Multiparameter water probes
  5. 2.5Class 1 and class 2 sound level meters
  6. 2.6Drift, interference and the effect of humidity
  7. 2.7Low-cost sensors versus reference equipment
  8. 2.8Sensor assessment according to CEN/TS 17660-1
  9. 2.9Encapsulation and outdoor protection
  10. 2.10Laboratory: characterisation of a particle sensor
  1. 3.1Nodes, gateways and platform
  2. 3.2Microcontrollers and data acquisition
  3. 3.3LoRaWAN, NB-IoT and LTE-M connectivity
  4. 3.4MQTT and CoAP protocols
  5. 3.5Solar power and energy management
  6. 3.6Edge processing
  7. 3.7FIWARE and Smart Data Models
  8. 3.8Cybersecurity according to ETSI EN 303 645
  9. 3.9Network deployment and maintenance
  10. 3.10Workshop: LoRaWAN node with MQTT transmission
  1. 4.1Co-location with reference stations
  2. 4.2Multivariate regression calibration
  3. 4.3Machine learning calibration
  4. 4.4Calibration transfer between nodes
  5. 4.5Drift detection and recalibration
  6. 4.6Measurement uncertainty according to the GUM
  7. 4.7Normative data quality objectives
  8. 4.8Data validation and flagging
  9. 4.9Metrological traceability
  10. 4.10Practical: calibration of co-located NO₂ sensors
  1. 5.1Time-series databases
  2. 5.2Streaming data ingestion
  3. 5.3Cleaning, filtering and gap handling
  4. 5.4Temporal and spatial aggregation
  5. 5.5OGC SensorThings API standard
  6. 5.6Open data and FAIR principles
  7. 5.7Data publication APIs
  8. 5.8Data governance and quality
  9. 5.9Cloud architectures
  10. 5.10Workshop: data pipeline for a sensor network
  1. 6.1Exploratory analysis of environmental series
  2. 6.2Anomaly and episode detection
  3. 6.3Source apportionment by PMF factorisation
  4. 6.4Spatial interpolation and kriging
  5. 6.5Gaussian dispersion models
  6. 6.6Forecasting with ARIMA and LSTM networks
  7. 6.7Fusion of sensor and satellite data
  8. 6.8Environmental digital twins
  9. 6.9Personal exposure and health effects
  10. 6.10Practical: 24-hour NO₂ forecasting
  1. 7.1Dashboards with Grafana
  2. 7.2Interactive maps with GIS
  3. 7.3Alerts and information thresholds
  4. 7.4Communicating with the public
  5. 7.5Air quality improvement plans
  6. 7.6Assessment of low-emission zones
  7. 7.7Citizen science and participatory networks
  8. 7.8Indicators for municipal managers
  9. 7.9Privacy and GDPR in urban data
  10. 7.10Case study: municipal dashboard
  1. 8.1Objectives and variables to monitor
  2. 8.2Sensor selection and assessment
  3. 8.3Network design and site selection
  4. 8.4Communications architecture
  5. 8.5Calibration and quality control plan
  6. 8.6Data platform and analytics
  7. 8.7Dashboard and alerts
  8. 8.8Budget and maintenance plan
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. There are no fixed timetables: students progress at their own pace within the intake, making it easier to combine with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Node-RED, InfluxDB and Grafana, Python (pandas, scikit-learn), QGIS, R (openair), in free, academic or evaluation versions. Assignments are based on real sensor intercomparison procedures against reference stations, pilot deployment of urban sensor networks and validation of environmental data series. Assessment is continuous by module, plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL and vibration/acoustics.
Evidence-oriented final project:safety case, test plan, compliance dossier and operational limits.
Industry-mentored:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with OT cyber-security, DIH and compliance as its pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Objectives and variables to monitor

Describe the key pollutants and parameters of urban environmental quality.

Sensor selection and assessment

Select environmental sensors according to their measuring principle and limitations.

Network design and site selection

Design IoT architectures for data capture, communication and storage.

Communications architecture

Apply calibration and quality assurance procedures to low-cost sensors.

Calibration and quality control plan

Build clean, traceable environmental data pipelines.

Career opportunities

Where this takes you

Environmental monitoring network engineerEnvironmental data scientistAir quality technicianEnvironmental IoT solutions developerSmart city platform managerSensor calibration specialist
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not 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.

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FAQ

Frequently asked questions

The programme comprises 800 hours in total, spread over 6 to 8 months. This is an average of between 10 and 15 hours per week, compatible with a full-time job.

You will work with Node-RED, InfluxDB and Grafana, Python (pandas, scikit-learn), QGIS, R (openair). Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.

A SEIUM in-house diploma upon passing the continuous assessment and the integrative project. It is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the higher programme. Please check the credit transfer policy when you enrol.

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