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.
Postgraduate Diploma in IoT Monitoring and Environmental Quality Data — studying from the United Kingdom
Civil and infrastructure engineering is a major employment sector in the United Kingdom, with significant activity in transport, water, energy and urban regeneration. Rail projects such as HS2 and ongoing network upgrades by Network Rail create demand for engineers in track, signalling, structures and systems. Smart city initiatives in cities including Manchester, Glasgow and Milton Keynes apply digital technologies to mobility, utilities and public services. Major contractors and consultancies including Balfour Beatty, Arup and AECOM employ civil and rail professionals across the country.
Fees for the United Kingdom: £746 (Pound sterling), with instalments and employer sponsorship available.
Relevant bodies in the United Kingdom
Typical roles
Questions from the United Kingdom
Which UK professional bodies are relevant to civil and rail engineering qualifications?
The Institution of Civil Engineers (ICE), the Institution of Engineering and Technology (IET) and, for rail, bodies such as the Permanent Way Institution and the Institution of Railway Signal Engineers are relevant in the UK. Chartered status is handled through the Engineering Council. SEIUM's qualifications are private and not accredited by these bodies, so you should confirm with ICE or the relevant institution how your study would be treated.
Do UK civil, rail and smart city employers recognise online private qualifications?
UK infrastructure employers, including consultancies, contractors, rail operators and local authorities, generally recruit based on competence, professional registration and project experience. A private qualification can add to your profile, but employers decide its relevance. Practical experience and progress towards professional registration usually carry more weight.
How does online study fit with a UK working schedule, and what about funding?
Online study lets you keep working in the UK, and no student visa is needed to study from home. Fees are payable in instalments, and some employers support job-related training, which is common practice in general terms but varies by employer. Each programme has a defined number of hours and an assigned technical tutor. Review the hours and funding options before enrolling.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the key pollutants and parameters of urban environmental quality.
Select environmental sensors according to their measuring principle and limitations.
Design IoT architectures for data capture, communication and storage.
Apply calibration and quality assurance procedures to low-cost sensors.
Build clean, traceable environmental data pipelines.
Develop analytical models and dashboards for decision-making.
Plan a complete environmental monitoring network for an urban area.
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.
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)
8 modules · 800 h
1.1Atmospheric pollutants: PM10, PM2.5, NO₂ and O₃1.2Directive (EU) 2024/2881 on air quality1.3WHO 2021 guideline values1.4Air quality indices1.5Environmental noise and the Lden indicator1.6Water quality in rivers and urban networks1.7Urban microclimate and heat island1.8Emission sources: traffic, industry and heating1.9Official reference networks1.10Case study: air quality diagnosis of a city
2.1Electrochemical gas sensors2.2Optical particle sensors2.3NDIR CO₂ sensors2.4Multiparameter water probes2.5Class 1 and class 2 sound level meters2.6Drift, interference and the effect of humidity2.7Low-cost sensors versus reference equipment2.8Sensor assessment according to CEN/TS 17660-12.9Encapsulation and outdoor protection2.10Laboratory: characterisation of a particle sensor
3.1Nodes, gateways and platform3.2Microcontrollers and data acquisition3.3LoRaWAN, NB-IoT and LTE-M connectivity3.4MQTT and CoAP protocols3.5Solar power and energy management3.6Edge processing3.7FIWARE and Smart Data Models3.8Cybersecurity according to ETSI EN 303 6453.9Network deployment and maintenance3.10Workshop: LoRaWAN node with MQTT transmission
4.1Co-location with reference stations4.2Multivariate regression calibration4.3Machine learning calibration4.4Calibration transfer between nodes4.5Drift detection and recalibration4.6Measurement uncertainty according to the GUM4.7Normative data quality objectives4.8Data validation and flagging4.9Metrological traceability4.10Practical: calibration of co-located NO₂ sensors
5.1Time-series databases5.2Streaming data ingestion5.3Cleaning, filtering and gap handling5.4Temporal and spatial aggregation5.5OGC SensorThings API standard5.6Open data and FAIR principles5.7Data publication APIs5.8Data governance and quality5.9Cloud architectures5.10Workshop: data pipeline for a sensor network
6.1Exploratory analysis of environmental series6.2Anomaly and episode detection6.3Source apportionment by PMF factorisation6.4Spatial interpolation and kriging6.5Gaussian dispersion models6.6Forecasting with ARIMA and LSTM networks6.7Fusion of sensor and satellite data6.8Environmental digital twins6.9Personal exposure and health effects6.10Practical: 24-hour NO₂ forecasting
7.1Dashboards with Grafana7.2Interactive maps with GIS7.3Alerts and information thresholds7.4Communicating with the public7.5Air quality improvement plans7.6Assessment of low-emission zones7.7Citizen science and participatory networks7.8Indicators for municipal managers7.9Privacy and GDPR in urban data7.10Case study: municipal dashboard
8.1Objectives and variables to monitor8.2Sensor selection and assessment8.3Network design and site selection8.4Communications architecture8.5Calibration and quality control plan8.6Data platform and analytics8.7Dashboard and alerts8.8Budget and maintenance plan8.9Report and presentation8.10Final review with the tutor
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.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the key pollutants and parameters of urban environmental quality.
Select environmental sensors according to their measuring principle and limitations.
Design IoT architectures for data capture, communication and storage.
Apply calibration and quality assurance procedures to low-cost sensors.
Build clean, traceable environmental data pipelines.
Where this takes you
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.
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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