Postgraduate Diploma in AAL, Home Sensing and Security
Online 800-hour Postgraduate Diploma in AAL, Home Sensing and Security. 8 modules covering UNE-EN 50134 (social alarm systems), IEC 60601-1-11 (electromedical equipment in the domestic environment) and Home Assistant. Personal tutor assigned and enrolment open.
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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
Define the objectives and service models of ambient assisted living.
Select domestic sensors suitable for monitoring activity and environment.
Integrate heterogeneous devices using interoperable communication protocols.
Develop algorithms for detecting activity, falls and anomalies.
Apply cybersecurity and functional safety measures to the AAL system.
Ensure compliance with privacy and data protection regulations.
Design solutions centred on older users and their carers.
Who it's for
- AAL solutions engineer wishing to specialise in AAL, Home Sensing and Security.
- IoT developer wishing to specialise in AAL, Home Sensing and Security.
- Telecare specialist wishing to specialise in AAL, Home Sensing and Security.
- Home automation engineer wishing to specialise in AAL, Home Sensing and Security.
- Privacy manager for care services wishing to specialise in AAL, Home Sensing and Security.
- User experience designer wishing to specialise in AAL, Home Sensing and Security.
- Graduates in engineering or sciences seeking to enter the telecare sector.
What you'll work with
- UNE-EN 50134 (social alarm systems)
- IEC 60601-1-11 (electromedical equipment in the domestic environment)
- ETSI EN 303 645 (consumer IoT cybersecurity)
- Regulation (EU) 2016/679 (GDPR)
- Directive (EU) 2019/882 (accessibility requirements)
- ISO 9241-210 (human-centred design)
8 modules · 800 h
1.1Active ageing and independent living1.2European AAL programme and its results1.3Needs of older and dependent people1.4Connected home and adapted housing1.5Stakeholders: users, carers and services1.6Telecare service models1.7Technology acceptance by older people1.8Ethics and user autonomy1.9Success stories and failures1.10Case study: analysis of a European AAL pilot
2.1PIR and presence sensors2.2Door, bed and chair sensors2.3Consumption meters as an activity indicator2.4Millimetre-wave radar2.5Environmental sensors: temperature, CO and smoke2.6Depth cameras and privacy2.7Wearables and emergency pendants2.8Sensor placement in the home2.9Calibration and maintenance2.10Laboratory: deployment of a domestic sensor network
3.1Zigbee, Z-Wave, Thread and Matter3.2BLE and Wi-Fi in home devices3.3Gateways and edge computing3.4MQTT and CoAP protocols3.5Interoperability with HL7 FHIR3.6IEEE 11073 standards for personal devices3.7Continua Design Guidelines3.8Link reliability and redundancy3.9Power consumption and battery life3.10Workshop: integrating sensors into an MQTT gateway
4.1Recognition of daily activities4.2Routine models and deviations4.3Fall detection: accelerometer and radar4.4Detection of nocturnal wandering4.5Sleep analysis at home4.6Machine learning with small datasets4.7False positives and alarm fatigue4.8Evaluation using sensitivity and specificity4.9Public datasets4.10Practice: fall detector using accelerometer data
5.1Physical safety: fire, gas and flooding5.2Alarm management and escalation5.3Receiving centres and standard EN 501345.4Cybersecurity in domestic IoT5.5ETSI EN 303 6455.6Secure firmware updates5.7Authentication and access control5.8Continuity during network and power outages5.9Risk analysis with ISO 149715.10Case study: threat analysis of an AAL system
6.1GDPR and health data in the home6.2Data protection impact assessment6.3Consent from people with cognitive impairment6.4MDR regulation and health software6.5Dependency law and social services6.6Accessibility under EN 301 5496.7Liability for detection failures6.8CCTV and proportionality6.9Ethics of continuous monitoring6.10Practice: impact assessment of a sensor system
7.1Co-design methods with older people7.2Voice interfaces and simplified screens7.3Design for visual and hearing impairment7.4In-home installation and training7.5Usability evaluation with SUS7.6Pilot trials in real homes7.7Business models and reimbursement7.8Integration with health and social care services7.9Quality-of-life impact indicators7.10Case study: evaluation of an advanced telecare pilot
8.1Definition of users and needs8.2Sensor selection8.3Communications architecture8.4Detection algorithms8.5Safety and alarm plan8.6Privacy assessment8.7Pilot plan and evaluation8.8Service model8.9Report and presentation8.10Final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Home Assistant, Node-RED, Eclipse Mosquitto (MQTT), Python (scikit-learn), in free, academic or evaluation versions. Trials are studied using real domestic living lab procedures, fall-detection tests and evaluation with older people. 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.
Define the objectives and service models of ambient assisted living.
Select domestic sensors suitable for monitoring activity and environment.
Integrate heterogeneous devices using interoperable communication protocols.
Develop algorithms for detecting activity, falls and anomalies.
Apply cybersecurity and functional safety measures to the AAL system.
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 command of Spanish to follow technical standards documentation.
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. That is between 10 and 15 hours per week on average, compatible with full-time work.
The programme works with Home Assistant, Node-RED, Eclipse Mosquitto (MQTT), Python (scikit-learn). 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 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 are recognised towards the higher programme. Please check the recognition policy when you enrol.
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