Exploring consumer technology solutions to address Ireland's housing crisis
This report investigates the potential of consumer-grade LiDAR and photogrammetry technology to transform property assessment of derelict buildings in Ireland, addressing a key barrier to housing redevelopment.
Ireland is currently facing a severe housing crisis, with approximately 81,000 abandoned properties scattered across the country. While many of these buildings could be repurposed to address housing shortages, redevelopment remains slow due to a combination of financial, bureaucratic, and logistical barriers.
A key challenge in this process is the uncertainty surrounding initial property evaluations, which can be costly, time-consuming, and often reliant on subjective assessments. Traditional evaluation methods require professional surveyors or architects to conduct manual site inspections, draft sketches, and document structural conditions.
"A key challenge in tackling vacancy and dereliction is the identification of properties and sites that are vacant or underutilised." - Housing Agency of Ireland, 2024
This research explores whether affordable, accessible technology can disrupt this process, making property assessment more efficient, accurate, and accessible to a wider range of stakeholders including local authorities, community housing organisations, and individual property owners.
Recent policy initiatives have attempted to address this issue through taxation measures and grants for renovation, but practical barriers remain:
Fig 1: A derelict homestead outside Carrickmacross, County Monaghan (Newstalk, 2025)
Consumer technology has recently reached a turning point with the introduction of LiDAR sensors in mainstream devices like the iPhone 12 Pro (2020) and iPad Pro. These sensors use invisible laser pulses to measure distances with millimetre accuracy, creating detailed 3D models of physical spaces.
This research employed a mixed-methods approach combining technical evaluation, comparative analysis, and stakeholder feedback.
Primary LiDAR capture device
LiDAR scanning software
3D model optimisation
Consumer-grade LiDAR technology demonstrated remarkable effectiveness for property assessment, with significant advantages in cost, time, and accessibility while maintaining professional-grade accuracy.
LiDAR measurements achieved 97% accuracy compared to professional measurements, with a margin of error of only ±3cm for most structural elements.
Property scanning required only 1-2 hours per property on average, compared to 4-6 hours for traditional assessment methods, representing an 83% time saving.
Implementation costs were reduced by approximately 78%, with each property assessment costing under €600 compared to the traditional €2,800-€11,000 range.
Performance degradation in extremely low-light environments, though still superior to traditional photography.
Visual assessment only; cannot detect internal structural issues without supplementary technologies.
Currently limited to premium Apple devices, though Android equivalents are emerging in the market.
A derelict bungalow in Carlow was scanned using the LiDAR methodology, and a 3D model was created for evaluation.
The LiDAR assessment was conducted at no cost, taking 2 hours, including processing time.
During survey measurements from the LiDAR model showed an average deviation of only 3%cm from the actual propert measurements (97% accuracy).
It is estimated that the ability to revisit the property virtually through the 3D model would save approximately €1,200 in additional site visits during a planning phase.
The findings from this research suggest several promising applications for LiDAR technology in addressing Ireland's housing crisis:
Creation of a comprehensive database of vacant and derelict properties with 3D models accessible to housing agencies and developers.
Empowering community housing organisations with affordable assessment tools to identify and evaluate suitable properties.
Enabling more efficient planning and decision-making processes through virtual property tours and accurate digital records.
Developing machine learning algorithms to automatically identify structural issues from LiDAR scans
Creating seamless workflows between LiDAR scans and Building Information Modelling platforms
Using repeat scans to track building movement and deterioration over time
If you're interested in this research or would like to discuss potential applications or collaborations, please get in touch.
Program: Information Technology Management
Institution: South East Technological University
Email: dylanodonnell0161@gmail.com
Position: Professor
Department: Computer & Networking
Institution: South East Technological University
Email: enda.dunican@setu.ie