The utilities industry is undergoing a transformation driven by technological advancements. This paper discusses how emerging technologies such as GPS, LiDAR, AI and Automation, are influencing asset data collection practices and significantly reducing the time required to update records, ultimately enhancing asset management efficiency. 

Traditional asset data collection methods can be time-consuming and prone to inaccuracies. This means that companies must invest significant resource to validate and process data to meet regulatory targets such as 42 days to update to the live layer in the Gas Industry. There is a view across Industries that we need to update records faster to ensure a safer more reliable Network, highlighting the need for innovative technological solutions that streamline record updates. Such as: 

GPS for Asset Location and Tracking 

Global Positioning System (GPS) technology enhances asset data collection by providing precise location tracking of utility assets. This capability allows for quick mapping of infrastructure and facilitates efficient maintenance operations. With GPS, technicians can easily locate assets without lengthy manual searches, drastically reducing the time needed to update records related to asset location, maintenance history, and operational status. 

LiDAR for High-Resolution Mapping 

Light Detection and Ranging (LiDAR) technology is utilized for high-resolution mapping and surveying, generating detailed 3D models of utility infrastructure. By capturing extensive spatial data quickly, LiDAR allows utilities to assess asset conditions and update records in real time. This technology significantly reduces the time required for inspections and record updates by providing immediate data on asset health and environmental factors affecting them. 

Big Data Analytics 

Big data analytics empowers utilities to process and analyse the vast amounts of data generated from GPS, LiDAR and many other data sources. By leveraging advanced analytics tools, utilities can automate data interpretation, identify patterns, and generate insights faster than traditional methods. This capability not only helps in predictive maintenance but also accelerates the updating of records by automatically flagging changes or discrepancies that require attention. 

Machine Learning and AI 

Machine learning algorithms further enhance the efficiency of record updates by analysing historical data to refine predictive models and optimize maintenance and replacement schedules. AI-driven systems can automatically update records based on real-time data inputs, ensuring that asset management systems reflect the most current information without the need for manual intervention. This minimizes delays associated with record-keeping and improves overall data accuracy. 

Automation and Remote Monitoring 

Automation technologies, including drones and robotics, significantly improve asset data collection and record updating. Drones equipped with cameras and sensors can perform aerial inspections, capturing data quickly and accurately. This data is then transmitted to central systems, allowing for immediate updates to asset records. Remote monitoring capabilities also enable utilities to track asset conditions continuously, ensuring that records are always current without the need for physical inspections. 

So, what are the Challenges……… 

While the integration of these technologies offers substantial benefits, challenges such as cybersecurity risks (such as adversarial attacks), data privacy concerns (AI storage of personal data) and ensuring data integrity (avoidance of data drift) during rapid record updates is crucial for maintaining operational trust.  

Another major challenge is the adoption of technologies in the field. The integration of new technologies with legacy systems often presents compatibility issues, requiring engineers to navigate new transitions. This can be compounded by concern of safety and compliance, as new tools and methods must adhere to stringent regulations while ensuring the safety of personnel and the public. For example, using GPS to capture data will involve using a pole to get the GPS signal and therefore the appropriate risk assessments should be carried out to ensure safe practices are followed.  

Resistance to change is likely making it vital for leaders to foster a culture that embraces innovation and supports their people and for change delivery teams to be cognisant of the above challenges and tailor their delivery approach accordingly. 

Conclusion 

Technology is significantly reshaping asset data collection in the utilities industry. By adopting GPS, LiDAR, data analytics, and automation, utilities can not only enhance their asset management processes but also drastically reduce the time required to update records. This efficiency leads to improved operational reliability and better service delivery. 

Call to Action for Utilities Companies  

• Choose the right solution for your problem – there is no ‘one size fits all’ solution   

• Phase adoption of technology to reduce workforce shock and increase stickability  

• Address resistance to change through advocating super users and bringing your people along the journey with you  

• Invest heavily in training for all users to build the right ‘tech savvy’ capability within your workforce  

Daniel Smith is a Senior Delivery Manager at Skewb, to speak with him about this topic in more detail, you can connect with him on LinkedIn.