AVOIDING DISASTER the horizon , such as performance based regulation . This is being considered , with multi-year plans incentivising utilities to modernise their operations and align customer needs with company goals and policy goals . For example , Minnesota uses a multi-year plan that , according to state legislature , can replace annual rates as long as it bases a portion of utility revenue on encouraging efficiency . Rates are also reasonably in line with the costs of service during the time period .
The introduction of intelligently integrated systems for location-based DOM would provide the assessment and management that utilities require to improve responsiveness . It would enable them to move away from being reactive , towards a process that helps them anticipate , plan and execute methods to reduce the impact of disasters . Even utilities that proactively mobilise without an outage or damage forecast model get it wrong ; most either over- or under-prepare . Predictive damage assessment tools can now leverage machine learning , historical and big data analytics to improve damage forecast modelling , drawing on past data sets to produce accurate and reliable estimates of the damage that assets can sustain . In addition , by automating processes , they can learn and respond to the evolving climatic scenarios .
The communication between data is strengthened by the integration of formerly disparate systems , such as command control centres , weather information and field damage assessment . A 2016 report funded by the UK ’ s Department for International Development ( DfID ) assessed the application of big data for climate change and disaster resilience . It demonstrated how big data could be used in the early detection of floods by gathering and analysing information about flooding from social media feeds with satellite observations . Scientists De Groeve , Kugler and Brakenridge were then able to build a real-time map of the location , timing and impact of floods .
The latest data sources generated and used by utilities , such as LiDAR , 3D imagery and Internet-Of-Things ( IoT ) sensor data , can also be integrated to enable better decisionmaking . For example , the use of IoT in the electric power industry enhances the grid ’ s resilience and durability
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