There is no one-size-fits-all solution, but government leaders will need systems integrators to make these IoT projects a success.
Government agencies managing multiple sources of Internet of Things (IoT) data are most likely to launch edge computing projects to save money and improve city services, according to an IDC government analyst.
Shawn P. McCarthy, research director for IDC Government Insights, predicts that local governments and the military will lead the way in adopting artificial intelligence (AI) to reduce fraud, improve services, and increase compliance. McCarty discussed these predictions as well as the current market during a webinar, "Edge Computing, 5G & AI: Government's Exponential Perfect Storm."
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"Integrating this data can save money, and that's where you're going to see most of the growth happen," he said.
The benefits of distributed AI are a positive return on investment, lower costs, focused efficiencies and data-driven decision making, but the required processing power is a significant challenge, he added.
Artificial intelligence is already improving government operations from fine-tuning maintenance schedules for Air Force planes to reducing pedestrian deaths on city streets. Other use cases for edge computing and IoT projects include:
McCarthy said some data analysis must be done at the edge to get the benefit of real-time analysis.
"When processing is done at the data center or in the cloud, you don't gain speed, you don't boost agility, and you have fewer options for fast automated responses," he said.
He described the AI opportunities along the entire spectrum of IoT platform elements as "small footprint AI," a smart device that does one task very well, as compared to Alexa, an AI device that has many capabilities.
No one-size-fits-all solutionIDC's Global IoT Decision Maker Survey 2019 found that federal government agencies are doing the most edge computing with about 25% of all IoT data collected and processed at the edge. Cities have the most edge-based computation requirements and process about 20% of the data collected at the edge. States and territories are lagging in this area but they also don't have to be outfront because they are not collecting the data. Across federal, state, and local governments, most data is processed through a hybrid model with some processed at the edge and the rest sent to a data center.
SEE: IoT: Major threats and security tips for devices (free PDF) (TechRepublic) Because of the complexity of the systems that these entities are managing, city managers will need systems integrators to make these projects a success.
McCarthy also shared these major IoT trends across all industries:
McCarthy said progress in edge computing is moving at different rates across different levels of government, reinforcing the idea that there is no one-size-fits-all solution.
"The best growth opportunities are at agencies with multi-structured data sources that can be used to create new solutions, build better services, and optimize operations," he said.
To make the case for IoT investments, city leaders should determine whether the project could reduce existing IT costs and whether the solutions could improve service levels to residents.
McCarthy also suggested this list of questions for government agencies trying to figure out how to get started with IoT projects:
Understanding these issues is a major step toward deciding if distributed AI is needed, he added.
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Shawn P. McCarthy, research director for IDC Government Insights, said some data analysis must be done at the edge to get the benefit of real-time analysis.
Image: IDC
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