Regionally, the Asia Pacific followed by Europe and North America are currently the largest markets for smart meter shipments and predicted to continue to be throughout the forecast period.
But ABI cautions that there’s a significant price pressure for lower cost smart meters in the Asia Pacific and Europe regions that is slowing revenue growth over the forecast period.
In the APAC region, ABI says that India is coming out of successful pilots and preparing for large-scale roll-outs of smart electricity meters to replace over 300 million metering points.
“As smart electricity meter roll-outs near completion in China, there is an increasing focus on utility smart gas and water meter roll-outs. LPWA network technologies will be popular choices for these metering segments with LoRaWAN technology from ZTE CLAA in China and TATA communications in India competing with telcos’ NB-IoT networks in the region,” said Adarsh Krishnan, principal analyst at ABI Research.
“In Europe, there’s a steady ramp-up of smart meter shipments until 2019 with strong growth in electricity and gas metering shipments. The growing footprint of LPWA networks in Europe will drive the uptake of smart metering infrastructure among water utilities to become the second largest market after the Asia Pacific region.”
ABI says the projected global revenue growth is welcome news in a market where smart electricity shipments are contracting and greatly slowing growth of overall revenues across the entire metering segment.
The report says that energy and water utility meter installations will result in annual shipments of 151 million smart meters in 2018 and will grow at a CAGR of 3.2% to reach 193 million units by 2026.
ABI reports that utilities are currently the leading adopters of IoT technology, deploying 618 million smart meters in 2018, while meter-to-cash is the primary application driver for smart meter implementation and monetisation opportunities for both energy and water utilities.
“Operating in data-rich environments, energy utilities are starting to spend more on implementing analytics platforms using machine learning and Artificial Intelligence (AI) to not only improve customer experience but also to improve energy efficiency, reliability and identify early potential infrastructure and service issues,” Krishnan said.