IoT projects will slow down and cities will have to decide whether 5G is best for vehicle infrastructure communication, says IDC.
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According to the IDC smart cities team, there will be fewer IoT projects, more input from citizens and more communication between cars and infrastructure in the next decade of working with smart cities.
Urban leaders will build digital trust in new technology by establishing a clear data usage policy as the first step in the technology procurement process.
Although climate change was not on the forecast list, Ruthbea Yesner, vice president of global government insights at IDC, said it is a huge engine for smart city work.
“Cities look at how everything from communication to technology can build community resilience and help them respond and adapt to this changing environment,” said Yesner.
IDC predicts that cities and governments will spend $ 196 billion on smart cities worldwide by 2023. The largest spending categories are fixed visual surveillance, public transport and smart lighting.
IDCs 10 predictions for smart cities will work in five major segments in 2020:
- Public safety
- Data usage
- Talent issues
- Digital trust
- Macro-economic impact of technology
The full list is below. The IDC smart cities team discussed predictions 1, 3, 4 and 10 during a recent webinar.
Roadblocks for IoT success
IDC’s predictions start with a clear description of the challenges that many city leaders face with IoT projects: 10% to 30% of IoT will not start or scale in 2020 due to poor performance data, poor understanding of products and lack of funding .
Yesner said IDC has found that more than 35% of cities have implemented an IoT project, while 12% said they had developed it but not launched it.
In a survey, city leaders said IoT projects got stuck or died due to a lack of internal skills, limited budgets, and a lack of understanding of the benefits of technology. Yesner said there are many roadblocks for success, including a lack of staff and resources.
“Some of these did not meet expectations because the results were too broad or not measurable,” she said.
Yesner said that assumptions often did not match the reality of how cities work. An example of expectations that do not match results is a popular project in which light bulbs are converted into LEDs. Yesner said that because many US cities are paying a flat rate for electricity, officials did not see any cost savings for using less electricity.
“You see energy savings through the conversion, but you get no benefits from programmability and dimming because you don’t adjust costs based on measured energy,” she said.
SEE: Smart cities: a guide for business leaders (free PDF)
Yesner also said that many products from suppliers are untested, immature and resold.
In a related IoT prediction, IDC believes that by 2023, 20% of cyber security incidents will stem from Smart City IoT device implementations, leading to a double-digit increase in cyber security software and staff training budgets.
Cities need a sensor strategy that addresses usage scenarios, data protection, and physical and cyber security plans, she said.
More data ethics policies
Alison Brooks, a vice-president of IDC for smart cities and communities, said that cities will respond to increasing skepticism about surveillance technology by adopting a clear data usage policy.
In No. 3, IDC predicts that 75% of tenders for the next generation of public safety technology will have preventive specifications that are determined by strict policy frameworks. Forecast No. 4 is about data policy.
Brooks said that residents usually accept “intelligence everywhere” data collection in consumer capacity, but not when the state uses a similar approach. She said that proponents of privacy are concerned with the ever broader monitoring of the daily activities of citiising and possible misuse of biometric data.
“This includes social media monitoring, predictive police work, mobile site simulators, automatic number plate recognition, drones and gun detection,” Brooks said.
To respond to these concerns, cities will begin to develop ‘carefully formulated and strictly covered policy frameworks that define acceptable use’. Establishing data usage policies must be the first step in the technical purchasing process.
“Policy must precede technical procurement and IT will need to work with more stakeholders to reduce risk implementation,” she said. “Agencies will have to keep project objectives very simple, limited and measurable.”
Yesner said that cities should build community involvement into every project to ensure ultimate success and even funding.
“If you go to a bond to pay for this work, part of the financing process will make the community fascinating and educational,” Yesner said.
5G versus DSRC for communication between vehicle and infrastructure
IDC’s prediction No. 10 emphasizes a challenge for cities to make it easy for cars and trucks to communicate with city infrastructure such as traffic lights, crosswalks and stop signs.
When municipalities started investing a few years ago in vehicle-to-infrastructure technology (V2I), specific short-distance communication was a viable choice. Now that 5G is becoming available, cities are now in the middle of the debate between two standards.
Max Claps, research director of IDC government insights, said some car manufacturers are split into some with 5G technology – BMW, Mercedes and Ford – while others, including GM and Volkswagen, use DSRC.
IDC predicts that by 2025, 25% of major cities worldwide have chosen one standard or the other and installed the V2I infrastructure.
“We encourage cities to work closely with regulators and automakers to ensure that the final roadmap minimizes investment costs,” Claps said.
He said that cities should also consider how services, storage and apps should be scaled over time.
“Vehicle-to-infrastructure connectivity is only as good as the data and content sent through endpoint to endpoint exchanges,” he said.
Another IDC 5G prediction is that by 2024, 75% of all major cities will use 5G to scale key services, including real-time crime centers, V2I connectivity, and smart stadiums.
IDC Worldwide Smart Cities and Communities: 2020 Predictions
1: In 2020, 10% -30% of Smart City IoT projects will not start or scale due to poorly defined results or KPIs, poor understanding of supplier offerings and / or insufficient funding and stakeholder involvement.
2: By 2021, 20% of cities will use composite indexes to assess the value of initiatives such as predictive policing, mobility as a service and personalized care.
3: By 2021, 75% of the following public procurement for public safety technology, under pressure from citizens and interest groups, will have specifications that are preventively covered by strict policy frameworks.
4: By 2022, 50% of large cities will develop a data ethics policy that determines how and what data can be collected, used and shared.
5: By 2023, 25% of Smart Cities’ successful digital twin platforms will be used to automate processes for increasingly complex, interconnected asset and product ecosystems.
6: By 2023, 20% of cyber security incidents will stem from Smart City IoT device implementations, forcing double digits in cyber security software and staff training budgets.
7: By 2024, 90% of greenfield cities and 20% of existing cities around the world will apply digital space planning capabilities and new zoning rules to realize the benefits of the growing sharing economy.
8: By 2024, 70% of the tasks of city data scientists will not be filled, resulting in more investments in automated process automation and AI-native systems, which will exponentially increase data capacities without staffing.
9: By 2024, a third of all Smart Cities use cases will be affected by 5G and 75% of large cities will use 5G to scale key services such as real-time crime centers, V2I connectivity and smart stadiums.
10: By 2025, 25% of major cities worldwide will have a connected vehicle infrastructure installed using 5G or DSRC as countries and regions settle to one or the other standard.
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IDC’s 2020 predictions for Smart Cities work include this illustration of when each prediction is likely to come true.