In the era of globalization and urbanization, the population that once lived in rural areas is shifting towards cities for a better lifestyle. According to the United Nations, 55% of people live in urban areas, and this number is expected to increase to 68% by 2050.
Key Takeaways
- IoT and AI are transforming cities into smarter, more efficient, and sustainable urban environments.
- Smart cities use IoT sensors for energy monitoring, smart poles for data collection, and advanced infrastructure for autonomous transportation.
- Cloud computing and edge technology are crucial for managing the massive amounts of data generated by IoT networks in smart cities.
- AI-powered smart cities offer benefits such as improved safety procedures, better quality of life, and enhanced sustainability measures.
- Key risks in smart cities include cybersecurity threats, data privacy concerns, and potential technological biases.
- Singapore, Oslo, and Amsterdam are leading examples of cities successfully implementing IoT and AI technologies for urban improvement.
IoT and AI are essential to transform rapidly growing cities into smarter, more efficient, and more sustainable ways. Earlier, smart cities felt like a pipedream to achieve. Today, it is the solution, leveraging advanced technologies to optimize infrastructure and services.
IoT and AI Redefining Smart City
The word “AI” has become quite common, appearing in contexts outside of science fiction and influencing our daily interactions. However, what does it imply in the larger context of smart cities? Unlike the robots in movies, their use cases are frequently far more practical.
1. Smart Energy
Smart cities use IoT sensors to track and monitor energy usage, which is one example of AI making cities smarter. By analyzing energy usage, smart cities provide authorities with real-time data to optimize energy consumption and save costs.
2. Smart Poles
Smart poles are another example of IoT technology driving the next wave of innovation in smart cities. Numerous features, such as wireless networking, lighting, and environmental monitoring, are built into these intelligent buildings. Smart poles outfitted with sensors and cameras, can record and relay data instantaneously, empowering city managers to make well-informed decisions grounded in the most precise and current data.
3. Smart Infrastructure
How we think about urban transportation has also started to change because of AI. Autonomous transportation is the way of the future, but before this seemingly futuristic idea becomes a reality, communities need to invest wisely in smart infrastructure. To be entirely autonomous, a vehicle must accurately sense its surroundings.
This requires sophisticated sensors and other smart city technologies to collaborate within a networked framework. Smart infrastructure will be critical to fulfilling the business’s potential as we move closer to the adoption of self-driving cars.
Role of Cloud in Handling Large Volumes of Data
Cloud computing is critical in managing the massive amounts of data generated through IoT networks. In 2021, there were 10 billion IoT devices in the world, and by 2025 global data generation will exceed 73 gigabytes.
5G is becoming accessible in cities, but many smart cities worldwide still lack network connectivity. Edge computing, a distributed computing paradigm that places computers and data storage closer to data sources, responds to this.
Instead of sending data to a distant data center for processing, edge technology enables quicker decision-making and data processing within the device. As a result, response times are faster, which is important for controlling and guaranteeing the success of the high bandwidth technologies required for smart cities.
Benefits of AI-Powered Smart Cities
IoT smart cities driven by AI are revolutionizing urban environments and providing significant advantages in various areas.
1. Safety Procedures
Cities use audio and vision-based technologies to reduce incident response times and increase safety. Although privacy concerns may arise from surveillance-based initiatives, cities can mitigate these issues by collaborating with vendors who adhere to principles, instituting data retention policies, and actively involving the community in camera-based deployments.
2. Quality of Life
People’s daily lives can be made better by technology if they use it to improve their government services, air quality, and commuting. The city provides services like hyperlocal air quality data and contextual maps that can layer other datasets, like financial inclusion data by area, on top of this digital infrastructure by utilizing linked assets and sensors.
3. Sustainability
City leaders prioritize sustainability when managing resource consumption, migration, and climatic events. Cities have used digital twins to better prepare for urban flooding by predicting which regions of the city may be most vulnerable. A vulnerability map allows the city to better prepare for and prevent flood consequences during weather occurrences.
What are the Key Risks Involved?
With every new technological development, there are worries about potential risks and unforeseen effects from its use. These dangers are heightened in the context of cities and government organizations because of the role public services play and the sensitive nature of the data at stake.
1. Cyber Security & Resilience
Cybercrooks are better able to launch cyberattacks and exploit gaps in the networks, sensors, and communication systems that make up smart cities’ interconnected infrastructure.
Assaults on vital infrastructure, like electricity grids and transportation networks, may involve ransomware assaults, identity theft, and data breaches. Large-scale repercussions from these hacks might jeopardize economic stability, public safety, and the continuous provision of basic services.
2. Data Privacy
The widespread deployment of sensors and video-based surveillance systems in AI smart cities results in the accumulation of massive amounts of personal information. This data includes people’s movements, behaviors, preferences, and interactions with urban infrastructure.
The collection of such sensitive information poses substantial privacy hazards, as citizens may be concerned about constant monitoring of their activities in public settings and the possibility of data misuse or exploitation by government or corporate groups.
3. Biasness
A further risk to equity in AI smart cities is the rise of the tech gap, since older populations may find it difficult to utilize high-speed internet or to adjust to smart city programs. These differences in digital literacy and technology access may make it more difficult for some people to utilize advanced digital services.
Some Use Cases on AI and IoT in Smart Cities
Globally, many cities have effectively integrated AI software development and IoT technology to enhance their creativity and productivity.
1. Singapore
Singapore is generally considered to be at the forefront. The population of the nation is aging, and the government is concentrating on digital technology and programs to increase productivity in the developed nation’s economy. This has included the transition to a digital healthcare system, which has normalized video consultations and introduced wearable Internet of Things devices for remote patient monitoring.
2. Oslo
Oslo is a smart city that prioritizes the development of an environmentally friendly, sustainable environment. Although smart cities and sustainable cities frequently have many of the same objectives, they are not the same. A city does not have to be intelligent to be sustainable. But in this instance, Oslo meets both requirements.
With over 650,000 LED lights across the city, all of which are linked to processing stations, the lights can intelligently modify lighting levels based on demand.
3. Amsterdam
Amsterdam places a high priority on environmentally friendly transportation, including bike lanes and electric car charging stations. Efficient traffic management is ensured by smart traffic systems, and environmental monitoring leads to better air quality and energy savings.
Infrastructure is improved via waste bin sensors and intelligent street lighting. The city’s dedication to sustainability and connection is fueled by a robust innovation environment and widespread Wi-Fi, making Amsterdam a role model for smart urban living.
Conclusion
The continued advancement of mobile technology, made possible by IoT app development services and AI, shows that connectivity is certainly feasible while maintaining sustainability. This will be accomplished in smart cities at two levels: the micro level, by individual users of increasingly sustainable technologies, and the macro level, by governments and multinational enterprises.
The dwellings in the future’s smart cities will employ IoT to become an integrated ecosystem that aims to increase efficiency and lower operating costs, making life easier and more comfortable for inhabitants, as opposed to a collection of disconnected smart gadgets.
