What is the Role of IoT & Machine Learning in Smart Cities?
The global population has entered the peak phase of modernization, which involves easy access to cutting edge technology. If you are living in an urban setup, you are already surrounded by an intelligent network of interconnected gadgets that are part of your daily routine. The idea of a ‘smart city’ can be defined as a sustainable framework that comprises information data and communication technologies to create & organize practices that smartly support urbanization.
What is essential for planning a smart city? The discussed framework comprises wireless technologies such as interconnected devices and the cloud, thereby acquiring a significant share. To endorse such a concept the likes of the Internet of things (IoT) & Machine learning (ML) are preferred without any doubt. These technologies are capable of absorbing the various demands of urbanization through the delivery of innovative and smarter options aimed towards comfortable living.
“Smart Cities are those who manage their resources efficiently. Traffic, public services and disaster response should be operated intelligently in order to minimize costs, reduce carbon emissions and increase performance” –
IoT applications’ presence is to manage and examine real-time data that collaborates with machine learning and works to assist municipalities, citizens, and organizations in upgrading the quality of living. According to Statista, It is estimated that the global share of people residing in urban areas will rise to 70% by 2050, as compared to 56% in 2020.
IoT in Smart City
Transforming any city into a smart city requires the active deployment of IoT technologies. You can look around and pick up several practical examples across different industries like manufacturing, healthcare, and transportation. The extensiveness of the internet across global regions is the core of IoT applications. Apart from the reduced cost of connection, the introduction of better gadgets with sophisticated sensors and Wi-Fi connectivity contributes to smarter involvement of the Internet of Things.
AI/ML in Smart City
The availability of intelligent machines through Artificial Intelligence (AI) & Machine Learning (ML) has been crucial in escalating the concept of smart cities. You can now incorporate sharp computing programs merged with human intelligence to create a cyber-physical space that includes traffic sensors, video cameras, environment sensors, smart meters, etc. Data acquisition is carried out on a regular basis to frame actionable insights targeted towards intelligent city planning.
Combined Applications of IoT & ML in Smart Cities
Intelligent Parking Systems
Since we are already familiar with IoT’s role across vehicle tracking platforms, its merger with ML can be used to support smart parking systems. These systems aim to spot vacant locations for a vehicle to be parked, especially in public places.
How does this technology function? An In-Ground vehicle detection sensor’s presence makes it possible as they are implanted within the pavement of various parking spaces. They are responsible for collecting data comprising time and duration for which space has been occupied by vehicles. Later, the data is transferred to the cloud to be processed and sent to the drivers searching for empty parking spaces.
Machine learning algorithms are also put in place to highlight peak hours that are possible with the comprehensive analysis of past trends and real-time data. The availability of an intelligent parking system is beneficial in reducing pointless congestion and fuel costs for people.
To uplift public safety within an urban city, you can actively use IoT technologies that are focused on providing real-time information via CCTV cameras and sensing tools. The comprehensive data collected using these systems help forecast potential criminal activities and implement safety measures.
For instance, the most striking arrangement of safety management is the deployment of the gunshot detection system. It involves connected microphones that are set up in different parts of the city. They collect sound patterns on a regular basis that is later passed onto the cloud platforms for processing. Machine learning is then introduced to filter out the sound of a gunshot. Interestingly, vital factors such as the gun’s location can also be estimated by calculating the sound’s speed reaching the sensor.
Smart Traffic Administration
Transportation is one prime aspect that can achieve a smoother arrangement with the inclusion of smart traffic solutions. The aim is to achieve avoid vehicle coagulation and help citizens save time and fuel. This can be achieved by deploying various sensors that can record speed, location, and other important information related to your vehicle.
Some of the useful systems included in smart traffic management are:
- CCTV cameras
- Road-surface sensors
- Traffic management platform
All these systems together help collect real-time data, which is then analyzed using machine learning. Hence, the user is served with updates related to traffic congestion, road divergence, and other related info. Furthermore, historical data can also be examined with the help of machine learning to highlight peak rush hours beforehand.
Water Management Plan
Water supply and conservation are part of sustainable living for urban cities. The act of setting up a water management system that includes devices such as smart meters is proving helpful to track down water consumption. Furthermore, average consumption for each household, enterprise, or industry can be evaluated using ML technology. Future consumption stats can also be assessed with machine learning algorithms applied to past data.
A smart water management system is efficient in improving water distribution across a city without compromising water pressure and quality. At present, several cities across the globe have started the use of these smart meters to avert potential leaks across underground water pipelines.
Smart Street Lamps
The operation of street lamps can be conveniently managed with IoT devices playing their part. Smart cities are now getting decorated with sensor-fitted street lamps that are linked to cloud platforms. These sensors are responsible for collecting information related to
The sensors help gather relevant data on radiance, schedule of public transport, operational timing, etc. Real-time data availability is useful to analyze various scenarios when merged with historical data and machine learning. Hence, smart lighting solutions help control the brightness and power on/off for streetlights based on traffic volume, timings, and environmental conditions.
The world is heading towards a supremely computerized environment well channelized by modern age technologies such as IoT, machine learning, and artificial intelligence. As mentioned above, we have discussed the application and usage of these technologies for planning a smart city that offers relaxed and comfortable living. For the perfect implementation of new technologies and IoT devices, collaboration with digital transformation experts and software testing providers is a must. It is expected that in the near future the knowledge of such professionals will be applied to remodel multiple cities around the globe.