Challenges and opportunities that people face in cities are likely to increase with increase as urban populations grow. Internet of Things (IoT) technologies is facilitating growth and improving the quality of living in urban centres. Smart cities rely on devices featuring actuators and sensors. The purpose of these sensors is to help collect data concerning the inhabitants and the infrastructures of a city.
However, the sensors do not change a city into a smart one. The processing and use of the data from the sensors to solve problems makes a city smart. “Central Cloud Management Platforms” collect and process this data for use. After the processing process, the control applications forward commands to actuators, which execute these commands to solve issues.
Unlocking the potential turn to change our cities
Connected Machine Learning (ML) tools provide opportunities of getting insights from the historical data the sensors provide in the data warehouses. ML models help the control applications to automate tasks and make our living comfortable. This is how smart cities are using IoT devices and sensors.
To control road traffic
The movement of people from one point to the other safely is vital in smart cities. Smart cities use various types of smart devices and sensors to guarantee that. In-vehicle mobile apps or sensors, with GPS, help track vehicle locations. Various road-surface sensors help in tracking the speed and the number of motor vehicles passing overhead. In smart cities, traffic lights linked to central cloud management platforms allow monitoring of green lights timings and alteration of other lights to help prevent congestion in real time.
For instance, road-surface sensors can identify any decline of vehicle speed, particularly reduction to 10mph. Control applications rely on programmed rules to identify congestions. To reduce congestion, control applications trigger the output action which platform users define, for example reroute the traffic part and alter traffic lights. Control applications send commands to actuators of traffic lights, which alter the lights. After rerouting of the traffic, the congestion reduces without the need of police intervention.
Use in public transportation
IoT sensors help reveal the patterns of public transport usage in a cities. The agencies use the data to facilitate the travelling experience. Conduction of complex analysis, combination of multiple sources, like traffic information and sale of tickets becomes easier with IoT technology in cities.
In London, for instance, the train operators are using IoT to predict the loading of passengers travelling within and outside the city. The operators combine the data they gather from ticket sales, the movement sensors and the CCTV cameras they have mounted along the platforms to help in decision-making. After the data analysis, they are able to predict how every car loads up with passengers. After a train arrives into the station, the operators encourage travelers to disperse along the train for maximum loading. With maximized capacity usage, the train operators are now avoiding train delays.
IoT usage for utilities
Smart cities equipped with IoT provide individuals with more control over home utilities and therefore helps them save more money. With networks of smart meters, utilities provide better services to the consumers. A smart meter, suing telecom network, can directly forward data to the public utility and provide more reliable meter readings. The smart meters also facilitate accurate billing for the used amount of energy, gas, or water each household has consumed.
Networks of smart meters enable utilities to gain better visibility and monitor the consumption of water and energy. With these networks, public utilities monitor the demand, redirect resources according to need, and encourage the consumers to use lesser water and energy, in case of a shortage.
Moreover, IoT technology has facilitated efficient remote monitoring of utilities. The services allow households to use smart meters to monitor their usage remotely. For example, a householder can use a smartphone to turn off the central heating in their home off. In case of a problem, such water leakage, the utility company will notify the household immediately and send a group of specialists to fix the issue.
IoT usage in street lighting
Smart cities are using IoT technologies to make the maintenance and control of streets lamps cost-effective and straightforward. Fitting street lamps with actuators and sensors and connecting them to cloud management platforms, makes them IoT devices.
The connectivity allows remote management of street lighting. The users also set rules that trigger some actions like brighten, dim, turn off and turn off the lights depending on the data concerning the environment of the device. A quick example, streetlights near pedestrian crossings switch to bright setting when a pedestrian starts crossing the road.
Integration of streetlights with the collected data, such as data from transport networks, makes dynamic control of infrastructure possible. For instance, when a bus enters a bus stop, the streetlights near it become brighter than the others are. That happens automatically.
Usage in waste management
Waste collection operators rely on set schedules when it comes to emptying containers. We cannot call that an efficient approach and it has led to fuel wastage and unimportant usage of city assets. Smart city solutions equipped with IoT are able to track the waste levels and to offer operational analytics and route optimization.
Fill level sensors forward data to a cloud management platform for better analysis. When the garbage containers are ready for emptying, the integrated control applications use the defined rules to alert the truck driver. That helps reduce chances of emptying half-full containers and facilitate better management of containers in an area.
Safety
Advancement of internet of things in cities plays a vital role in public safety. Gunshot detections are among the commonest cases. IoT sensors and devices can recognize when a gunshot is fired in a public area to help the security agencies take the necessary steps. The safety tools rely on connected microphones situated in various parts of the city. For the systems to work, the microphone has to pass this data to the primary management platform, which analyses the sound and detects the gunshot.
These analytics tools along with other platforms measure the occurrence time, the amount of time the gun sound took to hit a microphone and the gunshot’s location. After identification of a gunshot and place, control applications use set rules to alarm the police through their mobile applications.
