The fleet management industry can develop smart and intelligent transportation systems with the incorporation of sensor technology and IoT.
Sensors are nowadays used to monitor and predict the weather, climate, traffic patterns, and other elements. Fleets are rapidly embracing sensor solutions that help them become more efficient, effective, and cost-effective by eliminating errors and enhancing responsibility. Sensors can be used to evaluate the physical well-being of a driver or a group of drivers to identify causes that lead to accidents or injuries. The goal is to increase the fleet's safety and the employees' health.
How sensor can help fleet management?
In-vehicle and on-road infrastructures use IoT and sensor technologies to collect data on environmental and traffic conditions, which may then be analyzed to improve transportation safety and efficiency.
Sensors in vehicles read engine performance, pressure, light, and mechanical faults, such as tyre pressure, brakes, and so on. Sensors are deployed in a variety of applications to achieve better mobility, environmental sustainability, and economic development.
Different Types of Sensors used in Automobiles
Sensors inform the vehicle's computer of what is happening in the engine and other components. Sensors of various types are used in the design of modern vehicles. The fuel-air mixture, intake air temperature, tyre revolution, and manifold pressure are all measured and relayed to the computers. Depending on the application, the sensor can be classified as follows.
Sensors for safety
Sensors for diagnostics
Sensors for convenience
Sensors for environment monitoring
Types of Sensors used in Automobiles
The following are some of the most common sensors found in vehicles.
Mass Airflow Sensor (MAF): This sensor measures the air density in the engine. The MAF determines the mass flow rate of air into a fuel-injected internal combustion engine.
Engine Speed Sensor: The engine speed sensor monitors the crankshaft's rotational speed. The engine speed sensor provides input to control fuel injection and engine timing.
Oxygen Sensor: The oxygen sensor examines the content of exhaust gases for the proportion of oxygen. It is fitted on the exhaust manifold. The data is compared to the oxygen concentration of ambient air to determine whether the engine is running on a rich or lean fuel ratio. Engine computer gets this data to decide the fuel metering strategy and pollution controls.
Spark Knock Sensor: To prevent troubles in a car's engine, the spark knock sensor checks to examine if the fuel is burning smoothly.
Some other important sensors used in vehicles.
Manifold Absolute Pressure (MAF) Sensor
Fuel Temperature Sensor
Camshaft Position Sensor
Throttle Position Sensor
Vehicle Speed Sensor
Applications of In-Vehicle Sensors
Tyre-pressure monitoring: To warn drivers if the tyre air pressure is low using an audio, light, or vibration warning.
Proximity sensors: To detect an object when it approaches the vehicle. Proximity, ultrasonic, and electromagnetic sensors are employed in parking and reverse warning applications.
Ultrasonic sensors: These sensors use sonar technology to calculate the distance between a vehicle and an object, alerting the driver when the vehicle approaches a predetermined distance.
Electromagnetic: EM sensors alert the driver when an object enters an electromagnetic field produced around the front and back bumpers.
RADAR and laser sensors: RADAR constantly scans the road for forward, side, and rear collisions. To avoid potential crashes, RADAR allows safety applications to reduce power and activate brakes. When the vehicle changes lanes or drifts out of the lane, RADAR and speed sensors warn the driver of the potential danger. The driver is alerted by vibrations in the seat or steering wheel, or by an audible alarm.
Inertial Navigation Systems: Gyroscope and accelerometer sensors are used to detect the vehicle's properties, such as position, orientation, and velocity. To improve accuracy, INS is used in conjunction with global positioning systems (GPS).
Camera: The driver's body posture, head position, and eye activity are all monitored using cameras. Drivers can see further down the road and notice anything such as animals, people, or trees in their way using night vision camera software, which could cause a potentially dangerous situation or an accident.
LiDAR: Light Detection and Ranging is a key component in the development of autonomous vehicles. With a few unique qualities like continuous 360-degree sight and highly precise depth information, LiDAR allows a self-driving car to monitor its surroundings. LiDAR sensors emit laser light beams at predetermined intervals and then measure how long it takes the light to return to the sensor.
Sensors continuously monitor vehicle performance, allowing drivers to drive more efficiently. These data might also be provided to management from remote, and these figures allow the fleet manager to take further data-driven actions to increase fleet availability and efficiency. More data means more information, enabling fleet managers to take proactive measures and run their fleet more efficiently. With more data, management can maintain and deploy vehicles based on their performance and faults, rather than a one-size-fits-all approach. With increased access to vehicle and driver data, fleet managers will have a better understanding of fuel expenditures, idle time, accidents, compliance violations, and other costs associated with fleet management.