**10. Intelligent wheelchair sensors**

In order to apply features measuring of wheelchair, specific hardware circuits along with a software-based monitoring infrastructure are needed to be prepared and integrated in the system. Features can be read from various integrated sensors, and large origin of features is also the system's behaviour. For obstacles avoiding, intelligent wheelchairs need sensors to perceive their surroundings. Many sensors are used by intelligent wheelchairs as explained below:


In this chapter, MEMS sensors, which are magnetometer, accelerometer, and gyroscope, are used. MEMS sensors have many applications in measuring either acceleration or angular velocity about one or several axes as an input to control a system. Some details of accelerometer, gyroscope, and magnetometer sensors are presented below:

### **10.1 MEMS accelerometer in intelligent wheelchair**

The MEMS accelerometer is a highly sensitive sensor and capable of detecting the tilt. This sensor changes the direction of the wheelchair depending on tilt. For example, if the tilt is to the right side, then the wheelchair moves in the right direction, and if the tilt is to the left side, then the wheel moves in the left direction. The wheelchair movement can be controlled in forward, reverse, left, and right direction

**101**

*Embedded Devices Security Based on ICMetric Technology*

**10.2 MEMS gyroscope in intelligent wheelchair**

feedback through smartphone applications.

**10.3 MEMS magnetometer in intelligent wheelchair**

measures the magnetic fields based on Hall effect.

device identification.

in the following steps:

Step 7: Training phase. Step 8: Testing phase. Step 9: Results.

**11. The ICMetric security system**

sensors that are provided in the new system.

Algorithm (3.1): The Implement ICMetric

Output: Normal behaviour or abnormal behaviour. Step 1: Establishing parameters for simulation. Step 2: Generating mobility and traffic model. Step 3: Extracting features from trace file. Step 4: Pre-processing of the extracting features.

Input: Behaviour features that extracted from trace file of ns-2.

Step 5: Integrating of ICMetric number generated by MEMS sensors.

with obstacle detection using ultrasonic sensor. This wheelchair automatically senses

The MEMS gyroscope sensor provides an angular velocity of the wheelchair's wheel as compared to translating the acceleration values to rotation angles for calculating heel rotations. Angular velocities are used directly to estimate linear speeds and distances travelled, which allow us to provide wheelchair users with real-time

Intelligent wheelchairs used MEMS magnetometer sensors for measuring and detecting magnetic fields. Hall effect, magneto-resistive effect, and fluxgate effect are the most popular principles in magnetometer sensors. Magnetometer sensor

ICMetric technology presented here uses bias readings that have been generated from sensor devices. These readings are used to apply ICMetric basis numbers that were utilised as identification for device. Sensor-based identification field has proved that the use of sensory data is possible and that it is feasible to provide

Current defensive mechanisms are not enough for preventing the internal attacks in device, since they require ICMetric security system as protection system to increase their security. ICMetric technology depends on measureable features, which have been achieved from the properties of a particular embedded system. Features are generated in the particular system that represents a unique feature for that system. The focus is on utilising a magnetometer, gyroscope, and accelerometer

In this chapter, an intelligent wheelchair is required where the bias readings extracted from sensors embedded in intelligent wheelchair are utilised in the ICMetric security system generation. These bias readings were employed to create an ICMetric basis that was used as identifications for device. In this chapter, ICMetric security system based on bias readings is extracted from gyroscope, accelerometer, and magnetometer sensors. The proposed algorithm is summarised

Step 6: Dividing the extracted dataset into three groups which are training set, testing set, and validation set.

the presence of an obstacle in its path and turns its direction of movement.

*DOI: http://dx.doi.org/10.5772/intechopen.89240*

*Service Robotics*

ICMetric technology can improve secure communication between devices, reduce fraudulent activity, prevent unauthorised access to the systems and devices connected with the wheelchair, implicit detection of tampering of the software or hardware associated with the wheelchair, and prevent the fraudulent cloning or

While many security techniques are now developed, these cannot necessarily defend against unauthorised activity when the security and safety cannot be absolutely assured. The use of ICMetric technology to provide identification represents a new concept of controlling access to devices and is explicitly aimed at providing

The ICMetric security system proposed in this chapter uses bias readings that have been extracted from sensor devices. These readings exploited to create

In this chapter, suitable features can be gotten from the sensors to describe behaviour of intelligent wheelchair such as the gyroscope, magnetometer, and accelerometers. The offset is utilised in the sensor measurement to propose a security system that apply an ICMetric basis number using the sensor bias readings.

In order to apply features measuring of wheelchair, specific hardware circuits along with a software-based monitoring infrastructure are needed to be prepared and integrated in the system. Features can be read from various integrated sensors, and large origin of features is also the system's behaviour. For obstacles avoiding, intelligent wheelchairs need sensors to perceive their surroundings. Many sensors

• Ultrasonic sensors (i.e. sonar) and sonar sensors are very precise when the sound wave emitted by the sensor strikes an object at a right angle or head on.

• Infrared (IR) sensors emit light, rather than sound, and can be fooled by dark

• Laser Range Finders (LRFs) offer a 180°, two-dimensional scan within the plane of the obstacles in the environment. Another option is a 'laser striper', which contains a laser emitter and a charge-coupled device camera. The image of the laser stripe returned by the camera can be used to determine distances to

In this chapter, MEMS sensors, which are magnetometer, accelerometer, and gyroscope, are used. MEMS sensors have many applications in measuring either acceleration or angular velocity about one or several axes as an input to control a system. Some details of accelerometer, gyroscope, and magnetometer sensors are

The MEMS accelerometer is a highly sensitive sensor and capable of detecting the tilt. This sensor changes the direction of the wheelchair depending on tilt. For example, if the tilt is to the right side, then the wheelchair moves in the right direction, and if the tilt is to the left side, then the wheel moves in the left direction. The wheelchair movement can be controlled in forward, reverse, left, and right direction

or light absorbent material rather than sound absorbent material.

obstacles and drop-offs based on breaks in the stripe.

**10.1 MEMS accelerometer in intelligent wheelchair**

ICMetric basis numbers that were working as identification for device.

imitation of the electronics associated with the wheelchair.

protection against attacks and improving security.

are used by intelligent wheelchairs as explained below:

**10. Intelligent wheelchair sensors**

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presented below:

with obstacle detection using ultrasonic sensor. This wheelchair automatically senses the presence of an obstacle in its path and turns its direction of movement.
