Introduction & Definition of IoT: Tutorial 1

Question 1

What is a sensor? (Important)

Answer 1

A sensor is a device that is able to detect changes in an environment. A sensor converts some physical phenomenon into an electrical impulse that can then be interpreted to determine a reading.
- It should be sensitive to the phenomenon that it measures
- It should not be sensitive to other physical phenomenon
- It should not modify the measured phenomenon during the measurement process

Question 2

Types of sensors (Important)

Answer 2

• Thermometers,
• Pressure sensors, (Atmospheric Pressure)
• Light sensors,
• Accelerometers,
• Gyroscopes, (Measure & Maintain Orientation, planes, cars)
• Motion sensors,
• Gas sensors
• Proximity Sensor (Detect object without touching it, Self-driving cars)

Question 3

What is an actuators? (Important)

Answer 3

An actuator operates in the reverse direction of a sensor. It takes an electrical input and turns it into physical action. For instance, an electric motor, a hydraulic system, and a pneumatic system are all different type of actuators.

Question 4

Requirements of an IoT Sensor (Important) [HEELLS]

Answer 4

1) Low Power consumption is crucial in certain applications, for example small or portable devices. Here, an autonomous sensor processor paired with a sensing element (“Sensor bot”) is helpful for edge processing, for determining when to transmit to the cloud, thereby cutting down the resource costs of data transmission.

2) Low Latency has significant importance in situations where we need to transmit large volumes of data with minimal delay. For example, in virtual reality (VR) images need to be sent in real time speed in order to keep up with the dynamic motion of the user’s head.

3) High Data Sampling Rates may be required for rapid system activity learning applications, e.g. in predictive maintenance on vibrating machinery, the sensor must sample at a sufficiently high rate in order to capture all the relevant data leading to the equipment failure.

4) Ease of Integration varies widely and OEMs often have very different expectations of how much time and engineering resources they are prepared to invest into interpreting sensor data. To simplify sensor integration into their applications, many companies require increasingly intelligent sensors that provide a certain degree of data processing embedded inside the sensor with a vendor-provided software solution to match. For example, in robotics the OEMs will focus on the motion of the robot itself, preferring not to deal with raw sensor data at all.

5) Edge computing is analogous to the above-mentioned limbic system. Sometimes we require processing performance on the edge, and often this goes hand-in-hand with both the low power and ease of integration prerequisites.

6) Storage
Since the cost of memory in a sensor module is much higher, cloud storage presents a viable alternative to local storage and processing. The issue is that on the one hand, we do not want to transmit copious amounts of unnecessary data, but on the other hand we are constrained by the sensor’s physical storage capacity. Therefore, we must implement on-sensor intelligence and make sure the sensor discards the majority of unnecessary data and prevents flooding its memory capacity.