IoT applications consider one or more sensors to collect data from the environment. Sensors are a very important part of smart objects. IoT sensors are mostly small in size, have low cost, and consume less power. Various types of sensors are as follows:-

Fig. Generic block diagram of IoT device


Mobile Phone-Based Sensors

Our first smart object is a mobile phone, which plays a very important role in our daily life. Mobile has many types of sensors embedded in them. The smartphone is a very handy and user-friendly device that has communication and data processing features. Applications can be built on smartphone that uses sensor data to produce truthful results. The smartphone contains some sensors are as follows:- 

  1. The accelerometer senses the motion and acceleration of a mobile phone. It measures changes in the velocity of the smartphone in three dimensions. There are many types of mechanical accelerometers, we have a seismic mass in a housing, which is tied to the housing with a spring. The mass takes time to move and is left behind as the housing moves, so the force in the spring can be correlated with acceleration. In a capacitive accelerometer, capacitive plates are used with the same setup. With a change in velocity, the mass pushes the capacitive plates together, thus changing the capacitance. The rate of change of capacitance is then converted into acceleration. 
  2. The gyroscope detects the orientation of the phone very accurately. Orientation is measured using capacitive changes when a seismic mass moves in a particular direction. 
  3. The camera and microphone are very powerful sensors since they capture visual SVT audio information, which is processed to detect various types of contextual information For example, we can presume a user's current environment that he/she is having, E audio data, and technologies such as voice recognition can be exploited. 
  4. The GPS (Global Positioning System) recognizes the location of the phone, which is very essential for contextual information for the smart application. 
  5. The light sensor detects the intensity of ambient light. It can be used for setting u brightness of the screen and other applications in which some action is to be taken depending on the intensity of ambient light. For example, we can control the lights ie a room. 
  6. The proximity sensor uses an infrared (IR) LED, which emits IR rays, These rave bounce back when they strike some object. Based on the difference in time, we can calculate the distance. In this way, the distance to different objects from the phone can be measured. For example, we can use it to determine when the phone is close to the face while talking. 
  7. Many health and fitness applications are used for a person's health continuously tracking using smartphones. They continuously tracking of physical activities, diet, exercise, and lifestyle to determine the fitness level and give suggestions to the user accordingly.


Medical Sensors 

The Internet of Things can be very helpful for healthcare applications. We can use sensors, which can measure and monitor various medical parameters in the human body. This application can be beneficial for monitoring a patient's health when they are not in a hospital or when they are alone. Afterward, they can provide real-time feedback to the doctor, relatives, or the patient. 


There are many wearable sensing devices equipped with medical sensors that are capable of measuring different parameters such as heart rate, pulse, blood pressure, body temperature, respiration rate, and blood glucose levels. These wearables include smartwatches, wristbands, monitoring patches, and smart textiles. For example, a smartwatch includes features such as connectivity with a smartphone, sensors such as an accelerometer, and a heart rate monitor.


Data collected by the medical sensors are combined with contextual information such as physical activity. For example, the heart rate depends on the context. It increases when we exercise. So, we cannot presume an abnormal heart rate. So, for making the correct inference. We need to combine data from different sensors.


Neural Sensors

Neural sensors are used to understand the neural signals in the brain. This is known as neurofeedback. The technology used for reading brain signals is called EEG (Electroencephalography) or a brain-computer interface. The neurons inside the brain communicate electronically and create an electric field, which can be measured from outside in terms of frequencies. Brain waves can be categorized into alpha, beta, gamma, theta, and delta waves depending upon the frequency. We can assume whether the brain is calm or in thought, based on the type of wave. 


Environmental and Chemical Sensors

Environmental sensors are used to sense parameters in the physical environment such as temperature, humidity, pressure, water pollution, and air pollution. Parameters such as temperature and pressure can be measured with a thermometer and barometer. Air quality can be measured with sensors, which sense the presence of gases and other particulate matter in the air. 


Chemical sensors are used to detect chemical and biochemical substances. These sensors contain a recognition element and a transducer. The electronic nose (e-nose) and electronic tongue (e-tongue) are technologies that can be used to sense chemicals on the basis of odor and taste, respectively. 

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