Discussions of IoT often focus on the technology, so let’s start there. IoT consists of devices, which are the “things” that interact with the physical world and communicate with IoT Back-end systems over a network. There are two types of IoT devices: sensors and actuators.
An IoT system will typically be made of many devices – from dozens to millions – talking to a scaleable Back-end system. This Back-end system often runs in the Cloud. In some cases the IoT devices will talk directly to the Back-end systems. In other cases an additional system called an IoT Gateway will be placed between the devices and the Back-end systems. The IoT Gateway will typically talk to multiple local IoT devices, perform communications protocol conversions, perform local processing, and connect to the Back-end systems over a Ethernet, WiFi, or cellular modem link.
IoT devices consist of sensors, actuators, and communications. Sensors, as the name implies, read information from the physical world. Examples would be temperature, humidity, barometric pressure, light, weight, CO2, motion, location, Ph level, chemical concentration for many chemicals, distance, voltage, current, images, etc. There are sensors available for an incredible range of information and many more under development. Think of things like a tiny DNA sequencer or a sensor that can detect the presence of the bacteria or virus associated with various diseases – both of these are under development!
Actuators are able to change something in the physical world. Examples would be a light switch, a remotely operated valve, a remotely controlled door lock, a stepper motor, a 3D printer, or the steering, brakes and throttle for a self driving car.
IoT Device Examples
For an idea of the range of low cost IoT compatible sensors take a look at Spark Fun Electronics, a leading source of IoT device technology for prototyping, development, and hobbyists. The sensor section at https://www.sparkfun.com/categories/23 lists over 200 sensors that can be used with Arduino and similar systems. Note that these are basically development and prototyping units – prices in production quantities will be lower.
Some sensors are familiar – temperature is perhaps the most obvious example. But many are more interesting. Consider, for example, the gas sensors: hydrogen, methane, lpg, alcohol, carbon monoxide; all available at prices of $4.95 – $7.95. Combined one of these with an Arduino Pro Mini available for $9.95, and you can build a targeted chemical sensor for less than $20.00.
What can you do with a $20.00 lpg or carbon monoxide sensor? That is the wrong question. Instead, you should be asking the question “what problems am I facing that could be addressed with a low cost network connected sensor?” The point is that there is an incredible and growing array of inexpensive sensors available. The technology is available – what we need now is the imagination to begin to creatively use ubiquitous sensors, ubiquitous networking, ubiquitous computing, and ubiquitous data.
The application of modern electronics technology to sensors is just beginning to be felt. As in many other areas of IoT, the basic capabilities have been around for years – detecting and measuring the concentration of lpg vapor or carbon monoxide isn’t new. Detecting lpg vapor concentration with a sub $20 networked device that feeds the data directly into a large distributed computing system in a form that is readily manipulated by software is new. And huge!
Lpg and carbon monoxide are just examples. The same technologies are producing sensors for a wide range of chemicals and gasses.
The combination of useful capabilities, low cost, network connection, and integration into complex software applications is a complete revolution. And this revolution is just beginning. What happens to agriculture when we can do a complete soil analysis for each field? What happens if we have nutrient, moisture, light, and temperature information for each ten foot square in a field, updated every 15 minutes over the entire growing season? What happens when we have this information for a 20 year period? What happens when this information is dynamically combined with plant growth monitoring, standard plant growth profiles, weather forecasts and climatic trends?
Going further, what if this data is combined with an active growth management system where application of fertilizer, pesticide, and water is optimized for individual micro-areas within a field? Technology is progressing to the point where we can provide the equivalent of hands-on gardening to commercial fields.
As an example of work going on in this area see the Industrial Internet Consortium Testbed on Precision Crop Management at http://www.iiconsortium.org/precision-crop-management.htm.