Connecting Things to sensors has been possible for decades. In the modern Internet, this is often referred to as IoT, short for Internet of Things. Throw an ‘I’ on the front and you have IIoT for Industrial Internet of Things. So, if it has been possible to put sensors on Things for decades, why, you may ask, is there so much fuss in the news about IIoT right now? The answer is bandwidth: cost for network, storage, and computing bandwidth have all gone down and the Internet has become more available, almost anywhere, and certainly at most industrial and many Energy & AG sites.
The IIoT has created an opportunity for putting sensors on Things, almost anything, even a piece of wood, but without context awareness, we humans have to do a lot of mental “if/then/else” work to understand the sensor readings. Below are a few examples to help you understand the massive way that context-aware IIoT can add substantial value.
- Putting a motion sensor on a gate is useful but could be quite annoying if an alert went off every single time a busy gate moved. Adding time of day is helpful but we could make it far more useful by adding relevant context. So, let’s say that the gate is guarded after hours, but authorized users can still gain entry with a pass card. Problem is that, if the guard is on her rounds or otherwise, and not in the guardhouse, invalid entry is possible if the authorized user does not wait until the gate closed before parking.
Now, make it context-aware by putting a $150 gateway in the guardhouse, a $20 motion sensor on the gate, and a $10 Bluetooth sensor on the guard’s utility belt. Let’s also assume that the pieces are connected to Avimesa.Live so that the user can set their own context-aware rules. Here’s what happens next. The first piece of context awareness is time, so we only look for gate movement after hours. Now we add in some perimeter awareness (another context point) by only sending an alert to the guard’s cell phone when she is not in the guardhouse. The system knows she is not in the guardhouse because the perimeter-aware gateway can see the distance of the Bluetooth sensor from itself. The sensors on the gate are also Bluetooth enabled and the gateway sees the gate motion too.
*Flood sensors are used all over the place in industry and they are mainly not aware of their own context. Many of the flood sensors in use don’t even have a microprocessor to handle any type of rules processing. They often just send a signal when water is above a level or is detected at a place that should not have any significant moisture. Other than time of day, we can add a lot of value and save money by adding context awareness of regional weather conditions. Many flood sensors are in remote locations and use LTE, LoRa, or other wide area data networks that have data feeds. The more flood readings, the larger the cost, and it probably really doesn’t make a lot of sense to be constantly sampling water levels on a sunny day in many locations. How about if we add in a regional climate feed so the system only samples the flood sensors once per hour in sunny conditions. With this seemingly simple addition of context-awareness we can save money by only kicking up the sensing rate to once per minute when weather conditions indicate it should be done. This also adds a lot of value to the data collected — flood sensing details in unchanged conditions add relatively useless data to expensive databases, make graphs harder to read, and, of course, generate potentially annoying alerts. It should be noted that reducing the number of notifications and alerts to a user increases their likelihood of responding to an urgent alert.
- Methane sensing is growing in significance. This abundant gas is mainly created by natural processes but there is a steady increase in creation as a byproduct of human activity. Clearly, world governments are starting to put a lot of emphasis on methane levels with a variety of industries. The problem with methane detection is that the gas dissipates quickly and the sensors are relatively expensive.
Context-awareness for methane is more complex because of the geographical largeness and lots of regulations. There are already methane detection companies that use aerial (plane/helicopter/drone/satellite, etc.) to spot plumes or micro seepage and other leaks over a topography. The current methodology used, mainly in oil and gas is to use aerial topography reporting to dispatch personnel to GPS locations in need of service or inspection.
The same aerial methane companies and networks, in existence today, can be used to provide context awareness to methane sensors. Rather than deploy human resources, imagine being able to place solar and methane sensors with connections to context-aware gateways via drones and land robots to specifically pinpoint key methane detection points.
Solar power is essential for IIoT in working yards. The good news is that there are now many reliable low-cost solar units that can usually be customer installed. And for larger installations, there are a variety of professional solar suppliers, installers, and consultants that are largely high quality.
Sharing sensor data is fundamental to providing context. A Fire Department in a rural area can strategically put sensors around their county. Local businesses can use the FD shared sensors as context for their particular business sensors. Putting humidity sensors on acres of wood can be used to pinpoint key protection areas.
There are many new technologies coming to the forefront that are going to fuel the growth of IIoT and the need for context-awareness. Even without revolutionary things like StarLink, there is abundant Internet connectivity becoming available from the wireless providers and the new, low-cost, regional networks being created by LoRaWAN such as Helium. Tying all of these Things together would be difficult without context-awareness.
If you have questions about Avimesa and context awareness, contact us here. We will get back to you asap.