Such a hub needs to be able to translate different data types or units of measure, such as Fahrenheit to Celsius. It also requires a common data model to make it possible to compare and integrate data from any vendor’s devices, thus making it possible for the system to “understand the data.”
Problem 2: Too much data
In some cases, the total amount of data being collected may be so great that moving it over the network to a central location may not be viable. Consider an individual outside temperature sensor on the warehouse. To serve its various purposes, including maintenance, it transmits temperature, humidity, hardware version, software version, battery level, motion/position changes, etc. The list can go on and on.
This information may be sent every 30 seconds – maybe even every second depending on the criticality – and there are several hundred sensors on the outside of the large warehouse. And this is only one type of perhaps dozens of types of sensors.
What’s needed is an integration solution with the ability to aggregate only the desired data from wherever it resides, normalize it into common data models, and make it accessible as needed for monitoring, reporting, maintenance, and other scenarios. For example, the warehouse solution should be able to pull the outside temperature and humidity readings from only the 50 outer wall sensors in Zone 3 to check the climate balance for Zone 3.
Problem 3: Security
While the IoT peer-to-peer model (i.e. multiple connected devices working together) is essential for the warehouse solution and similar large-scale IoT use cases, this approach introduces an important security issue.
The overall security profile is only as strong as the weakest device that is part of it. If the security on a particular vendor’s outdoor sensors is weak, and a number of the other vendors’ sensors and devices depend on the data from those potentially compromised sensors, the possibility of a critical “indirect” impact is strong. For example, a breached sensor could deliver the wrong outdoor temperature to the system, resulting in a system decision to adjust a zone temperature in a way that ruins the food in that zone.
To solve this problem, the warehouse IoT peer-to-peer model must be implemented in a way that enables the system to double-check a particular sensor’s reading by checking with other physically co-located sensors to confirm that reading. For example, if one outdoor sensor is reading particularly high while its neighboring sensors uniformly read a lower temperature, then the system should not make an immediate decision to adjust the relevant zone temperature. Instead, the system should issue an alert to validate the functionality of that sensor and to check the physical area around the sensor.
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