TECHNOLOGY ADVANCEMENTS
There is always the possibility of having “bad data” due to a breakdown in quality somewhere in the system.
The solution has two parts: The first is to define and continuously calculate and monitor data quality metrics that can provide early warning of data quality problems. For example, consider an indicator that shows a rain gauge that is consistently not showing rainfall despite rainfall appearing on nearby stations or gridded datasets. The second part is to put in place an aggressive preventive maintenance and inspection protocol that can target issues before they arise.
Conquering scalability
There is a huge fundamental difference between IoT as a hobby and developing IoT products for mass production. Although early-stage concepts in commercial applications are typically tested on hobbyist platforms such as Raspberry Pi or Arduino (for ease of development and the relatively low cost of obtaining a working prototype), these boards usually consume a lot of power and do not stand up well to challenging environments. The next step up is a ruggedized industrial processor-based development kit and, finally, custom-built circuit boards. Costs quickly escalate along this path.
Other scalability challenges arise from the chosen IoT data transmission technology. Topographic and land-cover variability on the farm limit connectivity and conflict with corporations’ requirements of low latency, independent and reliable transmission services for IoT. The throughput of different technologies varies widely, which can sometimes bring back interoperability issues. For example, some technology/frequency bands allow for barely 15 bytes of payload in unidirectional mode while others may allow 100 times faster, bidirectional throughput.
Managing the growth of IoT programs within the enterprise is key. Leadership will likely want to test the value that IoT can deliver, within a fail-fast context, but estimating the total cost of ownership of a system is very difficult before processes for estimating and managing the obstacles are put in place. Estimating the costs of preventive maintenance, dealing with faulty or compromised hardware, diagnosing and remediating communications problems, and gauging the system’s ability to satisfy the equipment’s power requirements in the field are good examples of early uncertainty.
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