Concrete tips for the success of your IoT project
When starting an IoT project, it's best to start small and simple, as shown in the previous blog on the subject. It is also important not to limit yourself to a specific technology but to keep an open mind and try things out. The following components are usually included in a so called Proof of Concept but it can vary depending on the challenges of the project.
Often you want to measure something, such as temperature, position or brightness. These types of sensors are relatively simple and inexpensive, but there are also more advanced sensors such as FLIR cameras and rotating LIDAR sensors. The latter sensor is used, for example, in self-driving vehicle projects, but whatever sensor is needed, it must be possible to connect it to some kind of base unit.
A base unit may contain a microprocessor and storage but also built-in sensors and sometimes communication capabilities. However, it is unlikely that a base unit that meets all the requirements of the project will be available on the market, which means that a single base unit, such as Raspberry Pi or Arduino, will have to be chosen. At this stage, there are then parameters such as performance, power consumption, packaging and others to consider. For example, if you want the base unit to be able to detect objects with artificial intelligence, performance should be prioritised over power consumption. Similarly, if the device is exposed to water or dust (IP65), for example, encapsulation should be prioritised over performance.
The data generated by the sensors and processed in the base unit will then be sent off for further storage and analysis. This requires some form of communication with the outside world and there are a variety of technologies to consider in this context.
You can choose from established methods such as Wi-Fi, Bluetooth, GPRS and 3G/4G, but there are also other methods with associated advantages and disadvantages.
Some of these include NB-IoT (Narrowband IoT), LoRaWAN (Long Range Wide Area Network) and SigFox and here you may encounter advantages such as extremely long range and low power consumption but also disadvantages such as limitations in availability and transmission capacity. It is simply a matter of trial and error to evaluate which method best meets the requirements.
Storage and Analysis
A cloud service is preferably chosen for this purpose as it is quick and easy to set up, which is in line with the previously set objectives of the project. Here it is important to choose a provider that enables relatively easy integration with other systems, such as Microsoft Azure, which provides access to services such as IoT Hub, Logic App, SQL Database and Power BI for managing, storing and analysing the data that the sensors emit. In the future, there will also be the option to apply artificial intelligence to a larger amount of data, enabling, for example, predictive maintenance, anomaly detection or other machine learning functions.
Finally, the concept as a whole is evaluated to determine whether the desired value has been created and whether to proceed on a larger scale. Factors to consider include mass production of devices, global communication capabilities, security and privacy. Does this sound interesting? If so, don't hesitate to get in touch.