Multiple devices of different brands and models, many end-users, tons of data and multiple platforms to manage different devices: How can we deal with it? Integration and collaboration are the keys.
In terms of IoT, nowadays every city has to deal with a vast number of devices. In some cases, they are the same or pretty similar models of the same brand, with a powerful management console; but due to the current diversity, in most of the situations the devices belong to different brands, with each own platform for management and/or analytical purposes. Obviously, it is a kind of nightmare for the technical administrators of those platforms. Even more for the decision-makers when they need to correlate data from sensors using isolated platforms, without any kind of integration among them.
One of the key achievements of the CitiSim project is the unification of all of those different data sources in a single platform. Regardless the brand and model of the physical devices or if it is a commercial or an Open Source platform, the CitiSim framework is aimed not to compete against other solutions, but to integrate them, acting as a unification mechanism to add value to those solutions. For that reason, the modular design of the CitiSim framework allows an easy integration of different assets as they were simple data sources.
So far, CitiSim deployments can measure up to 20 different variables, like those related to environmental conditions (temperature, humidity, ozone, air pollution, wind direction, etc.), Energy (active power, voltage, power factor, amperage, etc.) and people (counting, position, direction, etc.) among others. All of those measures are possible by the integration of devices from manufacturers like Libelium, Sonoff, Circutor and Microsoft, as well as devices provided by Electricity companies like Verbund and the creation of sensors based upon Raspberry Pi, Arduino and Pycom electronics platforms.
In order to grant that connectivity between sensors and platform, CitiSim supports the most common mechanisms and protocols in terms of IoT. A good example is the MQTT adapter provided by CitiSim, useful for connections with remote sensors where a small code footprint is required and/or network bandwidth is a limitation.
With regard to other data sources, due to the modular and connector-based architecture, CitiSim can be integrated with other 3rd parties. In that sense, apart from other Big Data analytics solutions that already use the Kafka adapter, CitiSim is already connected with services like Weather Underground, a weather information service that provides meaningful weather data from around the globe. This kind of integrations clearly add value to data gathered by physical devices.
In terms of future, CitiSim is continually integrating other devices and data sources. In that sense, new adapters are being developed to add other IoT platforms to the CitiSim ecosystem. In the same way, other devices like smart lights (lampposts) and Smart Home related devices like those created by Xiaomi are planned to be integrated. Additionally, a large set of new sensors developed upon Raspberry Pi will increase that list.
With that amount of information provided by a continuous increasing variety of sensors and data sources, the CitiSim ecosystem can provide optimum mechanisms of integration with KPIs suitable to a large number of use cases connected with Smart Cities and many related topics, like air quality, emergencies, smart tourism, energy efficiency, etc.