IoT devices are expected to reach 20.8 billion in number by 2020, and most of the data they produce is best accessed while users are mobile.
There are a number of reasons why Smart Chatbots and IoT fit together so naturally:
– Smart Chatbots understand natural language. If you want to create a triggered rule for an IoT smart device to activate an action, such as “turn off the lights when there are no household cell phones in the house”, then all you have to do is request it in everyday language, even with the usual slang, typos, and synonyms. AI Natural Language Processing algorithms will unpack the intent and pass instructions to IoT gateway for processing. And as the AI learns, it becomes increasingly powerful.
– Smart Chatbots offer a de-parameterised interface. You will never need to specify all parameters systematically and in one go. If you forget to specify ‘seconds’ or ‘minutes’ when you set your log updates for your wearable health band or smartshoe, the system will either make an assumption – or just ask you.
– You don’t have to learn how different IoT apps work. Not only can you query IoT networks of devices using everyday language, you don’t have to remember any command structure, interface sequence, or even remember all the info you need to perform the intent. Using a Chatbot means you don’t need to download separate apps either because these are immediately and centrally accessible through existing chat clients.
– Smart Chatbots can refine IoT user requests for subsequent interactions and control. If your connected car sends you an alert that it’s low on oil, you can directly respond with “what type of oil?” or even “I’m in a rush, is it still safe to drive?” This reduces information abstraction problems seen in conventional interface designs. Following Elon Musk’s (recently announced) iWatch plans, why not send your Tesla off for a service at a convenient time by responding with a respective Chatbot message? Other examples might include domestic matters such as smart metering, when a user is alerted about their monthly consumption and needs to ask questions about their individual device consumption or control smart devices. Or one might ask, “I’m working from home on Monday so keep the heating on”. Similarly, in smart retail, questions such as “Can you tell me whether the red trousers I tried on earlier are ethically made, and if so, can you deliver them” would seem a natural use of Smart Chatbots informed by IoT information.
From a developer’s perspective, there are significant advantages to creating Smart Chatbots over conventional smartphone apps for an IoT interface: Smart Chatbots don’t require separate native apps for different mobile platforms and versions. SaaS Chatbots run through any messaging interface with minimum integration.
This also means:
1. Smart Chatbots don’t require specialist developers for each native mobile smartphone platform.
2. Smart Chatbots don’t require the overhead of app updates nor maintenance of older versions of the app at the back-end, across different OS versions and for each mobile platform.
The potential for IoT is eye-opening, especially when you consider that the same SaaS Chatbot stack will operate on any messaging platform, whether mobile, in-app, or via web chat. The real power however, lies in the sheer versatility of Smart Chatbots and in the pleasant and natural experience enjoyed by the end-user.
At action.ai we’ve been exploring the use of Smart Chatbots. This is a more recent technology trend that resonates extremely powerfully in the current IoT field (not to be confused with rules-based Chatbots, which are a distinct step backwards). With Facebook Messenger now reaching 900 Million Active Users per Month, and 2 Billion users on messenger platforms worldwide, we believe Smart Chatbots provide an effective and highly innovative IoT interface solution.