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Connected, but still not interoperable

Written by Lucas Lira Gomes at


Cisco call it the Internet of Everything (IoE), most players would rather name it the Internet of Things (IoT) and, although less common, you probably heard the term the Industrial Internet too. And if you ever read any post or whitepaper about one of those buzzwords, especially those written by big players in the market (e.g. Cisco, IBM), you probably saw a trend in depicting scenarios where your things (e.g. car, appliances, lighting, HVAC) are interconnected and, somehow, interacting among themselves independently of human interference. Great vision, but how far are we from it?

Right now IoT is composed by a jungle of different solutions. You can probably outline those that seem more promising. In the networking spectrum there is a whole stack solutions, which tries to provide you not only data link layer features but also routing, addressing and some even encryption, those are mainly Zigbee, Z-Wave, Bluetooth and WirelessHart. On the other hand you also have WIFI, raw IEEE 802.15.4, GPRS and all sort of radios operating in sub-gigahertz frequency ranges. Each has an use case of its own. Z-Wave, for instance, is more present in home automation, Bluetooth V4 is usually the right one for wearables, WirelessHart is an adaption of the Highway Addressable Remote Transducer Protocol (HART) protocol for industrial wireless networks and Zigbee is the wild card among them (i.e. thanks to DIGI’s amazing AT programming interface).

Along with that there is also efforts to bring the IP protocol to the constrained devices like those that use IEEE 802.15.4 and its variations. Well, the advantages are many. First there is the seamless exchange of information between devices utilizing any IP-enabled MAC/PHY (e.g. Wi-Fi, Ethernet). Second we cannot forget the battle-tested tooling all those years of IP predominance have provided us (e.g. ping, traceroute, netcat, wireshark, tcpdump). The IPSO Alliance is one of the major advocates in this matter. They have several whitepapers publicising standards like 6LowPan, an IPV6-compatible addressing with better header compression, and RPL, a mesh-enabled routing protocol for low power and lossy networks. The Zigbee Alliance also realised the advantages of IPv6-based wireless mesh networking and created ZigBee IP, and open standard built on top of IEEE 802.15.4 that provides end-to-end IPv6 networking.

On top of IP, on the application level, MQTT and COAP shine. The first is a lightweight PUB-SUB protocol based on TCP. Now you may wonder if MQTT is appropriate for wireless sensor networks. In fact anything TCP based is not by design, but in such cases you can use MQTT-SN, a UDP based variation of MQTT that is especially tailored for low-cost and low-power sensor devices that run over bandwidth-constrained wireless networks. While COAP is a lightweight HTTP compatible protocol, based on UDP, with support for multicasting and service discovery. Both of them are quite popular and you can probably find an implementation for your favourite programming language or IoT platform (e.g. Contiki OS, Arduino). Unfortunately, given a non-IP network, developing a gateway to map your custom protocol in the interface your backend/server uses and vice-versa is a necessary burden.

So, there is certainly no doubt there were major progresses on the connectivity front, but still something is absent in this equation. Connectivity is certainly necessary but IoT is as much about connectivity as the internet is about the web. That vision those big players describe of smart Xs, being X anything, autonomously interacting among themselves is heavily dependent of those devices being able to discover each other and access their functionalities, without being explicitly pre-programmed to do so. You probably saw companies like Smart Things, Ninja Blocks or the former Revolv, bought by Nest, stating that their platforms/hubs supports different vendors or “play well with others”, which is great but has its own limitations.

Up to now, in platforms like the aforementioned, integration of new products occurs in a incremental fashion. So if you want to support Phillip’s Hue or LIFX lamps, you will have to read the documentation of their REST API. Which seems great given REST apis are easy to integrate, but the crude reality of IoT is way less welcoming. In most you cases, you will find yourself with vertically integrated systems that do not permit easy third-party integration. And even if they permitted, the manual process of integrating with new devices and/or platforms have two problems.

First, a great deal of products does not provide public documented APIs for third-parties. And the reason is that, currently, most vendors tend to sell a solution, from hardware to user interface, therefore not caring for those who want to use their products differently from what they envisaged (i.e. makers suffer :/). Consider Plugwise, for instance, they have one of the most complete energy management solutions out there, but without a consistent effor to provide a public API or SDK. You may even find unofficial libraries, made by someone who probably had to sniffer Plugwise’s devices in order to reverse engineer their proprietary protocol. But using those, you would not have any guarantee of future support. Besides that it is common for unofficial libraries not to be feature complete, so good luck if you want to use the most recent capabilities.

Second, manual integration does not scale. Vendors may try to pinpoint the most popular products, to focus their integrations efforts, or form partnerships, but that degree of interoperability will come at the expense of tight vendor integration with specific partners.

To solve those problems, devices need to discover and access each other functionalities, not necessarily directly like M2M scenarios portrait. And for such two things are required. First a data model that could explicitly state what each piece of data is about, so that you do not have to read a manual to realise that a sensor is measuring temperature in Celsius. Ontologies are usually the answer in such cases, but OWL and RDF are not appropriate given the bandwidth limitations. The IPSO Alliance tried to fill this gap with its Smart Objects specification, which describes a reusable data model for IoT. That data model defines a set of data types and structures that can be used by different devices, in order to enable them to interoperate since the semantics is now in the data itself. Still, despite the Smart Objects specification, ontologies have an important role at the users level, as the tooling from semantic web technologies (e.g. SPARQL, OWL, RDF) can provide great value for those interested in composing their own IoT solutions by accessing higher level services.

Although being able to determine the content of the messages sent by sensors is important, no equivalent exists in terms of actuation. And that is key to a large adoption of IoT, especially in the end-consumer market. Right now, businesses can get value by tracking trends and analysing data, but for end-consumers automation is the real killer application. And by automation I mean not only actuation, that translates itself in an event in the physical world, but also remote configuration of these devices. All that provided, without devices being pre-programmed to do so, would be huge. But, unfortunately, no lightweight UPnP exist for the IoT yet.

Pythonic interfaces in Go Generators

iot ioe automation networking

Lucas Lira Gomes

Passionate Hacker, KDE/ArchLinux Zealot, and FOSS Enthusiast. I'm fond of Startups, Big Data, AI, NoSQL, Python, C++/Qt, Git, Cloud, IoT and all that jazz.

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