Any new technology involves a certain amount of uncertainty and business risk. In the case of the Internet of Things, however, many of the risks have been exaggerated or misrepresented. While the IoT vision will take years to mature fully, the building blocks to begin this process are already in place. Key hardware and software are either available today or under development; stakeholders need to address security and privacy concerns, and collaborate to implement the open standards that will make the IoT safe, secure, reliable and interoperable, and allow the delivery of secured services as seamlessly as possible (Push Technology).
Cisco is expecting the industry to gross over $19 trillion over the next few years. However, the problem is that these ‘things’ have myths surrounding them, some of which are impacting how organizations develop the apps to support them.
1) IoT and sensors
According to Cisco, “The fundamental problem posed by the Internet of Things is that network power remains very centralized. Even in the era of the cloud, when you access data and services online you’re mostly communicating with a relative few massive datacenters that might not be located particularly close to you. That works when you’re not accessing a ton of data and when latency isn’t a problem, but it doesn’t work in the Internet of Things, where you could be doing something like monitoring traffic at every intersection in a city to more intelligently route cars and avoid gridlock. In that instance, if you had to wait for that chunk of data to be sent to a datacenter hundreds of miles away, processed, and then commands sent back to the streetlights, it would already be too late — the light would have already needed to change.”
Cisco says that the solution is to do more computing closer to the sensors (fog computing) that are gathering the data in the first place, so that the amount of data that needs to be sent to the centralized servers is minimized and the latency is mitigated. Cisco says that this data crunching capability should be put on the router. This, however, is only part of the story. Getting the right data from the right device at the right time is not just about hardware and sensors, instead it is about data intelligence. If you can understand data and only distribute what is important, at the application level, this is more powerful than any amount of hardware you throw at the problem.
This prioritization of data should be done at the application level where there is logic. Combine this with data caching at the network edge and you have a solution that reduces latency.
2) IoT and mobile data
Smartphones certainly play a role in collecting some of this data and providing a user interface for accessing IoT applications, but they’re ill-suited to play a more central role. Consider the example of home automation: It hardly makes sense for critical home-monitoring and security applications, such as those that protect an elderly resident against an accident or illness, to rely upon a smartphone as its decision-making hub. What happens when that person travels and his smartphone goes into airplane mode? Does his home security get interrupted, or home electricity shut down?
Such examples make it clear that the IoT will, with a few exceptions (such as “wearable” technology and bio-monitoring systems) and some automobile-related applications, rely mostly upon dedicated gateways and remote processing solutions—not on smartphones and mobile apps.
Today, without any IoT services, more than 80% of the traffic over LTE networks goes through Wi-Fi access points. What happens when that data increases by 22 times? In addition, cellular networks and communication devices have serious drawbacks in areas such as cost, power consumption, coverage and reliability.
So, will the Internet of Things have a place for smartphones and cellular communications? Absolutely. But in terms of performance, availability, cost, bandwidth, power consumption and other key attributes, the Internet of Things will require a much more diverse and innovative variety of hardware, software and networking solutions.
3) IoT and the volume of data
The IoT is going to produce a lot of data – an avalanche. As a result, some IoT experts believe that we will never be able to keep up with the ever-changing and ever-growing data being generated by the IoT because it’s just not possible to monitor it all. Amongst all the data that is produced by the IoT, not all of it needs to be communicated to end-user apps such as real-time operational intelligence apps. This is because a lot of the chatter generated by devices is useless and does not represent any change in state. The apps are only interested in state changes, e.g. a light being on or off, a valve being open or shut, a traffic lane being open or closed. Rather than bombarding the apps with all of the device updates, apps should only be updated when the state changes.
4) IoT and datacenters
Some argue that the datacenter is where all the magic happens for IoT. The datacenter is absolutely an important factor for the IoT; after all this is where the data will be stored. But the myth here is that the datacenter is where the magic happens. What about the network? After all, IoT is nothing without the Internet actually supporting the distribution of information. So you might be able to store it or analyze it in a datacenter, but if the data cannot get there in the first place, is too slow in getting there or you cannot respond back in real time, there is no IoT.
5) IoT is a future technology
The Internet of Things is simply the logical next step in an evolutionary process. The truth is that the technological building blocks of the IoT—including microcontrollers, microprocessors, environmental and other types of sensors, and short range and long range networking communications—are in wide-spread use today. They have become far more powerful, even as they get smaller and less expensive to produce.
The Internet of Things, as we define it, while evolving the existing technologies further, simply adds one additional capability—a secured service infrastructure—to this technology mix. Such a service infrastructure will support the communication and remote control capabilities that enable a wide variety of Internet-enabled devices to work together (freescale).
6) IoT and current interoperability standards
Everybody involved in the standards-making process knows that one size will not fit all— multiple (and sometimes overlapping) standards are a fact of life when dealing with evolving technology. At the same time, a natural pruning process will encourage stakeholders to standardize and focus on a smaller number of key standards. Standards issues pose a challenge, but these will be resolved as the standards process continues to evolve.
The Internet of Things will eventually include billions of interconnected devices. It will involve manufacturers from around the world and countless product categories. All of these devices must communicate, exchange data and perform closely coordinated tasks—and they must do so without sacrificing security or performance.
This sounds like a recipe for mass confusion. Fortunately, the building blocks to accomplish many of these tasks are already in place. Global standards bodies such as IEEE, International Society of Automation (ISA), the World Wide Web Consortium (W3C), OMA, IETF and IPSO alliance (to name a few) bring together manufacturers, technology vendors, policymakers and other interested stakeholders. As a result, while standards issues pose a short-term challenge for building the Internet of Things, the long-term process for resolving these challenges is already in place.
7) IoT and privacy & security
Security and privacy are major concerns—and addressing these concerns is a top priority. These are legitimate concerns. New technology often carries the potential for misuse and mischief, and it’s vital to address the problem before it hinders personal privacy and security, innovation or economic growth. Manufacturers, standards organizations and policy-makers are already responding on several levels.
At the device level, security researchers are working on methods to protect embedded processors that, if compromised, would halt an attacker’s ability to intercept data or compromise networked systems. At the network level, new security protocols will be necessary to ensure end-to-end encryption and authentication of sensitive data, and since with the Internet of Things the stakes are higher than the Internet, the industry is looking at full system level security and optimization.
8) IoT and limited vendors
Open platforms and standards will create a base for innovation from companies of all types and sizes:
- Open hardware architectures. Open platforms are a proven way for developers and vendors to build innovative hardware with limited budgets and resources.
- Open operating systems and software. The heterogeneous nature of the Internet of Things will require a wide variety of software and applications, from embedded operating systems to Big Data analytics and cross-platform development frameworks. Open software is extremely valuable in this context, since it gives developers and vendors the ability to adopt, extend and customize applications as they see fit—without onerous licensing fees or the risk of vendor lock-in.
- Open standards. As we discussed earlier, open standards and interoperability are vital to building the Internet of Things. An environment where such a wide variety of devices and applications must work together simply cannot function unless it remains free from closed, proprietary standards.
Virtually all of the vendors, developers and manufacturers involved in creating the Internet of Things understand that open platforms will spur innovation and create rich opportunities for competition. Those that don’t understand this may suffer the same fate as those that promoted proprietary networking standards during the Internet era: They were sidelined and marginalized.
The reality of the IoT is that if you want to distribute data from the ‘thing’ across the network in real time over unreliable networks you need intelligent data distribution. To lighten the load on the network by reducing your bandwidth usage, you need to understand your data. By understanding it, you can apply intelligence to only distribute what’s relevant or what has changed. This means you send only small pieces of data across a congested network. The result is IoT apps with accurate, up-to date information, at scale, because you’ll be able to cope with the millions of devices connecting to your back end. You won’t be hit with huge pieces of data at once, shutting down your services.