The first generation of IoT solutions often solved a single problem, like smart meters for billing. Although described as IoT devices, they were limited and expensive by today’s standards. For example, most didn’t connect to the internet, used costly private networking technology as public LPWAs didn’t exist, and served as one component of a proprietary solution unable to share data.
IoT 2.0 will be different.
Yes, IoT solutions will solve significant problems like billing, but these devices will also collect and share vast amounts of data with other back-office systems and the internet at large. Think Big Data and AI.
For connectivity, they will rely primarily on global cellular standards LTE-M and NB-IoT. The convenience of global LPWA connectivity with predictable costs, lifecycles, and quality of service will be too good of a fit.
Another difference is scale. As costs and benefits become better understood, adoption will take off. Take smart metering in Australia. Experts predict Australia will see the roll-out of ten million smart water meters in the next five years. These smart meters will use NB-IoT for connectivity and Lightweight M2M for device management.
Why? The massive economies of scale behind these global standards allow the market to create smart meters that cost only a fraction of what lesser solutions cost a decade ago.
Finally, devices will connect to public clouds, like AWS, Azure, and Google, to report data. As the first generation of genuinely internet-connected objects and IoT infrastructure at a massive scale, these solutions will have different requirements.
Massive, data-centric, with lifespans measured in decades and connected to the internet, IoT 2.0 requires security, the ability to share data, and the knowledge the solution can support business objectives for a decade-plus.
Device Management is Foundational
All IoT solutions benefit from device management capabilities. These benefits will only become more apparent as adoption and our ability to measure IoT’s actual operational costs grow. Here is a partial list:
- Zero-touch commissioning – How do you securely install your application and security credentials on not just one but many devices, anywhere in the world, with just a few clicks of a mouse?
- Firmware updates (FOTA) – How do you deliver critical security updates to remote devices? Are you sure your FOTA mechanism is secure itself, or have you created additional vulnerabilities? Does it minimize the costly energy, computing, and network resources necessary to execute the upgrade?
- Diagnostics – Can you identify atypical behavior? Would you know if a hack occurred? What about measuring energy consumption on battery-operated devices?
- Connectivity – Use-case should decide connectivity type. Robust device management capabilities insulate developers from network complexities allowing the device to connect to the cloud securely.
- Data reporting – Electricity meters in Europe report most data fields every fifteen minutes. Doing this as efficiently as possible limits network traffic, cloud-resource utilization, and associated costs.
- Zero-Trust Security – True internet devices and infrastructure require internet-grade security. Remember, not only are these remote, vulnerable, constrained devices working on public networks, but they will operate and produce the products and services we need like food, electricity, and healthcare.
- Disaster Recovery – Hope for the best, plan for the worse. We will need a way to remotely isolate, lock, wipe and recover devices in urgent cases where disaster has struck.
These services ensure solution quality controlling operational costs by minimizing human intervention.
What is your Strategy?
If you agree IoT needs the above device management services, the question becomes, what is the most economically rational way to accomplish this?
Forget about a failed proof-of-concept. How would you like to be the company that has a failed IoT strategy? By failed, I mean lower-quality with higher operational costs.
Organizations must operate these solutions for decades with the understanding vendors will come and go, and technologies will continue to evolve. Also, with the understanding, the developers building the solution might not be there tomorrow.
IoT development strategy comes down to risk mitigation, quality assurance, time-to-market, buy versus build, proprietary versus standards, and hidden costs made all the more complicated by lack of experience and market nascency.
IoT Strategy Made Easy
Nobody builds their cloud or web server. They build applications on top of them. IoT development will eventually follow the same model.
Historically IoT solutions were proprietary efforts. From IoT devices to the front-end collecting the data, developers build everything for one specific purpose. Creating single-task IoT silos is costly, time-consuming, and limits IoT Big Data and AI opportunities.
What if, from data to device to cloud, everyone used the same open, standardized bricks to build any IoT object faster than ever? If instead of developing the whole IoT solution each time, developers could focus just on solution functionality.
If any device, built anywhere, could be managed by any device management server and easily share data with anyone?
These ideas are the vision behind Lightweight M2M device management. Increase solution focus. Reduce the costs of building and managing these devices. Assure interoperability. Provide a single interface for managing all IoT devices and sharing data.
Let developers, organizations, and ecosystems increase the focus on value creation.
Our world is digitizing.
British mathematician Clive Humby said, “Data is the new oil”.
Like the Gutenberg press or the Industrial Revolution, IoT is historic. IoT will become the world’s eyes, ears, and fingers, changing the costs of collecting and acting upon data.
Successful organizations will seize this opportunity. Lesser organizations will be relegated to history.