From the Internet to the Economy of Things

January 09, 2024 - 9 min read

Outlining the next technological leap forward as the IoT stack begins to implement AI and machine-to-machine interfacing, complemented by interoperable monetary layers recorded on blockchains.

From the Internet to the Economy of Things

Introduction

Smart contract platforms are powerful, yet disjointed environments when it comes to security guarantees and the digital assets of their native blockchain ledgers. The problem is trying to guarantee security and a seamless user experience when they need to operate with one another.

The consensus me c hanisms of different networks offer advantageous use-cases by their varying degrees of decentralization, scalability, finality, network fees, privacy, and security. That is to say, that there is no universally perfect blockchain, and each one makes difficult tradeoffs according to the needs of their users.

It’s also worth noting that blockchains are also under pressure to become interoperable with one another so that users, developers, and businesses themselves do not become trapped within siloed, walled garden ecosystems. This is exacerbated by the fact that Web3 is an emerging industry without any real clear winners or losers in the industry.

New participants need to weigh the costs and benefits of joining a network in terms of network effects, and if they might devote their time, capital, and energy towards a network which might become irrelevant over time if the technology can’t interoperate smoothly with other protocols. Thus, interoperability is of paramount importance.

Automated devices will also need the ability to transact with one another, so they’ll be needing smart contract wallets and some assets to trade with as well. This is where Oracles come into play as decentralized validators that can trustlessly provide these services in cases where all the parties involved in a transaction are governed in some form or another by AI. This is the transition to the Economy of Things (EoT) that we will get to later, but let’s recap a bit first for some context.

The Internet of Things

Of course, the Internet of Things (IoT) paradigm revolves around the interconnection of uniquely identifiable devices or “things” by leveraging their Internet or Bluetooth connectivity. IoT enables these devices to collect, transmit, and exchange data with each other almost entirely without human intervention. These “things” range from simple sensors to complex machinery, embedded with sensors, actuators, and communication modules.

As IoT continues to advance, it will inevitably shape the way we live and work in the modern world, and ultimately become integral with smart city infrastructure. It’s already widely used in industries like healthcare, agriculture, transportation, smart homes, and industrial automation, just to name a few. The data generated by these devices are analyzed to gain insights and optimize decision-making processes with minimal human intervention.

Sensor Integration and Communication Protocols

Perhaps the most obvious technological advantage of IoT devices is that they’re equipped with sensors that gather data from their surroundings. These range from simple temperature sensors to advanced ones like accelerometers or gyroscopes, depending on the device’s purpose. This would help devices recognize when others are nearby, or motivate them to shift positions in relation to others.

In precision agriculture, IoT devices are equipped with soil moisture sensors, weather stations, and drones. Deployed in the field, these sensors collect real-time data on soil conditions, weather patterns, and crop health. Armed with this kind of granular data, farmers are better able to optimize irrigation schedules, choose appropriate fertilizers, and detect potential diseases early on, increasing their crop yields and the efficient use of resources.

Additionally, IoT devices exchange data with each other using a variety of clever intercommunication protocols. Most commonly found are protocols like MQTT (Message Queuing Telemetry Transport), CoAP (Constrained Application Protocol), and HTTP/HTTPS. These have proven time and again that they can secure the efficient exchange of data between devices.

In the automotive sector, self-driving cars use IoT to communicate with each other and in some cases, the infrastructure itself. Vehicles equipped with communication modules use protocols like V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure) to share information about road conditions, traffic anomalies, speed traps, and potential hazards. This ultimately enhances safety conditions and will make the experience on roads far less stressful.

Edge Computing and Security Measures

To alleviate the burden on centralized cloud servers and improve performance, IoT systems utilize edge computing. This involves processing data closer to the source (at the edge of the network) rather than relying solely on remote data servers, accelerating real-time processing and reducing latency when it comes to the user experience. Effectively this means that devices are able to respond to their surroundings without much of a time lag.

In the energy sector, smart grids leverage edge computing for the processing of data in real-time. IoT devices embedded in power distribution systems collect data on energy consumption, grid stability, and track equipment health. Edge computing allows for the rapid analysis of this data, enabling quick responses to fluctuations in grid demand, power outages, or other disturbances without relying on centralized servers or in many cases, without relying on human intervention at all.

As IoT devices collect and transmit sensitive data, robust security measures are absolutely critical. This includes encryption of data during transmission, secure authentication mechanisms, and regular software updates to patch vulnerabilities. The amount of effort required to keep things up and running are rather significant, to say the least.

Take healthcare wearables for instance, like smartwatches and fitness trackers. These devices collect sensitive health data and “know” users’ locations and daily schedules. Consequently, these devices use encryption protocols during data transmission to ensure the privacy of each user. Additionally, 2FA and other secure authentication mechanisms are useful in preventing unauthorized access to sensitive health records, maintaining each individual’s privacy and when it comes to their identifiable data.

Interoperability, Data Analytics & Machine Learning

Interoperability is one of the most pressing issues when it comes to digital assets and the sophisticated automation involved with IoT devices. After all, if your devices are incompatible with those around you, they aren’t very useful! Therefore, ensuring that IoT devices from different manufacturers can communicate seamlessly is paramount. Standards and protocols like IoTivity and OCF (Open Connectivity Foundation) aim to address this issue, fostering interoperability amongst a diverse array of hardware devices and the quirks of their software.

It should come as no surprise that tech giants like Apple, Google, and Amazon are well-known for their development of smart home ecosystems. However, they are walled gardens in the sense that they don’t use an industry standard software, meaning users will likely need to choose only one and then stick with it. As for standardized protocols like Zigbee or Z-Wave are at the forefront of helping these devices work seamlessly.

Interoperability is really the key to allowing users to create integrated smart home setups, yet the companies themselves may have incentives for creating walled gardens when it comes to their tech. It will be interesting to see if a more useful yet interoperable technology is adopted over a single ecosystem which clearly dominates the market.

Fascinatingly, IoT devices generate vast amounts of data which can subsequently be analyzed to extract actionable insights. Machine learning algorithms are employed to make predictions, and optimize the efficiency of different processes. They just can’t transact with each other using digital wallets, yet.

In manufacturing, IoT sensors collect and report data on the performance and health of both equipment and materials. Machine learning algorithms can then analyze this data to set maintenance schedules so that equipment is replaced on schedule and long before failure can occur, reducing downtime and preventing costly breakdowns via these proactive measures.

General Electric’s Predix Platform stands out as a leader in implementing predictive maintenance systems in their industrial equipment. Utilizing edge-compute processing, the platform assures end-to-end data and user access control and compliance as it facilitates data transfers from equipment sensors to HMI/SCADA interfaces, increasing situational awareness amongst the hardware and software powering their IoT infrastructure.

What is the Economy of Things?

The Economy of Things (EoT) is a combination of AI, DeFi, and IoT, incorporating and augmenting the IoT with digital assets and smart contracts. It goes beyond simply interconnected IoT devices to one where the devices are themselves capable of real-time discovery, operations, indexing, and autonomous transactions. EoT is the next generation of the Internet of Things, when it comes down to it.

EoT devices are not only able to send and receive information—they can transact too. For example, an EV could pay for its own electricity at a recharging station, or a refrigerator might replenish its own inventory when certain items are running low. Samsung, GE, and LG all offer smart refrigerators which connect with other devices; users can even remotely monitor their fridge from their phones and receive alerts for replacing things like water filters, or issue warnings when someone forgot to close the fridge door!

Data availability is really what drives EoT. At its core, EoT requires that users delegate permissioned consent for their IoT devices to automate tasks. Data owners, whether consumers or enterprises, provide the essential usage insights that IoT devices collect prior to their monetization via EoT integrations like smart contracts transacting with digital assets.

Data providers and device owners should therefore be incentivized for their value-add, which ultimately drives the inherent value for EoT. This is where decentralized identifiers (DIDs) come into play as they anchor users to specific wallets and allow for direct payments and other automated monetization use cases. Ideally, user devices can provide the maximum amount of useful and actionable data while also cryptographically protecting individual identities.

Hyperconnected, Hyper-Liquid Automation with EoT

The widespread adoption of EoT requires a quantum-secure IoT network (sensors, edge devices, and cloud systems) grounded in skepticism that requires verification as opposed to trust. Tech enterprises can extend and secure their data and AI capabilities to the edge of their networks, support real-time discovery, and monetize fully-compliant EoT use cases.

The key challenges for an autonomous EoT characterized by machine-to-machine transactions are managing security risks, reducing overhead costs, and establishing industry standards that are interoperable and composable with each other. This is true for both IoT sensors and perhaps even more so when it comes to blockchain ecosystem fragmentation.

In fact, a European Telco provider called Vodafone is leading the way when it comes to real-world EoT implementations with its Digital Asset Broker platform. By combining unique SIM cards in each device, digital IDs, and smart contracts running on distributed ledgers, Vodafone is creating a seamless experience for users and their devices. For example, EVs outfitted with this technology offer zero-touch charging, pay-per-use financing, logistics and cold chain management, and other automated reporting functions in compliance with local laws.

After all the goal of Web3 and now EoT, is to be interconnected, interoperable, and composable in relation to other publicly-available ecosystems. To be trapped in a walled garden is unacceptable, it is incompatible with most peoples’ vision of the future. We’re dreaming of a future in which our lives are automated, and we need not worry whether or not our devices or wallets will be compatible with surrounding devices as we go about our days.

About Supra

Supra is at the forefront of researching and implementing decentralized Web3 services which optimize for scalability, security, and fast finality when it comes to settling transactions on-chain. Our developer toolkit consists of a growing library of comprehensive guides and technical whitepapers, and serves as the foundation for builders to understand and implement these tools.

You’re invited to join Supra’s epic journey to make digital assets more secure and interoperable, be a part of our vibrant community, and be the first to enjoy the stream of innovations pouring forth from Dr. Kate and Supra’s research team.