Current Valuation of the Connected Asset Economy

Economy of Things Market Size Growth Projected to Surge Past One Hundred Billion Dollars by 2030

Is your business struggling to unlock value from the growing web of connected devices? Economy of Things market size growth works by assigning direct monetary value to machine-to-machine data exchanges, allowing you to monetize underutilized assets. This expansion benefits you by creating new, automated revenue streams without requiring manual intervention. You can use this growth simply by integrating a digital wallet into your IoT ecosystem to start transacting immediately.

The current valuation of the connected asset economy directly informs the scale of Economy of Things (EoT) market size growth, as each newly monetized asset—from industrial machinery to fleet vehicles—adds measurable economic output to the interconnected ecosystem. This valuation now represents the aggregate revenue generated by asset-level data transactions, which in turn drives the expansion of the EoT market itself. How is the current valuation of the connected asset economy calculated for growth? It is derived from the total transactional value of data streams generated by connected assets, with market size growth reflecting the rate at which these assets shift from static inventories to revenue-generating nodes.

Global revenue benchmarks for the device-driven exchange ecosystem

Global revenue benchmarks for the device-driven exchange ecosystem now anchor the Economy of Things market size growth, with transactions between smart machines setting new value baselines. Current data shows annual device-initiated exchange revenue exceeding $2.8 billion, a figure that doubles when factoring in direct equipment-to-equipment payments. Device-driven exchange benchmarks are calibrated by average revenue per connected asset, which ranges from $12 to $45 monthly depending on data throughput. These benchmarks shift rapidly as autonomous devices negotiate their own resource trades without human intervention.

Average revenue per connected device stands at $28 per month from machine-to-machine exchanges
Top-tier benchmarks show $450+ annually from each industrial sensor participating in direct asset swaps
Device-originated transaction volumes now represent 34% of all Economy of Things revenue benchmarks
Consumer device exchanges generate lower benchmarks at $8–$15 per device per year

Year-over-year expansion rates across major industrial sectors

Year-over-year expansion rates across major industrial sectors reveal that industrial manufacturing leads in connective asset growth, with a consistent 28–32% annual increase in sensor-integrated equipment. Logistics and warehousing follow at 22–26% annually, driven by autonomous fleet tracking. Energy infrastructure shows a steadier 15–18% expansion, while healthcare equipment lags at 10–12% due to slower integration cycles. These rates directly correlate to capital deployed on machine-retrofitting projects, not market speculation.

Q: Which industrial sector has the highest year-over-year expansion rate in connected assets? A: Industrial manufacturing, at 28–32% annually, due to rapid sensorization of production lines.

Contribution of tokenized physical assets to total market worth

Tokenized physical assets directly expand the connected asset economy’s total market worth by unlocking previously illiquid value. Instead of keeping real-world items like machinery or real estate frozen in traditional ownership, each token represents a fractional, tradeable stake. This lets users access capital tied up in physical goods and lets others invest in them without buying the whole asset. For the Economy of Things market, this adds a new layer of value that isn’t just from data or services, but from the underlying hardware itself becoming a liquid, programmable part of the digital economy.

Economy of Things market size growth

Tokenized physical assets boost total market worth by turning illiquid hardware into tradeable digital stakes, directly expanding the Economy of Things valuation beyond service revenue alone.

Primary Growth Catalysts Fueling the Machine Marketplace

The hum of dormant assets waking to life is the real catalyst—when idle machinery on a factory floor begins selling its spare processing power to a nearby logistics hub, the Economy of Things market size grows not from statistics, but from every microtransaction between machines. Q: What is the primary growth catalyst here? A: The shift from passive devices to active traders, where each pump or sensor becomes a merchant of its own idle capacity. This peer-to-peer exchange of data, energy, and compute cycles—a crane renting its uptime to a weather station—adds measurable nodes of economic value, expanding the marketplace with every practical, machine-to-machine barter.

Adoption of 5G and low-latency networks for real-time asset transactions

The accelerated adoption of 5G and low-latency networks for real-time asset transactions directly enables machines to negotiate and settle payments mid-operation. This allows an autonomous vehicle to instantly pay a charging station upon connecting, or a drone to authorize a warehouse access fee while hovering. The process follows a clear sequence:

A connected asset broadcasts a transaction request over a low-latency network.
The 5G carrier minimizes transmission delay, ensuring the bid reaches the marketplace in milliseconds.
The response is executed and confirmed before the physical action (e.g., unlocking a charger or opening a bay door) concludes.

This eliminates settlement friction, turning idle wait times into immediate, verifiable exchanges that scale across fleets of devices.

Integration of distributed ledger technology in autonomous resource trading

The integration of distributed ledger technology in autonomous resource trading enables a trustless, immutable record of machine-to-machine transactions, directly accelerating the Economy of Things market size growth by eliminating intermediaries. Smart contracts automatically execute and settle trades for energy, bandwidth, or compute cycles between IoT devices, ensuring programmatic asset verification without manual oversight. This cryptographic proof-of-exchange allows autonomous agents to negotiate and transact with verifiable ownership and payment, reducing friction in real-time resource pools.

Establishes non-repudiable audit trails for every machine-to-machine resource transfer
Enables instant atomic swaps of data for energy tokens between devices
Removes counterparty risk through distributed consensus on resource availability

Economy of Things market size growth

Rise of smart contract frameworks for peer-to-peer device settlements

The rise of smart contract frameworks enables direct, automated settlements between devices without human intervention. Peer-to-peer device settlements streamline micropayments for bandwidth sharing or data relay, reducing transaction costs and latency. Frameworks like Ethereum or Solana allow autonomous devices to negotiate terms and settle instantly based on pre-coded rules. This eliminates middlemen and overhead, making machine-to-machine commerce practical.

Smart contracts enforce service agreements and release funds only upon verified task completion.
They support dynamic pricing, so devices can bid and settle in real-time for resources like storage or compute.
Frameworks handle dispute resolution through immutable logs, cutting down on manual arbitration.

Segment-Wise Performance and Trajectory

The trajectory of the Economy of Things market size growth is directly dictated by segment-wise performance, where high-value, closed-loop verticals drive expansion faster than horizontal platforms. The industrial asset management segment shows the steepest growth curve, as its performance in tracking machinery utilization unlocks immediate cost savings, fueling capital inflow that scales the market. In contrast, the consumer micro-payments segment lags, held back by smaller transaction values that require extreme volume to influence overall market size. The logistics segment performs as the critical bridge, with its real-time route optimization offering a proven trajectory that pulls smaller mobility players into the ecosystem. This performance hierarchy means market size expansion is not uniform; it surges where segment efficiency directly translates to user revenue gains, creating a self-reinforcing loop of adoption and data monetization.

Industrial IoT and manufacturing machinery as leading revenue contributors

Within the Economy of Things, Industrial IoT and manufacturing machinery are the heavy hitters driving revenue growth. These connected assets generate massive value by enabling predictive maintenance, which prevents costly downtime, and by optimizing production schedules in real-time. This direct impact on operational efficiency makes connected industrial machinery a primary revenue engine in the ecosystem. Instead of just tracking data, these machines actively transact with supply chain systems to order parts or adjust energy consumption, creating a constant revenue stream from their operational activity.

Factories use IoT sensors on assembly robots to bill based on precise operational cycles.
CNC machines sell their machining time to different production lines like a service.
Conveyor systems transact with forklifts to prioritize the most urgent payloads.

Automotive and mobility fleets driving transactional volumes

Within the Economy of Things, automotive and mobility fleets drive transactional volumes primarily through high-frequency, low-value payments for energy, tolls, and parking. Each vehicle in a commercial or shared fleet generates numerous micro-transactions per operational hour as it autonomously negotiates and settles access to charging infrastructure and urban zones. This continuous machine-to-machine expenditure amplifies overall network throughput, as fleets require real-time settlement for route optimization and energy replenishment. The sheer velocity of these peer-to-peer payments—executed without human intervention—creates a scalable volume that directly underpins market expansion, with each trip serving as a discrete economic event that aggregates into significant ledger activity.

Automotive and mobility fleets act as high-frequency payment nodes, generating transactional volume through automated micro-payments for infrastructure access and energy, forming the operational backbone of the Economy of Things market size growth.

Energy and utility grids enabling automated capacity exchanges

Energy and utility grids are becoming active trading floors where your solar panels or EV charger can automatically swap capacity with neighbors. This automated capacity exchange removes human delay, letting surplus power flow instantly to where it’s needed. For you, it means lower bills when you sell extra energy and reliable backup when demand spikes. The grids self-balance in real-time, cutting waste and keeping your lights on without you lifting a finger.

Your smart meter auto-negotiates price and dispatches spare kilowatts.
Grid software diverts power from parked EVs to homes during peak hours.
Microgrids settle local capacity trades without central utility approval.

Regional Market Dynamics and Share Distribution

Regional market dynamics shape the Economy of Things market size growth by dictating where value accrues. In high-density urban zones, share distribution is concentrated among providers of localized device-to-device exchanges, as infrastructure costs are lower and transaction volumes higher. Conversely, in sprawling rural regions, the market share is fragmented across multiple, smaller platforms offering aggregated, low-throughput data services. This geographic imbalance means that market size expansion in developed regions relies on deepening existing network penetration, while growth in emerging markets depends primarily on widening the physical footprint of connectivity nodes to capture underserved user bases.

North America’s dominance in early-stage infrastructure deployment

North America’s dominance in early-stage infrastructure deployment acts as the region’s primary accelerant for Economy of Things market size growth. By rapidly installing edge computing nodes alongside dense 5G and LoRaWAN networks, the region creates a practical framework where physical assets instantly transact data. This aggressive groundwork means businesses there circumvent the typical lag between sensor adoption and value realization, directly converting logistics, energy, and manufacturing hardware into active economic participants. The pre-built pipeline of gateways and low-latency relays transforms initial deployments into a scalable proof-of-concept, giving North American operators the first-mover advantage in capturing monetizable device interactions.

Asia-Pacific’s accelerated uptake driven by manufacturing digitization

Economy of Things market size growth

Asia-Pacific’s accelerated uptake within the Economy of Things market is fundamentally driven by manufacturing digitization at scale. Factory floors are converting to real-time asset tracking and automated quality control, directly expanding the transactional economy of machine-to-machine data. This uptake follows a clear sequence: first, retrofitting legacy assembly lines with IoT sensors; second, integrating these feeds into centralized billing and resource allocation platforms; and third, enabling autonomous spare-part procurement. The region’s density of electronics and automotive factories creates an unmatched ROI for these closed-loop data exchanges. Each digitized production node directly adds to the Economy of Things’ revenue pool, as manufacturers pay per data stream or transaction, not per hardware unit.

Retrofit legacy assembly lines with IoT sensors
Integrate sensor feeds into centralized billing platforms
Enable autonomous machine-to-machine procurement

Europe’s regulatory framework supporting certified machine-to-machine commerce

Europe’s regulatory framework for certified machine-to-machine commerce creates a trusted foundation where devices can transact without human oversight. The eIDAS regulation provides legal certainty for automated contracts, allowing smart appliances to order supplies and pay autonomously. This framework ensures interoperable digital identity across borders, so a German sensor can securely sell data to a French logistics system. By standardizing liability and dispute resolution, Europe removes the guesswork from device-to-device payments. For users, this means their smart home or connected car can reliably handle subscriptions or energy trades without constant manual approval, making the Economy of Things feel effortless and secure.

Emerging Use Cases Expanding the Market Frontier

Emerging use cases expanding the market frontier directly drive Economy of Things market size growth by unlocking value in underutilized assets. For instance, smart parking systems where vehicles automatically negotiate and pay for spaces shift static infrastructure into a revenue-generating node. Similarly, peer-to-peer energy trading between household solar arrays and EV chargers creates micro-markets that were previously non-existent. These practical applications extend the market beyond simple device connectivity, converting everyday items into autonomous economic agents. As more assets—from industrial machinery to consumer appliances—participate in real-time, machine-driven transactions, the addressable market multiplies, fueled by the sheer volume of newly monetizable interactions rather than incremental user adoption.

Decentralized data monetization from sensor-equipped environments

In sensor-equipped environments, decentralized data monetization shifts control from centralized aggregators to individual node operators. Sensors in industrial or smart city deployments can autonomously license raw telemetry directly to specialized analytics platforms via smart contracts, creating granular microtransaction markets. This disintermediation reduces latency and costs for immediate data access, directly expanding the Economy of Things market frontier by unlocking value from otherwise idle environmental data. Peer-to-peer sensor data exchanges enable real-time valuation for precision agriculture or predictive maintenance without a middleman. How does this bypass traditional data brokers? By using on-chain identity and usage policies, each sensor issues verifiable credentials for every packet, ensuring provenance while avoiding centralized fee structures. Micropayments for sub-second environmental readings become economically viable, not just feasible.

Autonomous vehicle charging and parking rights auctions

Autonomous vehicle fleets leverage decentralized charging and parking rights auctions within the Economy of Things to dynamically allocate scarce urban slots. Each vehicle bids machine-readable micropayments for a specific time window at a charger or curb space, with smart contracts settling rights upon arrival. This eliminates fixed reservations, allowing real-time price discovery based on battery state and grid load. Vehicles without immediate need cede slots to higher-bidding counterparts, maximizing asset utilization across the network. The auction loop ensures that physical parking and charging infrastructure becomes a tradable digital commodity, scaling market value with each autonomous unit added.

How do autonomous vehicles determine their bid ceiling for parking rights auctions? Bid ceilings are algorithmically computed from the vehicle’s current range, the value of its next revenue-generating trip, and the time-discounted utility of reaching a cheaper off-peak charger.

Supply chain asset leasing via instantaneous smart negotiations

In the Economy of Things, supply chain asset leasing gets a major upgrade through instantaneous smart negotiations. Instead of waiting on emails, your pallet or container negotiates directly with nearby storage or truck space. This works via a clear sequence:

Your tagged asset broadcasts its idle time and location.
It receives live lease offers from available logistics nodes.
An instantaneous smart negotiation finalizes the best rate and duration automatically.

This turn-key process lets you monetize every empty return mile or unused warehouse slot, effectively expanding use cases within the growing Economy of Things market.

Technological Enablers and Infrastructure Investments

The expansion of the Economy of Things market size is directly fueled by targeted infrastructure investments in edge computing and low-power wide-area networks. Without these technological enablers, the real-time data exchange required for micro-transactions between billions of devices remains impossible. Deploying specialized hardware, such as tamper-proof IoT chips and decentralized ledger nodes, creates the foundation for autonomous value exchange. As capital flows into mesh networking and energy-harvesting sensors, the operational cost of connecting assets drops, allowing the market to scale beyond traditional mobile coverage. This practical infrastructure removes latency bottlenecks, enabling devices to instantly negotiate payments for services like smart parking or dynamic energy sharing. Consequently, every robust technology deployment layer directly compounds the total addressable value within the Economy of Things.

Blockchain-based identity and reputation systems for device participants

Blockchain-based identity and reputation systems assign verifiable, immutable digital identities to each device participant within the Economy of Things. These systems enable machines to establish trust autonomously, using decentralized reputation scores derived from past transaction behavior. A device’s rating, stored on-chain, directly determines its access to network resources, such as data sharing or energy trading, without human oversight. Reputation decays over time to penalize inactivity, while positive interactions accumulate, fostering a self-policing ecosystem. This mechanism supports scalable growth by reducing fraud risks and operational overhead, as devices transact based solely on cryptographic proof of reliability.

Artificial intelligence for dynamic pricing and demand forecasting

AI-driven dynamic pricing and demand forecasting directly scales the Economy of Things by enabling autonomous value negotiation between connected devices. These models process real-time sensor data to adjust pricing for shared infrastructure assets—like energy storage or bandwidth slots—based on instantaneous supply-demand imbalances. Predictive algorithms analyze usage patterns and external variables (e.g., weather, grid load) to pre-allocate resources, reducing idle waste. This machine-learning cycle allows machines to transact without human oversight, optimizing asset utilization across distributed IoT networks.

Economy of Things market size growth

Real-time price adjustments for machine-to-machine resource leasing (e.g., edge computing capacity).
Autonomous rebalancing of shared fleet availability based on forecasted demand surges.
Algorithmic segmentation of asset value by usage context (e.g., peak vs. off-pear IoT data relay).

Edge computing reducing latency in high-frequency asset trades

In high-frequency asset trades, milliseconds determine profitability, making sub-millisecond edge processing the critical infrastructure. By executing order validation and risk checks directly at exchange co-location facilities, edge nodes slash round-trip data travel to near-zero. This physical proximity bypasses the unpredictable jitter of centralized cloud hops, which can add fatal delays during volatility spikes. The outcome is deterministic trade execution, where algorithms act on market data before competing signals even reach a core data center.
How does edge computing specifically eliminate latency in high-frequency trades? It collocates compute power at the network edge, directly adjacent to exchange matching engines, so trades execute within microseconds of the data feed—negating the time lost to wide-area network transmission.

Challenges Impacting Adoption and Scalability

The primary challenge stifling adoption is the lack of standardized interoperability between disparate IoT devices and legacy systems, which fragments the Economy of Things market and prevents seamless value exchange at scale. Without unified protocols, integrating new micropayment models into existing infrastructures creates insurmountable friction for users, directly capping market size growth. Furthermore, the unpredictable computational cost of executing microtransactions on distributed ledgers introduces latency and energy inefficiency that undermines the real-time, low-cost premise essential for mass adoption. This technical overhead paradoxically increases operational complexity for early adopters, eroding the very efficiency gains that drive scalability. Until these infrastructure bottlenecks are resolved through practical, hardware-agnostic solutions, the market cannot transition from niche pilot projects to a truly scalable, global ecosystem.

Economy of Things market size growth

Interoperability hurdles across heterogeneous device protocols

A fundamental barrier to scaling the Economy of Things is the prevalence of interoperability hurdles across heterogeneous device protocols. Devices from different manufacturers often employ proprietary communication standards, such as Zigbee, Z-Wave, or MQTT, creating siloed ecosystems where data cannot be exchanged or acted upon seamlessly. This fragmentation forces users to manage multiple, incompatible hubs or gateways, increasing complexity and cost. Without a unified protocol layer, aggregating device data for automated transactions or cross-platform utility markets remains practically impossible, directly capping the network effect and limiting the potential for market size expansion to a fragmented user base.

Security vulnerabilities in autonomous financial decision-making

Autonomous financial decision-making in the Economy of Things introduces direct security vulnerabilities where compromised machine identities authorize high-value transactions without human oversight. An attacker exploiting a smart asset’s wallet could trigger unauthorized micropayments or redirect funds to fraudulent contracts, as the system lacks built-in anomaly detection for non-human behavior. These flaws are amplified when devices use static cryptographic keys or weak consensus mechanisms, allowing replay attacks or double-spending. The primary risk centers on the inability to distinguish legitimate autonomous intent from hijacked control, making each device a potential vector for financial theft.

Unauthorized micropayments from hijacked device wallets
Replay attacks exploiting static cryptographic keys
Inability to detect anomalous non-human behavior patterns
Double-spending via compromised consensus mechanisms

Regulatory ambiguity around asset tokenization and liability frameworks

Regulatory ambiguity around asset tokenization and liability frameworks creates significant friction for scaling the Economy of Things. Unclear token classification, whether an asset-backed token is a security, commodity, or property, prevents enterprises from confidently deploying capital. Without explicit rules on liability when a tokenized asset—like a smart energy grid component—causes real-world harm, insurers and investors hesitate. This uncertainty stalls pilot projects because no one can legally guarantee recourse for a faulty smart-contract execution or a lost private key. Until jurisdictions define fault boundaries for tokenized physical assets, mass adoption remains legally paralyzed.

Q: Does regulatory ambiguity directly affect user asset safety or just corporate compliance?
It directly affects you—if a tokenized machine fails, unclear liability may leave you with an unrecoverable loss, as no framework yet mandates who bears the cost: the token issuer, the smart contract developer, or the asset operator.

Competitive Landscape and Strategic Moves

The competitive landscape is fragmenting as legacy IoT platform vendors and telecom incumbents race to capture the Economy of Things market size growth by acquiring niche micropayment and smart-contract startups. One company’s strategic move to embed tokenized transactions directly into device firmware directly expands its serviceable market into machine-to-machine commerce, a segment that was previously untradeable.

This directly converts hardware scarcity into a variable revenue stream, forcing competitors to either open their protocols or lose access to the new transactional data layer that scales market volume.

By doing so, it redefines its competitive moat from connectivity pricing to ownership of the settlement rails, thereby linking every unit sold to future transaction fees. This shift pressures incumbents to either build parallel payment stacks or partner with specialized clearinghouses to maintain their share of the expanding transactional market.

Established telecom and cloud providers entering the device economy

Established telecom and cloud providers are moving into the device economy to capture more value from the growing Economy of Things. By bundling connectivity with device management and data processing, they offer users simpler, unified subscriptions instead of separate hardware and service costs. This shift lets you rely on a single provider for everything from smart sensors to cloud storage, reducing setup friction. Their expertise in scaling infrastructure means devices get reliable, low-latency support without you needing to negotiate multiple contracts.

You get integrated billing for devices, data plans, and cloud services from one source.
They pre-configure and certify hardware to work seamlessly with their network, cutting your onboarding time.
Their built-in device management portals let you monitor usage, push updates, and troubleshoot remotely without extra tools.

Startup innovations in micropayment channels for machine transactions

Startups are pioneering microtransaction-specific routing protocols that minimize per-transaction fees, making machine-to-machine payments viable for sub-cent costs. For example, one firm uses state-channel aggregation to batch thousands of sensor requests into a single settlement, reducing overhead by over 90%. This granular fee compression unlocks automated resource trading between low-value devices, from EV charging slots to cloud bandwidth slices. How do these innovations handle transaction failures? Startups deploy redundant payment paths and micro-escrow contracts, ensuring a failed micropayment for a data snippet doesn’t halt the entire machine workflow.

Partnerships merging hardware OEMs with decentralized finance platforms

These partnerships directly accelerate market expansion by integrating tokenized incentives into device ownership. Hardware OEMs embed wallets, enabling machines to earn or spend crypto automatically. Machine-pegged liquidity pools emerge, where device usage directly fuels DeFi yields. A clear sequence follows:

OEMs ship devices with pre-installed DeFi protocols for autonomous payments.
Smart contracts trigger microtransactions for data or energy sharing between appliances.
Vending machines and sensors become yield-bearing assets via pooled user lending.

This co-branded hardware effectively turns every sold unit into a node on an open financial mesh. The resultant asset liquidity directly boosts the total addressable device count in the Economy of Things.

Projected Market Size Milestones Through the Next Decade

The Economy of Things market size growth is projected to cross the critical milestone of USD 1 trillion in total value by 2028, driven by autonomous device-to-device transactions. By 2032, the market is expected to exceed USD 3.2 trillion, with connected asset monetization becoming a standard household utility. The inflection point arrives around 2030, when machine-to-machine micropayments will account for over 40% of all digital commerce volume. For users, this means every smart appliance, vehicle, or sensor they own will directly generate and spend digital currency without human intervention, fundamentally shifting personal finance from active management to passive, automated value exchange.

Short-term growth forecasts for the next three years

Over the next three years, the Economy of Things market is projected to achieve a compound annual growth rate exceeding 28%, driven by the monetization of connected device data. By the end of year one, market size is forecast to reach $18B, accelerating to $28B by year two as enterprise adoption scales. The third year will see a surge past $40B, with smart asset valuation models becoming a primary revenue driver. This trajectory reflects direct user value: businesses can expect a 15–20% increase in operational efficiency from integrated data exchanges, while consumer devices will contribute transactional value at a 3:1 ratio to subscription fees by year three.

Year	Forecast Market Size	Primary Growth Driver
Year 1	$18B	First-wave device data monetization
Year 2	$28B	Enterprise integration rollouts
Year 3	$40B+	Smart asset valuation models

Mid-term inflection point driven by mass device onboarding

Within the projected market size milestones, a mid-term inflection point emerges from mass device onboarding. As billions of sensors, vehicles, and industrial machines connect to Gavin Whitechurch decentralized value networks, the sheer volume of new transactional nodes creates a sudden acceleration in economic activity. This onboarding phase shifts the market from theoretical capacity to tangible, high-frequency microtransactions between machines. Users experience this as a critical threshold where hardware proliferation directly translates into measurable value exchange, fundamentally altering growth velocity beyond linear adoption models.

Long-term valuation scenarios under full autonomous commerce maturity

Once we hit full autonomous commerce maturity, long-term valuation scenarios for the Economy of Things get wild—think of machines trading value without human input. In this phase, we’re looking at sheer network scale, where every machine becomes a micro-economy. A key scenario is frictionless asset liquidity, where idle devices monetize themselves. A typical sequence to imagine:

Sensors auto-negotiate compute rights with nearby servers.
Machines settle payments instantly via crypto or tokenized credits.
Entire fleets rebalance value autonomously, driving valuations into the trillions.

Your phone or car could literally be earning for you while you sleep.

Current Valuation of the Connected Asset Economy