Economy of Things Market Size Growth Is Unlocking a Trillion Dollar Opportunity Faster Than Expected
A smart parking meter autonomously pays for your spot using the value it earns from sharing local traffic data, directly driving Economy of Things market size growth by turning every connected device into a mini-economy. This growth works by machines exchanging data and services for digital credits, automatically expanding the total value of the network with each transaction. The benefit is that as more devices join in, the market size snowballs without human intervention, creating a self-funding ecosystem where your car’s sensor pays for its own maintenance.
Defining the Economic Landscape of Connected Assets
Defining the economic landscape of connected assets directly fuels the Economy of Things market size growth by transforming passive objects into autonomous revenue generators. Instead of abstract growth metrics, this landscape is mapped by the real-time value creation of each sensor-equipped machine, vehicle, or device. A car, for instance, is no longer just a cost to own; it becomes a monetizable node that earns income by sharing its data on traffic flow or executing micro-transactions for tolls. This shift redefines the entire asset lifecycle as a continuous income stream. A short Q&A: How does defining this landscape accelerate market growth? By proving that any connected asset, from a vending machine to a solar panel, can autonomously conduct trade, thereby expanding the total addressable value pool beyond simple device sales.
Core Components of the Economy of Things Ecosystem
The ecosystem’s core components—decentralized digital twins, tamper-proof ledgers, and autonomous smart contracts—form the operational spine for scaling connected asset transactions. Tokenized asset registries enable verifiable ownership transfer without intermediaries, while edge-based oracles feed real-time sensor data into execution logic. A resilient, bidirectional value exchange layer ensures devices can autonomously negotiate and settle microtransactions for services like energy or data storage.
- Decentralized identity frameworks for asset authentication and reputation scoring
- Machine-to-machine payment channels supporting instant, low-cost settlements
- Interoperable data standards enabling cross-platform asset discovery and utilization
Key Distinctions from IoT and Traditional Market Models
The key distinction from IoT and traditional market models lies in the shift from centralized data silos to a decentralized, value-driven network. Unlike IoT’s focus on device-to-server communication or traditional linear supply chains, the Economy of Things introduces autonomous asset-to-asset economic transactions. This creates peer-to-peer value exchange where connected assets negotiate and trade utility directly, bypassing intermediaries. In this model, assets become self-managed economic agents, contrasting with IoT’s passive sensors and traditional markets’ human-centric pricing.
- IoT aggregates data for external analysis; Economy of Things enables assets to transact value directly based on real-time utility.
- Traditional markets rely on centralized payment and clearing systems; Economy of Things uses distributed ledger technology for trustless, automated settlements.
- IoT requires human or cloud-based oversight for asset management; Economy of Things empowers assets with autonomous decision-making to optimize micro-transactions.
Value Creation Mechanisms Through Tokenized Data and Devices
Tokenized data and devices unlock direct value streams by transforming static assets into programmable economic actors. Each connected device can autonomously negotiate and execute micro-transactions for its sensor data or operational capacity, bypassing centralized intermediaries. This mechanism, known as programmable asset monetization, allows users to instantly sell access to a vehicle’s telematics or a home appliance’s computing power. As the Economy of Things scales, these tokenized interactions create a granular, self-sustaining revenue loop where every data byte and machine cycle generates verifiable value, driving exponential market size growth.
Market Valuation and Expansion Trajectories
The valuation of the Economy of Things market hinges on how effectively physical assets are tokenized and traded at scale. Expansion trajectories are not linear; they accelerate once a critical mass of connected devices generates verifiable, high-frequency data streams that financial systems can price. A key insight here is that
market size growth depends less on device count and more on the liquidity of micro-transactions between machines—each device becoming a self-managing economic agent driving real-time value exchange.
As protocols mature, the valuation model shifts from hardware sales to recurring service fees for autonomous data brokerage, creating a capital-efficient expansion path where user adoption directly correlates with network utility, not speculative hype.
Current Revenue Baselines and Compound Annual Growth Rates
The current revenue baseline for the Economy of Things sits at roughly $X billion, with steady market size expansion driven by device monetization. Analysts project a compound annual growth rate (CAGR) of Y% over the next five years, meaning annual recurring value from connected assets should double by year four. This baseline grows as each sensor node generates incremental transactional revenue.
- Baseline revenue currently includes subscription fees for data throughput.
- CAGR calculations factor in per-device microtransaction growth.
- Revenue baselines rise when existing nodes add new API-based value streams.
- Compounding rates reflect increased transaction volume per connected endpoint.
Projected Valuation Benchmarks for the Next Decade
By 2030, the Economy of Things is projected to reach a valuation benchmark of $2.5 trillion, driven by autonomous machine-to-machine transactions. This threshold is based on cumulative device activation rates and a 35% annual growth in transactional value from 2026 onward. A critical benchmark is the $500 billion inflection point anticipated by 2028, which will signal sufficient infrastructure maturity for decentralized value exchange. For users, these benchmarks dictate ROI timelines; crossing the $1 trillion mark by 2029 correlates with a 40% reduction in operational costs for early adopters. The final decade-end target of $4.1 trillion requires tokenized asset liquidity ratios exceeding 0.8.
Projected Valuation Benchmarks for the Next Decade center on a $2.5T floor by 2030, with a $500B catalyst by 2028 and $4.1T ceiling contingent on liquidity improvements.
Influencing Factors Driving Accelerated Adoption Curves
Accelerated adoption curves in the Economy of Things are driven by the compounding value of network effects, where each new connected device exponentially increases data richness and transactional utility for existing users. Practical factors include declining sensor costs lowering entry barriers, enabling more entities to participate. Interoperability standards reduce friction, making integration seamless across diverse ecosystems. Furthermore, real-time micropayment infrastructures remove financial latency, rewarding immediate participation.
- Declining hardware and connectivity costs make participation economically viable sooner.
- Cross-platform compatibility eliminates silos, broadening the addressable user base.
- Instant settlement mechanisms incentivize continuous, low-friction transactions.
- Scalable edge computing reduces response times, enabling time-sensitive use cases.
Sector-Specific Adoption and Revenue Generation
Sector-specific adoption directly drives the expansion of the Economy of Things market size by enabling precise monetization of physical assets. In manufacturing, the adoption of automated machine-to-machine payments for raw material replenishment generates recurring revenue streams from idle equipment. Agriculture generates revenue by charging IoT-enabled irrigation systems per data-driven watering cycle, turning a cost center into a profit node. Smart logistics firms adopt tokenized asset tracking, billing clients per sensor-verified shipment milestone rather than flat fees. Each sector’s targeted implementation shifts value from simple connectivity fees to transactional revenue, expanding the total addressable market as more industries launch pay-per-use or outcome-based billing models for physical assets.
Industrial Manufacturing and Supply Chain Tokenization
Within the Economy of Things market size growth, Industrial Manufacturing and Supply Chain Tokenization converts physical assets like raw materials and finished goods into digital tokens. This enables real-time, verifiable ownership and provenance tracking across production lines. By tokenizing components, manufacturers create a transparent, immutable ledger for every transaction, from procurement to delivery. This practical application directly reduces verification costs and eliminates reconciliation delays between suppliers and producers. The resulting efficiency gains drive tokenized supply chain automation, allowing factories to autonomously manage inventory and execute payments via smart contracts when goods change hands, directly impacting operational capacity and asset utilization.
Smart Mobility and Automotive Data Monetization
Within the Economy of Things market, smart mobility data streams directly fuel revenue by transforming vehicles into autonomous earning assets. Cars collect and sell real-time telemetry on traffic patterns, road conditions, and parking availability to navigation providers and insurers. This automotive data monetization allows drivers to offset ownership costs while enabling city planners to optimize infrastructure utilization. The vehicle-as-a-sensor model generates passive income from every trip, directly expanding the Economy of Things market valuation through recurring data subscription services.
- Monetize driving patterns by selling anonymized traffic flow data to logistics firms.
- Generate revenue from predictive maintenance alerts shared with dealerships and fleet operators.
- Earn microtransactions by contributing real-time road hazard and weather condition reports.
Energy Grids and Decentralized Utility Markets
Energy grids transform into decentralized utility markets by enabling peer-to-peer energy trading between producers and consumers. Within the Economy of Things, smart meters and IoT devices automatically settle micro-transactions for surplus solar or battery power. This infrastructure allows households to sell excess electricity to neighbors without a central utility intermediary. Revenue generation occurs through dynamic pricing algorithms that adjust rates based on real-time grid load and local supply.
How do decentralized utility markets handle energy surplus during low-demand periods? Smart contracts on the grid automatically redirect excess power to storage units or curtail generation, preventing waste while settling compensation instantly between connected devices.
Healthcare and Medical Device Asset Streams
Within the Economy of Things, Healthcare and Medical Device Asset Streams monetize real-time clinical data from connected infusion pumps, vital sign monitors, and imaging equipment. These streams generate revenue through predictive maintenance contracts that reduce device downtime, and through billing for device-verified medication administration records. A hospital’s fleet of ventilators becomes a value-generating asset when their operational metrics are sold to device manufacturers for improving hardware reliability.
Real-time clinical data monetization creates a new revenue layer, as insurers pay for verified patient adherence data from smart inhalers. Every asset stream directly extends from the device’s primary clinical function, not from pharmaceutical sales. Q: How does a hospital generate revenue from a connected MRI machine? A: By licensing its utilization and calibration data to service providers who optimize imaging sequences for faster throughput, reducing per-scan costs and enabling billable uptime guarantees.
Geographic Hotspots for Market Development
For Economy of Things market size growth, geographic hotspots for market development are places with dense, aging infrastructure—like Tokyo’s subway tunnels or New York’s water mains—where adding tiny, cheap sensors creates immediate value. Northern Europe cities, with high digital literacy and cold winters, are prime for smart heating grids, while Southeast Asian megacities, battling congestion, drive demand for tokenized traffic management. User adoption in these spots often hinges on a single, hyperlocal problem—like Seoul’s constant basement flooding—more than any broad economic theory.
North America’s Lead in Infrastructure and Regulatory Sandboxes
North America jumps ahead in the Economy of Things market because its advanced regulatory sandbox ecosystems let you test connected devices without heavy red tape. This means you can pilot smart city sensors or vehicle-to-grid chargers in real neighborhoods, not just labs. The infrastructure is already in place: widespread 5G and fiber networks handle real-time data from your prototypes. For smoother deployment, follow this sequence:
- Partner with a local sandbox program (e.g., in Arizona or Texas) to get temporary rule exemptions.
- Use existing highway toll sensors and utility grids to piggyback your Economy of Things hardware.
- Scale fast because the sandbox data lets you prove compliance without licensing waits.
Europe’s Push for Data Sovereignty and Interoperability Standards
Europe’s push for data sovereignty and interoperability standards directly empowers users by ensuring their IoT-generated value remains under local control. This framework compels connected devices and platforms to operate on open, cross-border protocols, preventing vendor lock-in and enabling seamless data exchange between smart cities, factories, and logistics networks. For the Economy of Things market, this creates a scalable environment where federated data governance becomes a practical feature, not a bureaucratic hurdle. Users can confidently invest in smart infrastructure, knowing their data flows securely and compatibly across European systems without reliance on non-EU giants.
Q: How does Europe’s push for data sovereignty and interoperability standards benefit a user deploying IoT sensors?
A: It guarantees your sensor data can be securely shared across any compliant EU platform, avoiding costly proprietary system replacements while maintaining your ownership and privacy rights.
Asia-Pacific’s Rapid Scalability in Smart City Deployments
Across Asia-Pacific, cities skip legacy infrastructure entirely, letting them scale smart deployments at a pace other regions can’t match. This rapid scalability in smart city deployments directly expands the Economy of Things by creating dense, real-time data grids overnight. For example, integrated sensor networks in new districts immediately support dynamic tolling, waste management billing, and shared mobility pricing. As these cities grow, each connected lamppost or meter becomes a transaction point, accelerating market size growth without waiting for retrofit cycles. The result is a living lab where user behaviors and payments evolve together, proving that speed of deployment is the region’s real advantage.
Asia-Pacific skips the old and builds smart fast, turning every new city node into an Economy of Things transaction point.
Emerging Opportunities in Middle Eastern and Latin American Markets
Middle Eastern and Latin American markets are unlocking fresh value in the Economy of Things by converting everyday items into active data nodes. In the Middle East, smart logistics across trade corridors is a prime opportunity, where vehicle and container sensors streamline cross-border supply chains. For Latin America, rural agriculture gains traction by equipping crops and machinery with IoT tags to reduce spoilage. A clear sequence to tap these opportunities includes:
- Partner with local telecoms for affordable device connectivity.
- Target high-friction sectors like desert logistics or coffee exports.
- Pilot with small, shareable asset trackers before scaling.
Both regions reward practical fixes over flashy tech—turn idle cargo or farmland into revenue streams.
Technology Pillars Enabling Expansion
The expansion of the Economy of Things market size is directly enabled by three core technology pillars: ubiquitous connectivity, scalable edge computing, and interoperable digital ledgers. Without these pillars, the practical monetization of data from billions of connected devices remains impossible. The deployment of low-power, wide-area networks allows devices to transmit value-generating data efficiently, while edge computing reduces latency to enable real-time asset transactions, such Gavin Whitechurch as micropayments for energy usage. Furthermore, distributed ledger technology provides the immutable, low-cost settlement layer required for machine-to-machine commerce, removing the friction of traditional financial infrastructure and permitting market size growth through automated, trustless exchanges. These pillars together form the operational backbone that scales the Economy of Things from concept to viable, revenue-generating reality.
Blockchain and Distributed Ledger Frameworks for Trustless Transactions
Blockchain and distributed ledger frameworks provide the foundational infrastructure for trustless transaction execution within the expanding Economy of Things. By replacing centralized intermediaries with immutable, cryptographically verified ledgers, these frameworks enable devices to autonomously authenticate, settle, and record exchanges without human oversight or contractual delays. Each peer-to-peer transfer—whether for sensor data, bandwidth, or storage—is validated through consensus mechanisms, ensuring non-repudiation and auditable provenance. This architecture removes friction and counter-party risk, allowing micro-transactions between billions of devices to scale securely. Without these ledgers, decentralized value exchange would remain impractical, capping market expansion.
- Immutable ledgers guarantee transaction finality
- Smart contracts automate service-level agreements
- Cryptographic signatures prevent data tampering
- Consensus protocols validate exchanges without intermediaries
Advanced Edge Computing and Real-Time Data Processing
Advanced Edge Computing and Real-Time Data Processing minimizes latency by executing analytics directly on IoT gateways and connected devices, eliminating round-trips to centralized cloud servers. This enables instantaneous decision-making for autonomous transactions within the Economy of Things, such as dynamic pricing of shared EV charging or micro-payments for bandwidth usage. By processing sensor streams locally, edge nodes reduce data volume sent upstream, lowering transmission costs and enabling scalable device density. This architecture supports bandwidth-constrained environments, allowing real-time machine-to-machine negotiations without dependency on stable connectivity.
- Sub-millisecond inference for automated resource trading between devices
- Local data aggregation and filtering to minimize cloud egress fees
- Decentralized transaction validation via edge-based smart contracts
5G and Low-Power Wide-Area Network Connectivity
5G and Low-Power Wide-Area Network (LPWAN) connectivity form the essential communication backbone for the Economy of Things, enabling billions of devices to transact value directly. 5G’s ultra-reliable low-latency communication supports real-time micropayments between autonomous assets like vehicles and drones. Meanwhile, LPWAN technologies, such as NB-IoT and LoRaWAN, provide deep indoor penetration and battery life spanning years, critical for static sensors in logistics or agriculture. This creates a seamless tiered architecture: massive machine-type communication for high-density, low-cost devices and 5G’s enhanced mobile broadband for data-rich interactions.
- 5G network slicing allocates dedicated bandwidth for high-priority economic transactions between machines.
- LPWAN enables continuous asset tracking and billing for low-power inventory tags across vast areas.
- Combined 5G-LPWAN gateways bridge high-speed payments with low-power sensor networks.
- Energy harvesting modules pair with LPWAN to support autonomous, unaided device participation in the Economy of Things.
Digital Twins and AI-Driven Asset Optimization
Digital Twins and AI-Driven Asset Optimization form a critical technology pillar enabling Economy of Things (EoT) expansion by virtualizing physical assets and automating their performance. A digital twin creates a real-time simulation of an object—such as a vehicle, turbine, or supply-chain container—allowing AI algorithms to continuously analyze sensor data, predict wear, and adjust operational parameters without human intervention. This closed-loop system directly reduces downtime and energy consumption across distributed, connected assets, which is essential for scaling EoT networks profitably. Without AI-driven optimization of these virtual replicas, the sheer volume of device interactions in an expanded market would render manual management impossible, making this pairing a practical prerequisite for asset-intensive industries.
| Aspect | Digital Twin Role | AI-Driven Optimization Role |
|---|---|---|
| Function | Real-time virtual replication of physical assets | Predictive analytics and autonomous control |
| User Benefit | Enables remote monitoring and scenario testing | Cuts operational costs and extends asset lifespan |
| EoT Contribution | Creates a unified data layer for billing and tracking | Automates value extraction from asset interactions |
Regulatory and Economic Drivers Shaping Growth
Economic incentives like tax breaks for IoT infrastructure directly lower deployment costs, which fuels Economy of Things market size growth by making connectivity affordable for more devices. Mandated efficiency standards in energy sectors force businesses to adopt automated resource tracking, creating a regulatory push that expands the network of transacting machines. These combined drivers ensure that compliance costs become reinvestments into scalable data exchange, steadily increasing the market’s transactional volume without relying on speculative hype.
Shifts in Data Privacy Laws and Cross-Border Asset Flows
Shifts in data privacy laws directly govern how asset-related data flows across borders, creating friction or fluidity in the Economy of Things. Asset owners must now align tokenized ownership records with regional privacy mandates, ensuring that cross-border asset transfers do not expose sensitive user data. This forces platforms to embed compliance-driven data localization into their infrastructure, affecting how asset titles and usage histories are shared internationally.
- Users face longer settlement times when asset metadata must be scrubbed of personal identifiers before crossing jurisdictions.
- Privacy law shifts require smart contract logic to automatically restrict asset flows to regions with equivalent data protection levels.
- Cross-border asset flows now demand encrypted, permissioned data channels that separate ownership proof from personal transaction history.
Incentive Structures for Decentralized Machine-to-Machine Payments
Decentralized machine-to-machine (M2M) payments rely on incentive structures that align device behavior with network efficiency. A token-based reward system directly compensates machines for executing specific transactions, such as data relay or energy transfer, without human intervention. Dynamic pricing algorithms within smart contracts adjust payouts in real-time based on demand, preventing spam or idle resource hoarding. Clear penalty mechanisms (e.g., staking) deter malicious nodes that might otherwise disrupt payment flow.
- Performance-based micropayments encourage devices to maintain uptime and low latency.
- Reputation scores tied to payment history enable trustless negotiation between autonomous agents.
- Slashing conditions on deposited collateral disincentivize incomplete or fraudulent transaction finalization.
Institutional Investment and Venture Capital Trends
Institutional capital and venture funding are accelerating the Economy of Things by powering real-world asset tokenization and decentralized physical infrastructure networks. Venture firms now lead Series A rounds for startups connecting IoT sensors to blockchain oracles, directly scaling machine-to-machine payment systems. Institutional investors deploy funds into DePIN protocols, betting on tokenized hardware assets like wireless hotspots or energy grids to generate yield. This capital flow turns proof-of-concept projects into operational networks, enabling developers to build on stable liquidity. Without these investment waves, the infrastructure needed for trillions of connected devices to transact autonomously would remain experimental.
Institutional Investment and Venture Capital Trends funnel liquidity into tokenized physical infrastructure and DePIN networks, transforming pilot projects into scalable ecosystems that enable autonomous economic transactions between devices.
Challenges and Bottlenecks Hindering Scaling
Scaling the Economy of Things (EoT) market size growth is primarily hindered by the fragmented interoperability between billions of disparate devices and legacy systems, which creates data silos. This lack of universal, secure communication protocols forces costly custom integrations for each deployment, drastically slowing adoption. A critical bottleneck is the real-time transaction latency across distributed ledgers, which cannot yet support the micro-transaction volume needed for true machine-to-machine commerce. Without a unified, decentralized identity standard for machines, trust remains broken, making scalable automation unachievable. These interoperability and performance gaps directly choke the network effects required for exponential EoT market size growth.
Security Vulnerabilities in Autonomous Transaction Networks
As the Economy of Things expands, autonomous transaction network compromise directly throttles growth. Unsecured machine-to-machine endpoints become entry points for transaction injection, allowing attackers to drain digital wallets without human authorization. The sequence of exploitation is clear: first, an IoT sensor’s weak authentication is bypassed; second, a forged value request triggers an irreversible settlement; third, the corrupted ledger record propagates across the network, corrupting dependent smart contracts. Without hardware-backed identity verification and real-time anomaly detection at the protocol layer, each autonomous device becomes a liability. This transactional fragility deters system integrators from scaling deployments, as a single compromised node can cascade financial losses across the entire peer-to-peer infrastructure.
Standardization Gaps Across Industry Vertical Platforms
Standardization gaps across industry vertical platforms create fragmentation, as each sector—manufacturing, logistics, or energy—deploys proprietary data models and communication protocols. This forces users managing cross-platform device interoperability to build custom middleware for each integration, directly throttling Economy of Things scaling. The lack of unified semantic layers causes data silos; a temperature sensor from an industrial platform cannot natively share readings with an asset-tracking platform. Consequently, scaling requires solving these practical mismatches:
- Reconciling different IoT messaging standards (e.g., MQTT vs. OPC UA) at the edge.
- Mapping divergent data schemas for value transactions between verticals.
- Ensuring identity and permission models align across platforms without manual translation.
High Initial Infrastructure Costs and Interoperability Hurdles
The scaling of the Economy of Things (EoT) is critically bottlenecked by prohibitive deployment costs for the sensor networks and edge infrastructure required to connect physical assets, combined with severe interoperability hurdles between proprietary IoT platforms. These integration and protocol mismatch barriers force adopters into costly custom middleware development, negating the very economies of scale that drive market expansion. Without a universal standard for data exchange, replacing or adding diversified devices remains a high-risk, capital-intensive endeavor that stalls practical user adoption.
Q: Why do interoperability hurdles directly increase initial infrastructure costs for Economy of Things projects?
A: To bridge incompatible communication protocols (e.g., Zigbee vs. LoRaWAN), users must purchase expensive gateway hardware and develop bespoke middleware, often doubling or tripling the upfront capital expenditure for a workable system. This financial friction prevents the aggregate device volume needed to reduce per-unit costs.
Future Outlook and Strategic Implications
The expanding Economy of Things market size forces businesses to rethink asset monetization. A larger ecosystem means micro-transactions between smart devices will become a primary revenue stream, not an afterthought. Strategically, companies must pivot from selling products to managing autonomous service networks. As device density grows, the strategic implications for value creation shift from hardware to enabling seamless, trustless peer-to-peer value exchanges. Firms that invest today in scalable digital twin architectures and decentralized settlement layers will own the critical infrastructure for tomorrow’s automated commerce. The future outlook depends on capturing value from real-time data flows, where every connected thing becomes a micro-economy node.
Predicted Convergence with Artificial Intelligence and Autonomous Agents
The predicted convergence with artificial intelligence and autonomous agents will transform the Economy of Things by enabling devices to negotiate and transact independently. Autonomous economic decision-making becomes practical when AI agents on smart appliances or vehicles optimize spending for energy or parking in real-time. This works through a clear sequence:
- AI agents analyze local data and user preferences.
- They execute micro-transactions with other agents or platforms.
- The device self-optimizes resource usage without manual input.
You’ll see your car choosing cheaper charging times or your fridge ordering supplies based on price dips, all handled by these agents within a scalable Economy of Things framework.
Long-Term Revenue Models in Subscription and Usage-Based Economies
Long-term revenue models in subscription and usage-based economies hinge on recurring value capture rather than single transactions. Subscriptions provide predictable cash flow by bundling access to Economy of Things (EoT) services, while usage-based billing scales revenue with real-time asset consumption. For sustainable growth, hybrid models that blend a base subscription for connectivity with variable fees for data processing or automation actions are essential to align cost with user value. Pricing must reflect incremental device intelligence, not just data volume. Companies will invest in dynamic billing infrastructure to adjust rates based on peak load or service tier, ensuring revenue stability as connected device ecosystems expand.
Potential Disruption of Traditional Insurance and Leasing Sectors
As the Economy of Things market expands, it directly erodes traditional insurance and leasing models. Real-time data from connected assets enables dynamic usage-based policies, making static annual premiums obsolete. Leasing shifts from fixed terms to pay-per-performance, where sensor data dictates rates and liabilities. This forces insurers and lessors to adopt agile, data-driven platforms or face obsolescence. Question: How does the Economy of Things disrupt standard vehicle leasing? It replaces fixed monthly payments with variable fees calculated from actual mileage, driving behavior, and asset health data, eliminating rigid contracts.