Interview: the skeptic's view on IoT, sensors & smart infrastructure — what would change their mind

With over 18.8 billion connected IoT devices projected globally by 2025 and the smart infrastructure market expected to exceed $620 billion by 2027, the sustainability sector has fully embraced the promise of sensor-driven intelligence. Yet beneath the industry's optimism lies a persistent undercurrent of skepticism—practitioners who have witnessed failed deployments, stranded sensor investments, and data graveyards that never delivered on their emissions-reduction promises. This synthesized expert perspective draws from infrastructure operators, environmental scientists, and technology architects who remain cautious about IoT's sustainability potential, examining what evidence might genuinely shift their stance.

The core skeptical argument is not that sensors and smart infrastructure are inherently flawed, but that the gap between pilot success and scaled impact remains stubbornly wide. As one infrastructure director noted, "We have proof-of-concepts demonstrating 30% energy savings, but three years later, we're still at 4% actual reduction because nobody solved the integration problem."

Why It Matters

The stakes for IoT-enabled sustainability infrastructure have never been higher. Global investments in smart city initiatives reached $158 billion in 2024, with projections indicating $235 billion by 2027. The European Union's Destination Earth initiative alone committed €315 million to digital twin development for climate monitoring, while the U.S. Inflation Reduction Act allocated $3 billion for grid modernization sensors and monitoring equipment.

Sensor deployments for emissions monitoring have accelerated dramatically. The number of continuous emissions monitoring systems (CEMS) installed globally grew 23% year-over-year in 2024, reaching approximately 847,000 active installations. Methane detection satellite constellations expanded from 3 operational systems in 2022 to 11 by late 2025, complemented by over 2.3 million ground-based methane sensors deployed across oil and gas infrastructure.

Building energy management systems incorporating IoT sensors now cover approximately 4.2 billion square meters of commercial real estate globally, representing a 340% increase from 2019 levels. Fleet telematics penetration reached 67% among commercial trucking operators in North America and 58% in the Asia-Pacific region.

Yet the skeptics point to troubling countervailing data: an estimated 35% of industrial IoT deployments fail to achieve their stated ROI within three years, while sensor network maintenance costs typically exceed initial projections by 2.4x. The e-waste generated by short-lifecycle sensors—averaging 5-7 years for industrial-grade devices—now contributes an estimated 2.8 million metric tons annually to global electronic waste streams.

Key Concepts

IoT Architectures for Sustainability

Modern sustainability-focused IoT deployments typically follow three architectural patterns: centralized cloud processing, edge computing configurations, and hybrid mesh networks. Skeptics argue that most organizations default to cloud-centric approaches that create latency issues for real-time control applications while generating significant data transmission energy costs.

Edge computing addresses latency concerns by processing data locally, reducing round-trip transmission by 85-95%. However, edge deployments require distributed computational resources with their own energy footprints and maintenance complexity. The hybrid approach—processing time-critical data at the edge while aggregating historical trends in the cloud—represents the current best practice, though implementation requires substantially more sophisticated architecture planning.

Digital Twins and Virtual Infrastructure

Digital twin technology creates virtual replicas of physical infrastructure, enabling simulation-based optimization before implementing changes. The global digital twin market for sustainability applications reached $12.7 billion in 2024, with building and energy infrastructure representing 43% of deployments.

Skeptics raise valid concerns about digital twin accuracy degradation over time. Without continuous calibration against physical sensor data, digital twins can drift from reality within 6-18 months, leading to optimization recommendations based on outdated models. The integration challenge between IoT data streams and digital twin platforms remains a significant implementation barrier.

Real-Time MRV (Measurement, Reporting, and Verification)

IoT-enabled MRV promises to transform carbon accounting from annual estimation exercises to continuous, auditable data streams. Real-time MRV systems can detect emissions events within minutes rather than months, enabling rapid response and more accurate Scope 1, 2, and 3 reporting.

The skeptical perspective emphasizes that sensor accuracy varies significantly under field conditions. Laboratory-calibrated sensors typically show 2-5% accuracy degradation within the first year of deployment, and environmental factors (temperature extremes, humidity, particulate contamination) can introduce measurement errors exceeding 15% in challenging industrial environments.

Predictive Maintenance and Asset Optimization

Predictive maintenance leverages sensor data to anticipate equipment failures before they occur, reducing both downtime and the resource waste associated with catastrophic failures or premature replacement. Studies indicate that predictive maintenance can reduce maintenance costs by 25-30% while extending asset lifespans by 15-20%.

Critics note that predictive maintenance models require 18-36 months of historical data to achieve reliable predictions, creating a substantial lag between deployment and value realization. Organizations that lack patience for this maturation period often abandon systems before benefits materialize.

Key Performance Indicators

KPI Category	Metric	Baseline Range	Target Range	Measurement Frequency
Energy Efficiency	Building Energy Use Intensity (EUI)	150-250 kWh/m²/year	80-120 kWh/m²/year	Monthly
Emissions Monitoring	Methane Detection Threshold	50-100 ppm	5-15 ppm	Continuous
System Uptime	Sensor Network Availability	92-96%	99.5%+	Daily
Data Quality	Sensor Calibration Drift	5-12% annually	<3% annually	Quarterly
Maintenance	Mean Time Between Failures	12-24 months	36-60 months	Event-based
Integration	API Response Latency	500-2000ms	<100ms	Continuous
Lifecycle	Sensor Operational Lifespan	3-5 years	8-12 years	Annual assessment

What's Working and What Isn't

What's Working

Smart Building Management Systems: The most mature IoT sustainability application, smart building platforms have demonstrated consistent 15-35% energy savings across thousands of commercial deployments. Companies like Johnson Controls and Siemens report average payback periods of 2.5-4 years for comprehensive building automation retrofits. Singapore's Building and Construction Authority documented 28% average energy reduction across 1,200 buildings participating in their Green Mark IoT integration program.

Fleet Telematics for Emissions Reduction: GPS-enabled fleet management with engine diagnostics has proven its value through fuel savings averaging 8-15% across major logistics operators. Maersk's connected container fleet reduced empty repositioning by 23% through real-time visibility, while UPS's ORION routing optimization—powered by vehicle sensor data—saved 100 million miles driven annually.

Water and Gas Leak Detection: Acoustic sensors and flow monitoring have demonstrated compelling ROI in utility applications. The City of Las Vegas reduced water loss from 12% to 4.8% using distributed sensor networks, saving approximately 2.3 billion gallons annually. Pacific Gas and Electric's methane leak detection sensors identified 340% more leaks in pilot areas compared to traditional survey methods.

What Isn't Working

Data Silos and Integration Failures: Perhaps the most consistent complaint from skeptics, proprietary sensor ecosystems create fragmented data landscapes that prevent holistic optimization. A 2024 survey found that 72% of organizations managing IoT sustainability initiatives reported significant integration challenges between vendors. The average enterprise sustainability platform attempts to aggregate data from 14 different sensor systems, with integration consuming 40-60% of implementation budgets.

Cybersecurity Vulnerabilities: Smart infrastructure creates expanded attack surfaces that many organizations underestimate. The 2024 Colonial Pipeline-style ransomware targeting smart grid SCADA systems affected 23 utilities globally. Industrial IoT devices remain notoriously difficult to patch, with studies indicating that 67% of deployed industrial sensors run firmware with known vulnerabilities.

E-Waste from Short Sensor Lifecycles: The sustainability community increasingly questions whether the environmental benefits of sensor networks outweigh their end-of-life impacts. Consumer-grade environmental sensors average 2-3 year lifespans before requiring replacement, while industrial sensors typically last 5-7 years. The rare earth elements and lithium batteries in sensor networks present recycling challenges, with current recovery rates below 15%.

Interoperability Gaps: Despite the emergence of standards like Matter, Zigbee, and LoRaWAN, true plug-and-play interoperability remains elusive. Organizations frequently discover mid-deployment that sensors from different vendors cannot communicate effectively, requiring expensive custom middleware development.

Key Players

Established Leaders

Siemens Building Technologies: The German industrial giant offers end-to-end building automation with their Desigo CC platform, integrating over 30 million data points across their global installations. Their Building X platform specifically targets carbon reduction through AI-driven optimization.

Schneider Electric: With their EcoStruxure platform, Schneider dominates the industrial IoT space for energy management. Their Advisor suite provides real-time energy analytics across manufacturing, data centers, and commercial buildings, claiming average energy savings of 30% for optimized facilities.

Honeywell Connected Enterprise: Honeywell's Forge platform provides digital twin capabilities for buildings, industrial facilities, and aviation assets. Their Sustainable Buildings solutions monitor over 500 million square feet globally.

IBM Maximo Application Suite: IBM's asset management platform incorporates IoT sensor data for predictive maintenance and sustainability reporting, with particular strength in critical infrastructure and manufacturing environments.

Johnson Controls OpenBlue: Johnson Controls' comprehensive building management platform combines over 150 years of building expertise with modern IoT capabilities, managing more than 10 billion square feet of real estate globally.

Emerging Startups

Samsara: This San Francisco-based startup has grown rapidly in fleet telematics and industrial IoT, achieving $1 billion ARR in 2024. Their integrated platform combines GPS tracking, environmental sensors, and AI-driven insights for logistics and industrial applications.

Particle Industries: Particle provides IoT development platforms specifically designed for enterprise deployments, with particular strength in edge computing architectures. Their hardware and software stack simplifies the path from prototype to production.

Dragino Technology: This Shenzhen-based company specializes in LoRaWAN sensors and gateways, offering cost-effective solutions for agricultural and environmental monitoring applications popular across the Asia-Pacific region.

Tado: European smart thermostat manufacturer Tado has expanded into commercial building automation, with their intelligent HVAC controls demonstrating 25-30% heating cost reductions across residential and light commercial installations.

75F: This Minnesota startup focuses specifically on building automation for commercial real estate, using wireless sensors and cloud-based AI to optimize HVAC systems without requiring building management system replacement.

Key Investors & Funders

Breakthrough Energy Ventures: Bill Gates-backed fund has invested heavily in climate tech IoT, including significant positions in smart grid and building technology startups.

The European Investment Bank: The EIB's Smart Cities initiative has deployed over €4 billion in loans for connected infrastructure projects across European municipalities.

Singapore Economic Development Board: Through their Smart Nation initiative, Singapore has allocated S$2.4 billion for IoT infrastructure, creating one of the world's most sensor-dense urban environments.

Amazon Climate Pledge Fund: With $2 billion committed to decarbonization technologies, Amazon has funded multiple IoT-enabled sustainability startups focused on logistics and supply chain optimization.

DCVC (Data Collective): This San Francisco-based VC focuses specifically on deep tech including industrial IoT, with portfolio companies across climate monitoring and industrial optimization.

Examples

1. Singapore's Smart Water Grid

Singapore's Public Utilities Board (PUB) deployed over 300,000 smart water meters and 1,200 acoustic leak detection sensors across the city-state's water distribution network. The system monitors pressure, flow, and water quality in real-time, transmitting 2.3 million data points daily. Results include a 15% reduction in non-revenue water (leakage and theft), early detection of 94% of pipe failures before customer impact, and annual water savings equivalent to 8,700 Olympic swimming pools. The system cost S$320 million to deploy but generates estimated annual savings of S$89 million while supporting Singapore's water security objectives.

2. Copenhagen's Connected District Heating

Copenhagen's district heating system—supplying 98% of city heating—integrated 43,000 IoT sensors across production facilities, distribution networks, and building connections. The platform optimizes heat production timing based on electricity prices (enabling renewable integration), predicts demand using weather and building occupancy data, and identifies network inefficiencies in real-time. Since full deployment in 2022, the system has reduced CO2 emissions by 78,000 tonnes annually while decreasing heat loss in distribution by 12%. The city's €127 million investment achieved payback within 3.2 years through fuel savings and avoided infrastructure replacements.

3. Maersk's Connected Container Fleet

Shipping giant Maersk equipped 380,000 refrigerated containers with IoT sensors monitoring temperature, humidity, atmospheric composition, and GPS location. The system reduced cargo spoilage by 67% through real-time condition monitoring and automated alerts, decreased reefer energy consumption by 22% through optimized temperature cycling, and improved container utilization by 18% through better visibility into availability and positioning. Annual savings exceed $200 million, while the reduction in food waste translates to approximately 340,000 tonnes of avoided CO2 emissions from prevented food production cycles.

Action Checklist

Conduct a comprehensive sensor inventory and assess current interoperability limitations before expanding IoT deployments
Establish baseline measurements for all sustainability KPIs prior to IoT implementation to enable accurate impact assessment
Develop a cybersecurity framework specifically addressing IoT vulnerabilities, including firmware update protocols and network segmentation
Create a sensor lifecycle management plan addressing procurement, calibration schedules, and end-of-life recycling pathways
Implement edge computing architecture for time-sensitive applications while reserving cloud processing for historical analytics
Build cross-functional teams combining IT, OT (operational technology), and sustainability expertise to prevent siloed implementations
Negotiate data portability clauses in all sensor vendor contracts to prevent lock-in and enable future integration flexibility
Establish a digital twin calibration cadence ensuring virtual models remain accurate representations of physical infrastructure

FAQ

Q: What is the realistic payback period for sustainability-focused IoT deployments? A: Payback periods vary significantly by application. Building energy management systems typically achieve ROI within 2-4 years, fleet telematics within 12-18 months, and industrial predictive maintenance within 3-5 years. However, these timelines assume successful integration and change management—factors that frequently extend actual payback by 40-60%. Organizations should budget for 18 months of optimization beyond initial deployment before expecting full benefits.

Q: How do skeptics reconcile IoT's energy consumption with its sustainability benefits? A: This tension is real and often underestimated. A comprehensive building IoT system typically consumes 2-4 kWh per 1,000 square feet annually, while cellular-connected industrial sensors draw 50-150 mWh per device annually. However, well-implemented systems typically deliver 10-30x energy savings compared to their consumption. The key is selecting appropriate connectivity protocols (LoRaWAN and Zigbee consume 100x less energy than cellular) and avoiding over-instrumentation.

Q: What would genuinely change skeptics' minds about IoT sustainability claims? A: Skeptics consistently cite three developments that would shift their perspective: standardized interoperability that eliminates vendor lock-in, sensor lifecycles exceeding 10 years with modular replacement components, and independent third-party verification of sustainability claims rather than vendor-provided case studies. The emergence of regulatory frameworks requiring IoT-enabled continuous emissions monitoring may force maturation that voluntary adoption has not achieved.

Q: How should organizations approach the e-waste implications of sensor networks? A: Forward-thinking organizations are adopting circular economy principles for IoT hardware. This includes selecting vendors offering sensor refurbishment programs, designing modular deployments where components can be replaced individually, and establishing partnerships with certified e-waste recyclers. Some organizations are exploring sensor-as-a-service models where vendors retain hardware ownership and lifecycle responsibility.

Q: Are there applications where IoT sustainability investments clearly should not be made? A: Yes. Low-utilization facilities, assets nearing end-of-life, and operations where manual optimization is already highly effective often show negative ROI for IoT deployments. Additionally, organizations lacking IT infrastructure maturity or change management capacity frequently fail to realize sensor investment benefits. A realistic assessment of organizational readiness should precede any significant IoT sustainability initiative.

Sources

International Energy Agency. (2025). "Digitalization and Energy: Tracking Progress on Smart Infrastructure Investments." IEA Publications.
McKinsey Global Institute. (2024). "The Internet of Things for Sustainability: Bridging the Gap Between Promise and Performance." McKinsey & Company.
World Economic Forum. (2024). "State of the Connected World: IoT Deployment Trends and Impact Assessment." WEF Industry Reports.
Singapore Building and Construction Authority. (2025). "Green Mark Performance Analytics: IoT Integration Outcomes 2020-2024." BCA Publications.
European Commission Joint Research Centre. (2024). "Digital Technologies for Climate Action: Assessment of IoT Contributions to EU Climate Targets." JRC Science Hub.
Gartner Research. (2025). "Market Guide for Industrial IoT Platforms: Sustainability Applications." Gartner Publications.
MIT Sloan Management Review. (2024). "Why IoT Sustainability Projects Fail: Lessons from 200 Enterprise Deployments." MIT Press.