You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
Client Challenge



A required part of this site couldn’t load. This may be due to a browser
extension, network issues, or browser settings. Please check your
connection, disable any ad blockers, or try using a different browser.
</reference>

<statements>
1. Studies show that IoT‑enabled HEMS can substantially reduce residential electricity costs and peak loads by shifting consumption to off‑peak hours, integrating local generation, and orchestrating storage. For example, one real‑time HEMS implementation integrating PV and BESS reported up to a 90% reduction in power costs for a single dwelling alongside improved user comfort and significant peak‑to‑average ratio reductions. Such results are encouraging ongoing deployment of cloud‑backed HEMS architectures that use scalable ingestion, storage, and analytics layers to support clusters of homes and multi‑level energy communities.
2. AI-driven HEMS platforms that automatically schedule appliances, HVAC, storage, and EV charging based on tariffs, forecasts, and user preferences, often delivered as cloud-connected services with mobile and voice interfaces.
3. Smart home products increasingly rely on hybrid cloud-edge architectures to manage data volume, latency requirements, and privacy constraints. Cloud platforms provide scalable ingestion, storage, and analytics across millions of devices, enabling advanced features such as predictive maintenance, fleet-wide firmware management, and tariff-aware optimization. At the same time, edge compute in devices—via embedded microcontrollers and NPUs—enables local decision-making for latency-sensitive tasks like security detection and sleep stage classification.
4. Architecture-centric studies of HEMS and smart home platforms emphasize modular microservices, technology-agnostic device compatibility, and standardized APIs for utilities, aggregators, and third-party app developers. This architectural direction informs product trends toward platform-oriented offerings: hubs, border routers, energy dashboards, and developer-friendly APIs that act as foundational layers for multiple device classes rather than isolated products.
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.