Amazon Lookout for Equipment

aid: amazon-lookout-for-equipment
name: Amazon Lookout for Equipment
description: Amazon Lookout for Equipment uses machine learning to analyze sensor data from your industrial equipment and
  detect abnormal patterns that signal potential failures. It helps you avoid unplanned equipment downtime by identifying
  potential equipment failures before they occur.
type: Index
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/amazon-lookout-for-equipment.png
tags:
- AWS
- Equipment Monitoring
- Industrial IoT
- Machine Learning
- Predictive Maintenance
url: https://raw.githubusercontent.com/api-evangelist/amazon-lookout-for-equipment/refs/heads/main/apis.yml
created: '2026-03-16'
modified: '2026-05-19'
specificationVersion: '0.19'
apis:
- aid: amazon-lookout-for-equipment:amazon-lookout-for-equipment-datasets-api
  name: Amazon Lookout for Equipment Datasets API
  description: Equipment sensor dataset management
  humanURL: https://aws.amazon.com/lookout-for-equipment/
  baseURL: https://lookoutequipment.amazonaws.com
  tags:
  - Datasets
  properties:
  - type: OpenAPI
    url: openapi/amazon-lookout-for-equipment-datasets-api-openapi.yml
  - type: Documentation
    url: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/API_Reference.html
  - type: GettingStarted
    url: https://aws.amazon.com/lookout-for-equipment/getting-started/
  - type: Pricing
    url: https://aws.amazon.com/lookout-for-equipment/pricing/
  - type: FAQ
    url: https://aws.amazon.com/lookout-for-equipment/faqs/
  - type: JSONSchema
    url: json-schema/amazon-lookout-for-equipment-dataset-schema.json
  - type: JSONSchema
    url: json-schema/amazon-lookout-for-equipment-model-schema.json
  - type: JSONLD
    url: json-ld/amazon-lookout-for-equipment-context.jsonld
common:
- type: PostmanWorkspace
  url: https://www.postman.com/kinlaneapi/amazon-lookout-for-equipment/overview
- type: AgenticAccess
  url: agentic-access/amazon-lookout-for-equipment-agentic-access.yml
- type: TrustCenter
  url: security/amazon-lookout-for-equipment-trust-center.yml
- type: VulnerabilityDisclosure
  url: security/amazon-lookout-for-equipment-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/amazon-lookout-for-equipment-domain-security.yml
- type: Authentication
  url: authentication/amazon-lookout-for-equipment-authentication.yml
- type: Portal
  url: https://aws.amazon.com/lookout-for-equipment/
- type: Portal
  url: https://aws.amazon.com/lookout-for-equipment/
- type: Documentation
  url: https://docs.aws.amazon.com/lookout-for-equipment/
- type: TermsOfService
  url: https://aws.amazon.com/service-terms/
- type: PrivacyPolicy
  url: https://aws.amazon.com/privacy/
- type: Support
  url: https://aws.amazon.com/premiumsupport/
- type: Blog
  url: https://aws.amazon.com/blogs/machine-learning/tag/amazon-lookout-for-equipment/
- type: GitHubOrganization
  url: https://github.com/aws
- type: Console
  url: https://console.aws.amazon.com/lookoutequipment/
- type: Signup
  url: https://portal.aws.amazon.com/billing/signup
- type: Login
  url: https://signin.aws.amazon.com/
- type: StatusPage
  url: https://health.aws.amazon.com/health/status
- type: Contact
  url: https://aws.amazon.com/contact-us/
- type: Features
  data:
  - name: Anomaly Detection
    description: Detect abnormal equipment behavior using ML models trained on equipment sensor data.
  - name: Predictive Maintenance
    description: Predict equipment failures before they occur to reduce unplanned downtime.
  - name: No ML Expertise Required
    description: Automatically build ML models from historical sensor data without data science expertise.
  - name: Multi-Sensor Support
    description: Analyze data from hundreds of sensors simultaneously to detect complex failure patterns.
  - name: Real-Time Inference
    description: Run continuous inference on streaming sensor data for real-time failure detection.
- type: UseCases
  data:
  - name: Manufacturing Predictive Maintenance
    description: Detect early warning signs of equipment failures in manufacturing machinery.
  - name: Energy Sector Monitoring
    description: Monitor industrial equipment in power plants, wind turbines, and oil refineries.
  - name: Mining Equipment Health
    description: Track the health of heavy mining equipment to prevent costly breakdowns.
  - name: HVAC System Monitoring
    description: Detect anomalies in HVAC systems to prevent equipment failures in buildings.
- type: Integrations
  data:
  - name: Amazon S3
    description: Store and access equipment sensor data in S3 for model training and inference.
  - name: AWS IoT SiteWise
    description: Collect and organize equipment sensor data with IoT SiteWise and analyze with Lookout.
  - name: Amazon Kinesis Data Streams
    description: Stream real-time sensor data from equipment to Lookout for Equipment.
  - name: AWS IoT Core
    description: Connect industrial equipment to AWS via IoT Core for data ingestion.
- type: SpectralRules
  url: rules/amazon-lookout-for-equipment-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/amazon-lookout-for-equipment-vocabulary.yaml
- type: Integrations
  url: https://aws.amazon.com/marketplace
integrations:
- name: Sign in
- name: Agent Mode
- name: Why AWS Marketplace?
- name: Get started in AWS Marketplace
- name: Industry
- name: Resources
- name: Become a Channel Partner
- name: Sell in AWS Marketplace
- name: Manage Your Account
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com