Lesson 1Security fundamentals end-to-end: device identity, secure boot, secure storage, TLS, OTA signingHere we introduce full-chain security for industrial sensors, covering device identity, safe startup, protected storage, TLS connections, OTA signing, and key handling, showing how to weave these into designs without disrupting ease of use or constant operation.
Provisioning device identity and certificatesSecure boot chains and firmware integritySecure storage of keys and secretsTLS configuration for constrained devicesSigned OTA updates and rollback safetyLesson 2Embedded systems architecture: MCUs, real-time OS, drivers, bootloaderWe cover built-in system designs for industrial sensors, including picking MCUs, memory plans, real-time systems, drivers, bootloaders, and organising firmware for steadiness, testing ease, and secure field updates via air.
Choosing MCU families and peripheralsMemory maps, flash, and RAM planningRTOS tasks, scheduling, and prioritiesDriver abstraction and hardware isolationBootloaders and firmware update flowsLesson 3Operational nonfunctional requirements: availability, latency, scalability, throughput, maintainabilityThis part outlines nonfunctional needs for industrial sensors like uptime, delay, growth capacity, flow rate, and upkeep, and demonstrates turning them into solid design goals, service agreements, and balance choices across layers.
Defining SLAs and SLOs for sensor fleetsModeling latency and end-to-end timingThroughput, batching, and backpressureDesigning for availability and failoverMaintainability, observability, and supportLesson 4Sensor hardware components: transducers, conditioning, power, enclosuresWe look closely at main hardware parts of industrial sensors, such as converters, signal prep, power supply handling, and casings, stressing reliability, low noise, and shielding from harsh weather in remote spots.
Selecting transducers for target phenomenaSignal conditioning and analog front endsPower budgeting and energy harvestingBattery life, regulators, and protectionEnclosure design and environmental sealingLesson 5Connectivity options: Ethernet, Wi‑Fi, BLE, LoRaWAN, cellular (NB‑IoT, LTE‑M) and tradeoffsHere we weigh connection choices for industrial sensors like Ethernet, Wi-Fi, BLE, LoRaWAN, and mobile types, explaining balances in reach, speed, energy use, expense, steadiness, and rules for various site setups.
Ethernet and industrial fieldbus integrationWi-Fi for high-throughput local networksBLE for commissioning and local accessLoRaWAN and sub-GHz long-range linksNB-IoT and LTE-M cellular deploymentsLesson 6Cloud architecture patterns for IoT: ingestion, message queues, time-series storage, APIsWe present cloud patterns for IoT sensor info, including intake points, queue systems, time-based storage, APIs, and data streams, guiding scalable, safe, and budget-friendly backends for big device groups.
Designing ingestion endpoints and gatewaysMessage queues, topics, and routingTime-series databases and retentionAPIs for data access and integrationStream processing and alert pipelinesLesson 7Understanding industrial sensor requirements and typical use casesThis clarifies gathering industrial sensor needs and linking to common cases like process watch, upkeep prediction, safety checks, and rule following, while juggling costs, power, precision, and fitting in.
Eliciting stakeholder and field requirementsDefining accuracy, range, and sampling needsEnvironmental and regulatory constraintsPower, cost, and lifetime trade studiesTranslating use cases into specs and KPIsLesson 8Edge processing and data reduction: sampling, filtering, aggregation, local ML inferenceWe explain how edge units sample, clean, and sum sensor data, when to trim or pack it, and use simple machine learning on-site to cut bandwidth and wait times yet keep vital insights.
Designing sampling rates and windowsFiltering noise and outlier rejectionAggregation, compression, and downsamplingLocal ML inference and model selectionBalancing edge and cloud responsibilities
