Lesson 1Security fundamentals end-to-end: device identity, secure boot, secure storage, TLS, OTA signingHere we cover full security for industrial sensors, from device IDs, safe starting up, secure data keeping, TLS connections, OTA signing, and key handling, plus how to fit these into designs without messing up ease of use or running time.
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 look at embedded setups for industrial sensors, picking MCUs, memory plans, real-time OS, drivers, bootloaders, and organising firmware for reliability, testing ease, and safe field updates.
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 details nonfunctional needs for sensors like uptime, speed delays, growth ability, data flow rates, and upkeep ease, turning them into solid targets, service promises, and design 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 check key hardware parts for industrial sensors: sensors themselves, signal prep, power supply handling, and casings, stressing reliability, low noise, and protection in rough outdoor sites.
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 tradeoffsCompare connection choices for sensors like Ethernet, Wi-Fi, BLE, LoRaWAN, cellular types, weighing range, speed, power use, cost, steadiness, and rules for various site needs.
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, APIsSee cloud patterns for IoT sensor data: intake points, queues, time-based storage, APIs, stream handling, designing scalable, safe, cheap 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 casesLearn to gather sensor needs and link to cases like process watching, breakdown prediction, safety, rules, balancing cost, 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 inferenceFind out how edge units sample, clean, group sensor data, when to drop or shrink info, and use simple ML on-site to cut bandwidth and delays while keeping vital info.
Designing sampling rates and windowsFiltering noise and outlier rejectionAggregation, compression, and downsamplingLocal ML inference and model selectionBalancing edge and cloud responsibilities
