Distributed Fibre Sensing
DAS, DTS and compatible DSS observe spatial phenomena along the corridor.
IDRCIN combines a passive canopy fibre corridor, sparse research-defined autonomous LoRa scientific pods, UAV mapping and time-aware reconstruction. Fibre remains primary; a point pod is deployed only when a specialised physical probe is scientifically necessary.
IDRCIN combines distributed fibre sensing, autonomous specialised point sensing, UAV / remote sensing and temporal reconstruction. Different scientific questions require different capture modes. Research Question First remains the governing rule.
DAS, DTS and compatible DSS observe spatial phenomena along the corridor.
A specialised local probe is considered only when fibre cannot answer the question adequately.
LiDAR, RGB and research-defined thermal surveys provide terrain and canopy geometry.
Chainage, XYZ, instrument state and time align inside the proposed Temporal Digital Twin.
The approved physical baseline remains one ultra-light canopy cable containing approximately 5-6 optical fibres. It has no intermediate electronic fibre nodes, no intermediate DAQ and no powered repeaters.
A LoRa pod is an independent, retrievable research instrument. It is not an intermediate fibre node and does not support or repeat the fibre signal.
Direct low-duty-cycle LoRa communication may be evaluated to an existing authorised receiver or research station where RF conditions, link budget, spectrum approval and field validation permit.
A future direct path may be considered where technically and commercially feasible. Canopy attenuation, terrain shadowing, service availability, regulatory approval and field validation remain unresolved.
Each set may use one or more sensing modes only where scientifically appropriate: FD = Fibre Distributed, FE = Fibre Endpoint, AP = Autonomous Point Sensor, HY = Hybrid, RS = Remote Sensing.
Primarily distributed canopy fibre and repeat UAV context. A point probe is exceptional, not assumed.
The canopy cable remains primary. Autonomous endpoint/drop and retrieval remain validation targets.
Researcher-assisted placement, calibration and retrieval for precision probes at selected endpoints.
Point-sensor selection is a formal decision inside the existing fibre workflow, not a parallel wireless deployment programme.
Distributed fibre, fibre endpoint instrumentation and autonomous specialised point sensing are complementary. They have different spatial, power, payload and maintenance models.
Best for spatial phenomena along a compatible fibre corridor: thermal behaviour, vibration, strain-related response and validated event candidates.
Precision measurements at an approved terminal or optical endpoint. Power and interface depend on the selected instrument; arbitrary electronics do not run directly over passive fibre.
One specialised probe at one selected point. LoRa carries small summaries, events and health telemetry, not continuous high-bandwidth raw data.
| Attribute | Fibre Distributed | Fibre Endpoint | Autonomous Point Pod |
|---|---|---|---|
| Spatial model | Continuous corridor | Terminal point | Selected point |
| Power at measurement point | Typically passive fibre | Depends on instrument | Battery |
| Communication | Fibre | Fibre / endpoint system | Low-duty-cycle LoRa |
| Payload | High / continuous at interrogator | Instrument dependent | Small scientific payload |
| Maintenance | Low along passive fibre | Endpoint dependent | Selective and condition-based |
| Best use | Spatial phenomena | Precision endpoint | Specialised physical probe |
Lightweight, identifiable, retrievable, relocatable and reusable where practical. Large permanent multi-sensor stations require explicit research justification.
Normal operation sends periodic summaries. An event may trigger a compact payload. Target battery life is subject to sampling profile, sensor load, RF conditions and field validation.
Timestamped storage, sequence numbers, retry limits, duplicate detection, last-known-good state, watchdog, safe reboot, battery/sensor/communication state and calibration metadata are conceptual requirements.
Every autonomous pod must be registered in the same geospatial system as the fibre route so point measurements can be related to distributed events, terrain, canopy and time.
DSM, DTM and CHM remain derived spatial products. A pod is a time-aware asset overlay, not evidence that a live operational Digital Twin already exists.
Digital Surface Model from canopy and surface returns.
Derived terrain model from filtered ground returns where available.
Derived canopy height model, commonly DSM minus DTM.
pod_idsensor_typeresearch_programdeployment_setsensing_modezonelatitudelongitudeelevationdeployment_dateplanned_retrieval_datebattery_statelast_seencommunication_statesensor_healthcalibration_versionfirmware_versiondata_completenessretrieval_statusPossible means architecturally available for evaluation. It does not mean approved, mandatory or validated at every location.
| Capability | Set A | Set B | Set C |
|---|---|---|---|
| Distributed fibre sensing | Primary | Primary | Primary |
| Fibre endpoint sensing | Possible | Research-defined | Precision endpoint |
| Autonomous point sensing | Selective candidate | Possible where validated | Research-defined |
| LoRa required | No | No | No |
| Battery instrument possible | Conditional | Candidate | Possible |
| Human calibration | Reference visits | Research-defined | Primary role |
| Retrieval method | Corridor campaign | Autonomous target / human fallback | Human-assisted |
| Research-specific probe | Exceptional | Where justified | Where justified |
LoRa is not assigned to a fibre channel. The six-fibre baseline remains unchanged; autonomous pods are independent scientific instruments.
DTS along the corridor. Interpretation requires compatible fibre, optical budget, calibration and environmental context.
Instrument count does not equal research count. This library separates measurement principle, mode, power, communication, calibration, maintenance, maturity and limitation.
Temperature-related fibre response vs chainage/time
Distributed mechanical response
Distributed strain-related response
Optical strain / temperature at terminal points
Research-defined optical endpoint signal
Air temperature
Relative humidity
Photosynthetically active radiation
Incoming solar radiation
Ultraviolet exposure
Atmospheric pressure
Wind vector
Rainfall amount / intensity
Surface wetness
Tilt / acceleration
Local acoustic waveform
Volumetric or method-specific soil water
Soil temperature
Soil electrical conductivity
Soil pH
Soil oxygen concentration
Soil redox potential
Soil CO2 concentration
Soil CO2 flux
Water pressure / level
Pore-water pressure
Water temperature
Stage / water level
Water velocity
Turbidity
Water pH
Conductivity / TDS proxy
Dissolved oxygen
Water redox potential
Sap-flow proxy / tree water transport
Stem diameter change
Leaf surface temperature
Georeferenced point cloud
Georeferenced imagery / surface model
Surface thermal imagery
An autonomous pod supplies one variable among many. It does not replace fibre or UAV context.
LoRa is not forced into the catalogue. Programmes remain separated into fibre, endpoint, autonomous point, hybrid, remote-sensing and no-additional-hardware modes.
NeuralOps is an analysis layer, not an LLM behind every sensor. Deterministic validation, immutable raw data and traceable transformations come first.
RF, battery, calibration, fouling, enclosure, retrieval and ecological impact must be tested. Satellite / NTN remains not yet validated.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
Candidate requirement; define pilot method and acceptance criteria before deployment.
| Test | Measurement | Pass Condition | Decision |
|---|---|---|---|
| RF | Packet / link performance | Pilot-defined | GO / MODIFY / STOP |
| Battery | Consumption profile | Research-cycle viability | GO / MODIFY / STOP |
| Enclosure | Moisture / corrosion | Stable | GO / MODIFY / STOP |
| Scientific | Measurement value | Unique useful data | GO / MODIFY / STOP |
| Retrieval | Recovery success | Acceptable | GO / MODIFY / STOP |
| Ecology | Physical impact | Within approved threshold | GO / MODIFY / STOP |
Dashboard states: ONLINE, NO RECENT DATA, LOW BATTERY, SENSOR FAULT, COMMUNICATION DEGRADED, CALIBRATION DUE, RETRIEVAL DUE, RETRIEVED and LOST / UNRECOVERED.
No zero-maintenance claim is made.
Benefits: sparse deployment, no new terrestrial gateway network, reduced repeated entry, reusable/retrievable instruments and low-duty-cycle operation.
Costs: batteries, electronics, enclosure material, possible lost pod, retrieval activity and wildlife interaction.
Any future use is conditional on canopy attenuation, terrain shadowing, link-budget analysis, commercial service availability, regulatory approval and field validation. Coverage is not guaranteed.
The Do-Not-Deploy Principle prevents electronics from being added merely because they are available.
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