Home → Blog

You need to prove your cold-chain stayed within temperature limits, who handled it when, and why a late delivery still met Good Distribution Practice (GDP) rules. By the end of this post, you’ll be able to stitch your own temperature sensor/webhook events together with FreightPulse logistics intelligence—getting real-time natural-disruption alerts around ports, chain-of-custody verification via carrier lookups, and audit-ready compliance reports backed by consistent fuel and congestion context.

Introduction

Cold-chain integrity doesn’t live in a single system. Temperature telemetry streams in from IoT devices. Custody handoffs happen as carriers change at the cross-dock. External risk—cyclones, earthquakes, and severe weather—can derail a lane before you can react. The problem: each data source has its own format, its own refresh cadence, and usually its own integration work.

In this guide, we’ll show how to use FreightPulse as the logistics backbone for your cold-chain integrity monitor. You’ll pair your temperature events with FreightPulse’s single REST API for disruption alerts, carrier verification (FMCSA/FMC), and port congestion context (IMF PortWatch). You’ll also pull fuel-price series for surcharge calculations—all in one JSON schema without stitching five vendors together.

The outcome is a developer-first pattern you can drop into your existing shipment tracker: webhook in your temperature readings, fetch risk signals around the relevant port radius, validate the carrier at each handoff, attach congestion and fuel snapshots for your compliance PDF, and push real-time notifications when risk exceeds thresholds.

Why FreightPulse

Quick Start

Base URL: https://freightpulsehq.com/api/v1

Authentication: send X-API-Key: YOUR_API_KEY. Unauthenticated requests are allowed up to 100/day per IP, useful for initial tests. All responses share this shape:

{
"success": true,
"data": { ... }
// or on error:
// "success": false,
// "error": "Human-readable message."
}

First request: check for high-severity natural disruptions near the Port of Los Angeles (useful when a refrigerated shipment is arriving via transload).

curl -H "X-API-Key: YOUR_API_KEY" "https://freightpulsehq.com/api/v1/disruptions?port=USLAX&severity=high"

Illustrative JSON (values may vary):

{
"success": true,
"data": {
"results": [
{
"id": "gdacs:TC:1001305",
"type": "cyclone",
"severity": "moderate",
"title": "Tropical Cyclone SAUDEL-26",
"country": "Japan",
"starts_at": "2026-08-18T12:00:00+00:00",
"source": "GDACS"
}
]
}
}

Field highlights you’ll actually use:

Python example: alert enrichment on disruptions

import requests
import datetime

API = "https://freightpulsehq.com/api/v1/disruptions"
headers = {"X-API-Key": "YOUR_API_KEY"}

params = {
"port": "USLAX", # filter by port radius; 100 km for US weather
"severity": "high"
}

r = requests.get(API, headers=headers, params=params, timeout=10)
payload = r.json()

if payload.get("success") and payload.get("data", {}).get("results"):
for event in payload["data"]["results"]:
evt_type = event["type"]
severity = event["severity"]
title = event["title"]
starts_at = event["starts_at"]
print(f"[{starts_at}] {severity.upper()} {evt_type}: {title}")
else:
print("No high-severity disruptions near the port.")

Core Endpoints

1) Natural Disruptions near ports: GET /disruptions

Use this to preempt temperature excursions caused by external hazards—like severe weather stopping reefers at a terminal or delaying a handoff. You can filter by hazard type, severity, country, or port radius.

Endpoint: /disruptions

Key params:

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/disruptions?port=USLAX&type=severe_weather"

Sample JSON (illustrative):

{
"success": true,
"data": {
"results": [
{
"id": "noaa:WX:12345",
"type": "severe_weather",
"severity": "moderate",
"title": "High wind advisory near LA Basin",
"country": "United States",
"starts_at": "2026-08-20T06:00:00+00:00",
"source": "NOAA/NWS"
}
]
}
}

How to use it in your monitor:

2) Carrier verification for custody events: GET /carriers

When custody changes hands, validate the carrier’s identity and safety profile before accepting responsibility. This helps close compliance gaps in GDP and 21 CFR Part 11-aligned SOPs.

Endpoint: /carriers

Key params:

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/carriers?q=54283"

Example JSON (from FMCSA SAFER data):

{
"success": true,
"data": {
"type": "trucking",
"query": "54283",
"results": [
{
"dot_number": 54283,
"legal_name": "SWIFT TRANSPORTATION COMPANY OF ARIZONA LLC",
"status": "active",
"safety_rating": "S",
"drivers": 12883,
"address": {
"city": "Phoenix",
"state": "AZ",
"country": "US"
}
}
]
}
}

Field notes:

3) Port congestion context for ETA risk: GET /port-congestion

Cold-chain temperature is tightly coupled to time-in-transit. While you don’t need live AIS for many workflows, you do want a consistent congestion proxy for audits and planning. FreightPulse approximates congestion via IMF PortWatch AIS data using a 7-day average of port calls versus a 90-day baseline. Note: this data is lagged by about 6–7 days and is not real-time.

Endpoint: /port-congestion

Key params:

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/port-congestion?port=USLAX"

Example JSON:

{
"success": true,
"data": {
"results": [
{
"port": "Los Angeles-Long Beach",
"locode": "US LAX",
"country": "United States",
"congestion": "moderate",
"as_of": "2026-08-14",
"metrics": {
"recent_avg_portcalls_per_day": 8.7,
"baseline_avg_portcalls_per_day": 10.2,
"ratio_vs_baseline": 0.85
}
}
]
}
}

Operational use:

4) Fuel price snapshots for surcharge math: GET /fuel-prices

Cold-chain shipments often carry fuel-linked surcharges. You’ll want a consistent snapshot to include in your invoice or compliance appendix.

Endpoint: /fuel-prices

Params: none (national and PADD breakdowns are returned in one call).

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/fuel-prices"

Example JSON:

{
"success": true,
"data": {
"timestamp": "2026-07-30T12:00:00Z",
"source": "EIA (U.S. Energy Information Administration)",
"currency": "USD",
"unit": "gallon",
"data": {
"diesel": {
"national_average": 3.847,
"change_week": -0.023,
"change_percent": -0.6,
"regions": {
"east_coast": 3.912,
"midwest": 3.756,
"gulf_coast": 3.623,
"rocky_mountain": 3.891,
"west_coast": 4.456,
"california": 4.892
},
"historical": {
"30d_avg": 3.82,
"90d_avg": 3.75,
"yoy_change_percent": -8.2
}
},
"gasoline": {
"national_average": 3.156,
"historical": {
"30d_avg": 3.1,
"90d_avg": 3.05,
"yoy_change_percent": 1.1
}
}
}
}
}

What to store:

Real-World Use Cases

Putting It Together: Event Flow Blueprint

Here’s a simple event-driven pattern you can deploy inside your existing shipment tracker or TMS module:

  1. Webhook: Your IoT device sends temperature readings. When temp exceeds threshold, create an “excursion candidate” event.
  2. Context fetch: Call /disruptions?port=... to capture any overlapping natural hazards. If present and severity is moderate or high, flag a probable external cause.
  3. Custody check: On pickup/delivery scans, call /carriers?q=... to verify the carrier. Store legal_name, dot_number, status, and safety_rating on the custody timeline.
  4. Dwell risk: Pull /port-congestion for the relevant port to annotate risk. Remember that congestion is lagged (~6–7 days) and represents a 7-day average vs a 90-day baseline.
  5. Financials: Request /fuel-prices once per week (or per invoice run) and cache the result; attach the timestamped diesel.national_average to your surcharge calculation and PDF.
  6. Notify: If excursion + hazard overlap occurs, send a real-time notification with the disruption title and starts_at in UTC. Include carrier status at handoff time.
  7. Report: For the compliance report, compile temperature series (from your device), FreightPulse disruption evidence, carrier verification snapshots, and congestion/fuel context.

Error Handling and Practical Details

Optional: Live trucking rates for backup routing

If a hazard overlaps your pickup window and you need a contingency plan, you can get a US FTL quote inline. This is outside cold-chain telemetry but valuable for operator UX when re-planning a lane.

Endpoint: /freight-rates

Key params (trucking mode): origin_zip and destination_zip (required), optional pickup_date, qty, total_weight_lb.

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/freight-rates?mode=trucking&origin_zip=10001&destination_zip=90210"

Example JSON:

{
"success": true,
"data": {
"mode": "trucking",
"service": "FTL (53' dry van)",
"source": "Warp",
"price_usd": 7207.92,
"transit_days": 4,
"pickup_date": "2026-08-24",
"delivery_date": "2026-08-28"
}
}

Blend this with your temperature and disruption context to recommend an alternate pickup window or fallback carrier when risk is high.

End-to-End Example: Enrich a Temperature Excursion

Scenario: A pharma shipment’s sensor reports 9.2°C at a Los Angeles transload. Your app executes:

  1. GET /disruptions?port=USLAX&severity=high to see if a severe hazard overlaps the event window.
  2. GET /carriers?q=DOT_NUMBER from the scanned BOL to verify the current carrier is active and record its legal_name and safety_rating.
  3. GET /port-congestion?port=USLAX to annotate delay risk (keep in mind the 6–7 day lag and 7-day vs 90-day comparison).
  4. GET /fuel-prices to snapshot diesel.national_average for your FSC entry.

The alert payload your on-call sees includes: the temperature spike details, the disruption title and starts_at, carrier legal_name/status, congestion ratio_vs_baseline with as_of, and the current diesel national average. Your post-incident report cites each FreightPulse response alongside the raw sensor series you already store.

FAQ

How often do FreightPulse fuel prices update?

Fuel prices come from EIA and are returned with a timestamp field. Cache them for weekly billing or reporting cycles and reference the timestamp in your surcharge logic.

Can I look up ocean carriers as well as trucking carriers?

Yes. Use /carriers with type=ocean and q set to the FMC organization number or carrier name. Air lookups return available:false.

Does the port congestion data reflect real-time vessel wait times?

No. FreightPulse uses IMF PortWatch AIS data to provide a lagged proxy: a 7-day average of port calls versus a 90-day baseline, typically 6–7 days delayed. It’s ideal for planning and investigations, not minute-by-minute berth ETA decisions.

Can I filter natural-disruption alerts to only those near a specific port?

Yes. Pass port=LOCODE (e.g., USLAX). Events are filtered by distance around the port (300 km, and 100 km for US weather) so you get relevant alerts for shipments tied to that terminal.

What response shape should I code against across endpoints?

All endpoints return {"success":true,"data":{...}} on success and {"success":false,"error":"..."} on failure. Program against this wrapper and then parse the data payload for each endpoint’s fields.

Conclusion + CTA

Cold-chain integrity requires more than just temperature streams—you need verifiable custody events, risk awareness around ports, and consistent context for audits. With FreightPulse, you call a single REST API to enrich your sensor timeline with disruption alerts, carrier verification, fuel snapshots, and congestion trend context. Start with a few endpoints, wire them into your alerting and reports, and iterate from there. Try FreightPulse for free and ship your first integrated cold-chain monitor today.