DEV Community: Smrati

Storing IoT time-series data: InfluxDB vs TimescaleDB for asset tracking

Smrati — Fri, 08 May 2026 11:21:35 +0000

Millions of data points per day in your asset tracking solution? Location logs, sensor readings, status messages – all generate millions. The way you store your data influences dashboard performance, querying capabilities, and even your infrastructure bill. Check out which of the two below can help you make the right choice.

Two options

InfluxDB

Custom-built time-series database
A completely new database optimized to handle time-series workloads. Own query language, own storage engine, own everything – specifically tailored to writing a lot of data.

Built from scratch
Query language – Flux
TSM engine

TimescaleDB

PostgreSQL time-series extension
A PostgreSQL database extension with hypertables and built-in time-series optimization features. SQL support – all your joins, foreign keys and other advanced SQL stuff.

PostgreSQL based
SQL support
Hypertables

Asset location data writing — InfluxDB

InfluxDB utilizes the line protocol for its writing operations — small, quick, and built to handle a massive number of devices all streaming at once:

// Writing to InfluxDB v2 using the JS client
const { InfluxDB, Point } = require('@influxdata/influxdb-client')

const client = new InfluxDB({
  url: 'http://localhost:8086',
  token: process.env.INFLUX_TOKEN
})
const writeApi = client.getWriteApi('myorg', 'asset-tracking')

// Write a location + sensor reading point
const point = new Point('asset_location')
  .tag('asset_id', 'truck-01')
  .tag('fleet', 'north-region')
  .floatField('lat', 43.6532)
  .floatField('lng', -79.3832)
  .floatField('speed_kmh', 62.4)
  .floatField('temp_c', 4.2)
  .timestamp(new Date())

writeApi.writePoint(point)
await writeApi.flush()

Asset location data writing — TimescaleDB

TimescaleDB makes use of traditional SQL insert statements on a hypertable — familiar territory for any PostgreSQL developer. The partitioning and compression are handled seamlessly behind the scenes:

-- Create hypertable (run once)
CREATE TABLE asset_locations (
  time       TIMESTAMPTZ      NOT NULL,
  asset_id   TEXT            NOT NULL,
  lat        DOUBLE PRECISION,
  lng        DOUBLE PRECISION,
  speed_kmh  DOUBLE PRECISION,
  temp_c     DOUBLE PRECISION
);

SELECT create_hypertable('asset_locations', 'time');

-- Insert a reading (standard SQL)
INSERT INTO asset_locations
  (time, asset_id, lat, lng, speed_kmh, temp_c)
VALUES
  (NOW(), 'truck-01', 43.6532, -79.3832, 62.4, 4.2);

Querying — that's where the rubber meets the road

Both databases excel at querying a range of times but differ when trying to relate the asset data with your business environment. Here is the same query — "average speed by asset for the past 24 hours" — in both:

// InfluxDB — Flux query
from(bucket: "asset-tracking")
  |> range(start: -24h)
  |> filter(fn: (r) => r._measurement == "asset_location")
  |> filter(fn: (r) => r._field == "speed_kmh")
  |> group(columns: ["asset_id"])
  |> mean()

-- TimescaleDB — standard SQL
SELECT
  asset_id,
  AVG(speed_kmh) AS avg_speed,
  time_bucket('1 hour', time) AS bucket
FROM asset_locations
WHERE time > NOW() - INTERVAL '24 hours'
GROUP BY asset_id, bucket
ORDER BY bucket DESC;

Head-to-head comparison

Criteria	InfluxDB	TimescaleDB
Write throughput	Extremely high (better)	High (with tuning)
Query language	Flux (learning curve)	Full SQL (better)
Relational joins	Not supported	Full JOIN support (better)
Compression	Automatic (TSM) (better)	Manual policy setup
Retention policies	Built-in, simple (better)	Via PostgreSQL jobs
Ecosystem / tooling	Grafana native	Full PostgreSQL ecosystem (better)
Existing PostgreSQL stack	Separate system	Drop-in extension (better)
Operational complexity	Medium	Low (if you know Postgres) (better)

Tip on compression for TimescaleDB:
Activate column-level compression for chunks older than 7 days – IoT data compresses by 90-95% using the default compression policy in TimescaleDB. A 100GB raw database is typically reduced to less than 8GB. Configure it once and forget about it: SELECT add_compression_policy('asset_locations', INTERVAL '7 days');

Asset tracking-specific requirement – joining
This is where TimescaleDB shines over almost any other asset tracking solution. Your time-series data is not an island and needs to be joined with other asset data, such as metadata, asset fleet membership, geofencing details, and maintenance history. This is a single SQL command in TimescaleDB:

-- Join location data with asset metadata — trivial in TimescaleDB
SELECT
  a.asset_id,
  a.vehicle_type,
  a.assigned_driver,
  AVG(l.speed_kmh) AS avg_speed,
  MAX(l.temp_c) AS max_temp
FROM asset_locations l
JOIN assets a ON l.asset_id = a.asset_id
WHERE l.time > NOW() - INTERVAL '1 hour'
  AND a.fleet = 'north-region'
GROUP BY a.asset_id, a.vehicle_type, a.assigned_driver;

However, InfluxDB requires two separate systems to pull data from and join the results at the application level. Works, but not as efficiently as TimescaleDB.

Quick decisions chart
IoT ingest only, highest write speeds → InfluxDB
Grafana, basic time range queries → InfluxDB
PostgreSQL already up and running → TimescaleDB
Joining assets to metadata, maintenance, users → TimescaleDB
Complex analytics, reports, SQL knowledge → TimescaleDB
Large scale, metrics-only ingestion without relations → InfluxDB

Most asset tracking applications need to combine location information with other types of data like asset metadata, geofencing conditions, and maintenance records. For such use cases, TimescaleDB should be used. Pure telemetry ingestion pipelines, without any need for relational features, will find InfluxDB more suitable because of its throughput.

AssetTrackPro's platform has built-in support for time series ingestion, storage, and querying at scale, so you won't have to build your own database layer from the ground up. Check out our platform →

Are you developing an IoT data pipeline? Then let us do the work for you – we provide a scalable asset telemetry backend so that you can focus on your core functionality.
Explore AssetTrackPro

IoT protocols for asset tracking: MQTT vs HTTP vs CoAP — what to use when

Smrati — Thu, 07 May 2026 14:22:09 +0000

Choosing an unsuitable protocol in an asset tracking stack does not lead to immediate failure but to massive failures. There will be higher latencies, shorter than expected battery life, and even the message broker might be unable to handle thousands of concurrent connections.
The following is the right choice criterion.

Overview of three protocols

MQTT

Message Queuing Telemetry Transport
Pub/sub over TCP. Designed for unreliable networks and constrained devices. There is a broker that mediates communication between publisher and subscriber; peer-to-peer communication is never used.

Pub/Sub properties
Based on TCP
Persistent connections

HTTP

Hypertext Transfer Protocol
Client-server request/response mechanism over TCP. In HTTP, each device establishes a connection, sends the data, waits for a response and closes the connection. High level of compatibility allows communication to happen everywhere.

Req/Response features
Stateless
Universal application

CoAP

Constrained Application Protocol
HTTP semantics over UDP. Created especially for IoT constrained devices with low latency, multicast abilities, and an observe option for asynchronous delivery of messages.

UDP based
Lightweight
Multicast

MQTT vs HTTP vs CoAP

Criteria	MQTT	HTTP	CoAP
Transport	TCP	TCP	UDP (lightest)
Overhead	2 byte header (wins)	~800 byte headers	4 byte header
Connection	Persistent (wins)	Per-request	Connectionless
Battery impact	Low	High	Lowest (wins)
Reliability	QoS 0/1/2 (wins)	TCP guaranteed	Optional ACK
Scalability	High (broker fans out) (wins)	Medium	High (multicast)
Ecosystem	Strong IoT support	Universal (wins)	Niche IoT only
Firewall-friendly	Port 1883/8883	Port 80/443 (wins)	Port 5683 (UDP)

MQTT

: location update publication
The use of an ongoing connection means that the handshaking process per each message is no longer relevant, which makes it very effective in cases when thousands of tags report their location every few seconds.

const mqtt = require('mqtt')
const client = mqtt.connect('mqtts://broker.assettrackpro.com', {
  clientId: 'asset-tag-7821',
  username: 'device',
  password: process.env.MQTT_TOKEN,
  clean: false,                 // persist session across reconnects
  reconnectPeriod: 1000
})

// Publish with QoS 1 — at least once delivery
client.publish(
  'assets/7821/location',
  JSON.stringify({ lat: 43.65, lng: -79.38, ts: Date.now() }),
  { qos: 1, retain: false }
)

HTTP

: simplicity beats efficiency
If the update interval is quite long (every five minutes or even longer), if the backend system is built on REST architecture, or if the updates have to go through firewalls which do not allow access to nonstandard ports, then HTTP may be preferred. While the overhead is significant, it becomes reasonable in low update frequency cases.

// Simple HTTP POST — works everywhere, no broker needed
await fetch('https://api.assettrackpro.com/v1/location', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${TOKEN}`
  },
  body: JSON.stringify({
    assetId: '7821',
    lat: 43.65, lng: -79.38,
    ts: new Date().toISOString()
  })
})

CoAP

: when low power consumption comes first
CoAP, being based on UDP, does not require connection setup and skips roundtrips inherent to TCP connections. In case the tag consumes energy from a battery designed to function for decades with one charge and updates location every fifteen minutes, then the number of transmitted bytes could make a difference in terms of extended functionality. The next code sample shows an example of CoAP POST with node-coap module.

const coap = require('coap')

const req = coap.request({
  hostname: 'coap.assettrackpro.com',
  pathname: '/location',
  method: 'POST',
  confirmable: true      // CON message — expects ACK
})

req.write(JSON.stringify({
  id: '7821', lat: 43.65, lng: -79.38
}))

req.on('response', res => console.log(res.code))
req.end()

QoS recommendations for MQTT messages

QoS level 0 works well for high frequency location pings if some data loss is acceptable (position updates every five seconds with acceptable loss of one message).
QoS 1 can be used to send alerts, breach messages, and other events for which the delivery of every message is crucial.
QoS 2 (Exactly Once) will rarely be necessary for asset tracking purposes.

Protocol to be Selected for a Particular Situation: An Empirical Decision Approach

The following decision model highlights how different communication protocols can be assigned to certain applications. According to empirical observations, the following protocol assignments take place:

Large amounts of data to be updated within thousands of devices: MQTT
Real-time dashboard applications and alerts: MQTT
Limited pinging through firewall: HTTP
Back-end API integration and fast interoperability: HTTP
Extremely low power consumption with decades-long battery lifespans: CoAP
Restricted environments with low RAM in microcontrollers: CoAP

For practical asset tracking stacks, usually, MQTT is used for devices' communications, whereas HTTP interfaces are created for integrations with other services and systems. As far as CoAP is concerned, it still plays a rather specialized role and proves extremely useful when focusing on the maximum possible battery lifespan in the case of LoRaWAN or NB-IoT.

Empirical evidence suggests that AssetTrackPro allows devices to send their data through MQTT, HTTP, and CoAP.
Learn More about AssetTrackPro↗

NB-IoT vs LoRaWAN for industrial asset tracking: a technical breakdown

Smrati — Wed, 06 May 2026 17:56:55 +0000

NB-IoT and LoRaWAN networks have been built for the deployment of IoT applications requiring low power consumption and wide coverage area. While on the face of it both technologies address the same need, opting for the wrong technology for your use case can result in insufficient coverage, high power consumption, and unexpected costs.

NB-IoT
Narrowband IoT
Cellular technology standard (3GPP) operating in licensed spectrum, using the same infrastructure as your current 4G or 5G connection. Deployed by carriers such as Verizon, AT&T, Vodafone. You will be charged per unit per month.
Licensed spectrum
Managed by carriers

LoRaWAN
Long Range Wide Area Network
Protocol operating in unlicensed ISM bands (868MHz EU, 915MHz US). You can set up your own gateways or rely on a shared network such as The Things Network. No carrier charges per device.
Unlicensed spectrum
Deploy independently

Direct head-to-head technical comparison

Criteria	NB-IoT	LoRaWAN
Coverage	Carrier network (roaming across the globe) (better)	Self-deployed or community network
Downlink support	Bidirectional capability (better)	Class A/B/C restrictions
Data throughput	~200kbps (better)	0.3 to 50kbps
Latency	Time of 1 to 10 seconds (better)	Time of 2 to 30+ seconds
Battery lifetime	2 to 5 years	5 to 10+ years (better)
Cost of the network	Pay per device per SIM card	Gateway capex only (better)
Indoor penetration	Good	Excellent (better)
Deployment control	Carrier-dependent	Full control (better)

LoRaWAN uplink payload structure
LoRaWAN uplinks are purposely small, usually less than 51 bytes per uplink. An example of an asset tracking payload that fits in this limit is:

// Encode asset tracking data into minimal bytes
// lat/lng as int32 (÷1e6), temp as int16 (÷100), battery as uint8

function encodePayload(lat, lng, tempC, batteryPct) {
  const buf = Buffer.alloc(11)
  buf.writeInt32BE(Math.round(lat * 1e6), 0)  // 4 bytes
  buf.writeInt32BE(Math.round(lng * 1e6), 4)  // 4 bytes
  buf.writeInt16BE(Math.round(tempC * 100), 8) // 2 bytes
  buf.writeUInt8(batteryPct, 10)            // 1 byte
  return buf
}

// Total: 11 bytes — well under LoRaWAN's 51-byte SF7 limit

Registration of NB-IoT devices with AT commands
The following command set can be used on NB-IoT modules for device attachment and sending an uplink:

// Attach to NB-IoT network and send a UDP packet
AT+CFUN=1                   // full functionality mode
AT+CEREG=1                  // enable network registration URC
AT+CGDCONT=1,"IP","nbiot.apn" // set APN
AT+CGACT=1,1               // activate PDP context

// Open UDP socket and send payload
AT+CSOC=1,2,1               // create UDP socket
AT+CSOCON=0,"your-server.io",5683
AT+CSOSEND=0,0,"AABBCCDD..."  // send hex payload

Which to choose and when

NB-IoT

Fleet management
Cross-border assets requiring carrier roaming service

Frequent data transmission
Assets communicating every few minutes with two-way commands

Field asset tracking
Oil & gas and utility sectors with carrier network and no infrastructure requirements

LoRaWAN

Campus/Building
Static location, full control, no recurring carrier charges

10-year battery assets
Assets that infrequently move requiring decades of deployments

High density sensors
1,000+ sensors where SIM cards per device are unaffordable

*Dual radio hybrid tip: *

For assets that are mostly static on the campus but need transport from time to time, use a dual radio tag – LoRaWAN while inside (cheap, long battery) and NB-IoT once it exits the geofence (carrier network automatically activates).

The economics of scale

For small-scale deployments, the $2 per month SIM card cost for NB-IoT is not a factor. For 5,000 assets, the annual connectivity cost alone is $120,000. A LoRaWAN solution with 10 gateways could cost $15,000 initially and virtually nothing annually. The point of convergence, at which LoRaWAN becomes economically superior, is about 500 to 1,000 devices per site.

How to make a decision?

Moving assets over large geographical areas? Use NB-IoT.
Need two-way communication and OTA updates? Use NB-IoT.
Fixed site, more than 500 assets, budget considerations? Use LoRaWAN.
Require 10 years of battery life? Use LoRaWAN.
Devices that perform both functions? Hybrid tag radio

Both technologies are commercially available. AssetTrackPro provides NB-IoT and LoRaWAN asset tracking solutions for industrial applications, including hybrid tags for mixed environments.
Find out more about AssetTrackPro ↗

Cold chain monitoring: how multi-sensor IoT devices protect high-value assets

Smrati — Tue, 05 May 2026 16:56:00 +0000

Temperature alone isn’t enough. Your vaccine cargo could have stayed in range all the way to the destination, yet be compromised due to lack of monitoring of parameters such as humidity, shock or light. Here’s how IoT tracking devices help ensure end-to-end control by covering all bases.

Why single parameter monitoring is inadequate

Single parameter loggers typically monitor temperature only. This may be sufficient for simple food shipments. But in case of biologics, mRNA vaccines, blood products and precise pharmaceuticals, more than one condition affects integrity.

Even when your blood bag is kept at proper temperature levels, it can still be compromised due to shock from being constantly moved around. Even when you keep your insulin vial chilled but it is exposed to sunlight in a warehouse, it becomes ineffective.

The five sensors that matter

Temperature
Essential sensor for pharmaceuticals. Must record continuously at 30-60 second intervals for the entire trip.
Range: -80°C to +60°C

Humidity
Required for lyophilized products and packaging integrity.
Range: 0-100% Relative Humidity

Shock and vibration
Tracks accidental drops, bumps, and excessive vibration.
Threshold: adjustable G-forces

Light exposure
Triggers when a package is opened without authorization or exposed to UV radiation.
Measures lux and UV light range

GPS location
Links each sensor reading to an accurate GPS location — crucial for breach analysis.
Accuracy: 3-5 meters outdoors

Example of payload from multi-sensor cold chain tag

All data points collected from a well-designed cold chain tag should be part of the payload structure, including all sensor readings, location, and the breach flag:

{
  "assetId": "VIAL-7821-B",
  "ts": "2025-03-14T09:32:11Z",
  "sensors": {
    "tempC": 4.2,
    "humidityPct": 58.3,
    "shockG": 0.3,
    "lightLux": 0,
    "lat": 43.6532,
    "lng": -79.3832
  },
  "breach": false,
  "breachType": null
}

How a breach flag is calculated on the edge device
The breach flag must be calculated on the device itself prior to sending. Below is a simplified example of Node.js code for how this can be done:

function evaluateBreach(reading, thresholds) {
  const breaches = []

  if (reading.tempC > thresholds.maxTemp ||
      reading.tempC < thresholds.minTemp) {
    breaches.push('TEMPERATURE')
  }
  if (reading.humidityPct > thresholds.maxHumidity) {
    breaches.push('HUMIDITY')
  }
  if (reading.shockG > thresholds.maxShock) {
    breaches.push('SHOCK')
  }
  if (reading.lightLux > thresholds.maxLight) {
    breaches.push('LIGHT_EXPOSURE')
  }

  return {
    breach: breaches.length > 0,
    breachType: breaches[0] ?? null,
    allBreaches: breaches
  }
}

Warning Severity Matrix

Type of Breach	Severity	Action
Temperature excursion	Critical	Send immediate SMS + webhook + ship notification
Humidity breach	Critical	Send alert + hold shipment until investigation
Shock exceeded threshold	Moderate	Log event + contact receiving team
Light exposure detected	Moderate	Send alert to inspect on receipt
Route deviance from GPS path	Monitor	Log incident + contact logistics coordinator

Compliance tip:

To meet FDA 21 CFR Part 11 and EU GDP requirements, all readings must be timestamped with tamper-proof timestamps, and an unbroken chain of custody must be maintained in the logs. Design your data architecture such that records cannot be altered after being written; append-only database or blockchain anchoring can work here.
Connectivity options for cold chain tags
All cold chain environments aren’t always covered by reliable cellular networks. Select your connectivity based on the deployment:

Cellular (LTE-M / NB-IoT) - optimal when used for cold chain transportation over long distances and large geographies. Global coverage, near-real-time monitoring, moderate power consumption. BLE + Gateway - best option when you have fixed gateways in your warehouse/facilities. Lowest power consumption. LoRaWAN - best suited for remote cold storage and rural/distance-based distribution centers. Satellite (Iridium/Starlink) - backup connectivity for locations beyond the reach of terrestrial networks.

AssetTrackPro’s cold chain tags are equipped with multiple sensors to monitor temperature, humidity, shock, lighting, and location (GPS). Threshold configuration, breach alerts, and automatic compliance report generation are included. Cold chain deployments at various companies, including pharmaceuticals, hospitals, and blood banks. Learn more →

Building a cold chain monitoring system? AssetTrackPro's IoT devices cover every sensor that matters — with compliance reporting ready out of the box.
Explore AssetTrackPro ↗

How edge computing in smart tags reduces latency in asset monitoring

Smrati — Mon, 04 May 2026 17:04:48 +0000

Transmitting all data to the cloud seems like an easy task until you realize that the sensor network for your asset tracking system will have 10,000 nodes sending data at one-second intervals.
This is why moving processing to the tag itself makes such a difference when it comes to latency, bandwidth, and battery drain.

The issue with cloud-first IoT

The standard IoT approach is simple: read sensor data → send to the cloud → process it in the cloud → send out alert. Looks great on paper. Hard to implement.

Each step takes time. A round-trip trip from your tag to the cloud and back to decide whether the temperature of the asset is higher than 8°C could range from 200ms to 2 seconds. In cold chain logistics or on high-speed assembly lines, this is not "slow." This is a failure.

Cloud first vs edge first: how it plays out in reality

Cloud first (conventional)

All decisions go to the server
→Tag reads sensor
→Data is transmitted
→Processed in the cloud
→Warning sent back
→Response initiated
Latency: 200ms – 2 seconds

Edge first (smart tag)

Decisions occur on the tag
→Tag reads sensor
→Onboard computing executes
→Local alert is generated
→Summary is transmitted to cloud
→(only when there’s an exception)
Latency: <5ms

What "edge computing on a tag" really means

Today’s smart tags have onboard processors such as the Nordic nRF52 or STM32 family – low power ARM cores capable of processing decision-making locally. Here is what a basic threshold alert might look like in firmware:

// Runs on-chip — no cloud needed for this decision
void check_temperature() {
  float temp = read_sensor()
  if (temp > THRESHOLD_MAX) {
    trigger_local_alert()  // buzzer, LED, or BLE broadcast
    queue_cloud_event({
      type: "TEMP_BREACH",
      value: temp,
      ts: get_timestamp()
    })
  }
  // No breach? Nothing sent. Zero bandwidth used.
}

The crucial point is that exceptions are all that matter. An RFID sensor reading the temperature every 10 seconds in a 12-hour transport will send 4,320 readings. But if three of those 4,320 exceed the limit, you send 3 events – not 4,320. The savings in bandwidth will be 99.9%.

What edge computing makes possible

Sub-5 ms notification
Decisions made locally without the need to communicate with a distant server
Offline capability
RFID tags will continue functioning regardless of connection loss
Battery life extension x3-x5
Sending exceptions instead of entire streams means lower power consumption
Reduced bandwidth expenses
Savings on mobile network bandwidth or LoRaWAN

The tradeoffs you need to know

Factor	Edge compute	Cloud-first
Alert latency	<5ms	200ms–2s
Firmware complexity	Higher	Lower
OTA update risk	Logic lives on device	Update server only
Offline resilience	Full	None
Battery life	3–5× longer	Baseline
Data bandwidth	Up to 99% less	Full stream

OTA note: If logic runs on the tag, a firmware rollout gone wrong can render thousands of deployed tags useless. Make sure to implement a rollback partition and test on a staging group prior to rolling out edge logic updates to production tags.

Edge vs. Cloud - Where Logic Should Live

Use edge compute in the tag whenever you need: sub-second latency, assets operating in offline environments, or cost-effective bandwidth management on cell or LoRaWAN connections. Cold chain monitoring, manufacturing lines, remote facilities - all are good candidates.

Cloud-first is the way to go when you have: complex logic, frequently changing logic, or need to correlate data across several assets in order to compute (e.g., fleet-wide anomaly detection). Best-in-class systems combine both - edge for immediate decisions locally, cloud for analytics and insights.

Experience edge computing in action. AssetTrackPro’s intelligent tags leverage on-chip edge logic in cold chain, manufacturing, and logistics applications.
Learn about https://assettrackpro.com/↗

RTLS vs GPS: choosing the right location tech for indoor vs outdoor tracking

Smrati — Fri, 01 May 2026 07:17:07 +0000

GPS is universal – until you enter a building.
RTLS is great inside – until the asset exits through the front gate. Making the wrong choice is expensive, but it also jeopardises the precision your entire tracking solution relies upon.

What they actually are
GPS

Global Positioning System

A satellite-based positioning technology in which a GPS module embedded within a tracker uses satellite signals to pinpoint location. Needs direct visibility of satellites – walls, ceilings, and other dense materials interfere greatly with the signal.

Accuracy range of 3-5m outdoors
Satellite-dependent
RTLS

Real-Time Locating System

An indoor positioning infrastructure utilizing Bluetooth Low Energy (BLE), Ultra-Wideband (UWB), WiFi, or RFID anchors to locate assets through communication between tags and readers/anchors positioned throughout the building premises using RSSI, TDOA, and AoA algorithms.

Accuracy range of 10cm to 3m indoors
Infrastructure-dependent

Head-to-head comparison

Criteria	GPS	RTLS
Indoor accuracy	Poor (signal loss)	High (10cm–3m) _wins _
Outdoor accuracy	High (3–5m) wins	Not applicable
Infrastructure cost	Low (satellite-based) wins	Medium–High (anchor install)
Tag/device cost	$15–$80	$5–$50 (BLE) / $30–$150(UWB)
Battery life	Days–weeks	Months–years (BLE) wins
Update frequency	Every 5–60 sec	Near-continuous wins
Setup complexity	Low wins	High (site survey needed)

Usage for each technology

RTLS - indoor application

Hospitals
Intravenous infusion devices, wheelchairs, emergency medical kits in various floors
Warehouses
Forklifts, pallets, bins within huge warehouses
Manufacturing facilities
Work-in-progress inventory tracking in different manufacturing process stages

GPS - outdoor application

Fleet management
Trucks, vans, delivery trucks traveling on roads
Construction site
Heavy machinery used at open construction sites
Yard management
Cargo containers and trailers in open yards

The hybrid solution

– what the majority of enterprise implementations utilize
Logistical and manufacturing operations do not operate within environments where assets remain exclusively indoors or outdoors. A pallet moves out of a warehouse, is put into a vehicle, travels to a distribution facility, and then heads back indoors. No single technology will account for the entire journey.

The solution: Utilize GPS for the outdoor/travel segments, while relying on BLE-based RTLS for the indoor segments, with the transfer occurring automatically when the asset crosses into a geofenced area. This transition doesn’t require any changes to the tag; today’s hybrid tags can accommodate both technologies and automatically switch between them based on signal strength.

Deployment advice: Always conduct a site survey before installing any anchor points in an RTLS deployment. The multipath effect caused by metal racks, machinery, and concrete floors can reduce precision by 40%–60% if anchors are placed without taking into account the RF environment.

Choosing an RTLS technology for indoors

RTLS isn’t created equally. If precision is your priority, then UWB is best, delivering up to 10-30 cm precision. However, it will cost you more upfront with higher costs per tag and infrastructure setup. BLE provides a good balance between performance and budgeting, offering a range of 1-3 meters, affordable tags, extended battery life, and versatile gateways which can serve as general IoT infrastructure. Wi-Fi RTLS utilizes pre-existing network components; however, the accuracy is lower (3-10 meters) and consumes network resources heavily.

Decision-making

Outdoor/mobile assets → GPS
Indoor assets → RTLS (BLE/UWB)
Indoor and outdoor/mobile assets → hybrid GPS/BLE tag
Indoor sub-30cm precision → UWB

Check out RTLS and GPS in practice. AssetTrackPro specializes in designing hybrid indoor and outdoor asset tracking solutions using BLE, UWB, and GPS technologies for logistics, manufacturing, and healthcare.

Learn more about AssetTrackPro ↗

Building a Real-Time Asset Tracking Dashboard with IoT Data Streams

Smrati — Thu, 30 Apr 2026 17:13:25 +0000

Constructing a Real-Time Dashboard for IoT Asset Tracking Using Data Streams

In this day and age, real-time tracking of assets is no longer optional; this is something that keeps chaos at bay. And if your business involves tracking any assets ranging from laptops, warehouse stock to delivery fleets, then you need to utilize data streams provided by IoT to have a real-time view.

The Basic Concept

In essence, an IoT data stream-based real-time dashboard collects continuous streams of data from IoT-enabled assets and presents such in a useful and readable way. The type of data presented may include location, status, and even alerts depending on your requirements.
Basic Components

IoT Devices (Sources of Raw Data)

These are the hardware sources which are responsible for collecting raw data. This could be RFID tags, Bluetooth beacons, GPS receivers or other sensors that collect required information.

Data Collection (Ingestion) Layer

Use various tools that will collect data stream in real time, some of these tools may be MQTT brokers or other similar APIs. It is recommended to use MQTT since it is a light-weight protocol and perfect for IoT.

Data Stream Processing

This is where it really gets fun. You need to look into real time processing of data by software tools like Apache Kafka or Apache Flink. These types of tools allow you to filter out the information passing through them, to cleanse it and also to activate some kind of action such as sending alerts for assets that should not have left their location.

The Backend and Database

To save the structured data, you will want to use an actual database such as MongoDB (which gives you a lot of flexibility) or PostgreSQL. If you are monitoring something that changes over time, you can use a time series database like InfluxDB to store those data points.
The Frontend Dashboard
You will use either React, Vue, or plain JS to display the data you saved to the backend above. Some useful JavaScript libraries include Chart.js or D3.js for creating live graphs, maps or status indicators.

The Flow of Data

A piece of IoT hardware sends data → the IoT device connects to an MQTT broker which receives the data → a stream processor checks the data and runs analytics on the data stream → the backend saves the data for future retrieval → the dashboard showing the user the data updates in real time.
Ta-da! No delays or guess work.

Features that Matter

The Most Important Feature is Real Time Asset Location Tracking (being able to visually see the location of your assets on a map is essential).
Immediate Alert Notifications (alerts for theft, movement, or an anomalous condition).
Monitoring the Health of Your Assets.
Usage Analytics (who used what and when).
Don't just dump nothing into a systems - turn that nothing into value.

Don't over complicate your architecture at first. Start with something simple then build on that.
Latency is King - optimise your data pipeline for speed; this is a critical aspect of an IoT solution.
Security is Not Optional - be sure to encrypt your data and that users authenticate before accessing your solution.
Test Your Solution in Real-World Scenarios - not in a perfect setting.
Here's Where It Comes in Handy

Think about an organization dealing with dozens of assets scattered around different places. Rather than resorting to the chaos of Excel sheets and estimation, they can see everything right before their eyes. This is where solutions such as AssetTrackPro-like platforms make all the difference, organizing the chaos without burdening anyone.

Bottom Line

The moment your assets start moving, they need tracking. The moment you start tracking them, you need the data to be real-time. The moment it becomes real-time, you definitely need a useful dashboard.
Otherwise, what's the point?

See this in production. AssetTrackPro builds enterprise-grade IoT tracking systems with real-time dashboards for logistics, manufacturing, and healthcare.
Explore AssetTrackPro ↗

RFID vs BLE vs NFC: Which asset tracking tech should you build on?

Smrati — Wed, 29 Apr 2026 13:00:18 +0000

Selecting an improper radio technology can cost you several months of time spent on re-engineering the solution. So below we offer our recommendations on when to choose RFID, BLE, and NFC technologies in terms of asset tracking solutions.

RFID

Radio Frequency ID
Uses electromagnetic fields to auto-identify tags attached to objects. Passive tags need no battery — they draw power from the reader.

10cm–10m range
No battery needed

BLE

Bluetooth Low Energy
Broadcasts beacon signals continuously. Gateways or phones pick them up and triangulate position with RSSI. Low power, long battery life.

Up to 100m range
1–3 yr battery

NFC

Near Field Comm.
Short-range, tap-to-read protocol. Ideal for manual check-in/out workflows where a human physically scans an asset tag.

Under 10cm
Passive tags

Criteria	RFID	BLE	NFC
Read range	10cm – 10m	Up to 100m	<10cm
Tag cost	$0.10 – $2	$3 – $15	$0.10 – $1
Power source	Passive (reader-powered)	Battery (active)	Passive
Real-time location	Partial (gate-based)	Yes (continuous)	No
Infrastructure cost	Medium–High	Medium	Low
Best use case	Inventory gates, warehouses	Live location, large sites	Check-in/out workflows

Which technology to choose?

Choose RFID when you need to scan hundreds of things at once — be it conveyor belts, docking stations, or storerooms of any retail shop. UHF RFID readers can scan 200+ tags within a second. It's perfect for automated warehouses and other logistics centers.

Choose BLE when you need precise continuous localization across your facility — hospitals tracking devices, manufacturing companies controlling tools usage on multiple floors, logistics centers monitoring assets movement. Simply deploy BLE gateways with an interval of 10-30m, and you'll get your own indoor positioning system.

Choose NFC when you don't need continuous localization but want to have audit trails. Tool checkout operations, asset transfers between different shifts, logging some compliance activities — NFC tags are relatively inexpensive, tamper-proof, and don't require any infrastructure whatsoever except for smartphones.

Conclusion

Quick decision support
Scanning many objects at choke points → RFID
Tracking live objects in open spaces → BLE
No infrastructure budget for check-in/check-out → NFC

Want to see these technologies in action?
AssetTrackPro builds end-to-end RFID, BLE, and NFC tracking systems for logistics, manufacturing, and healthcare.

Why RFID-Based Asset Tracking is a Game-Changer for Growing Businesses

Smrati — Tue, 28 Apr 2026 13:35:05 +0000

The emergence of businesses is directly related to the increase in complexity of asset management. Managing laptops, machinery, inventory, and tools without an advanced system could lead to a nightmare. The introduction of the RFID system solves this problem.

What Is RFID & How It Works?

RFID involves placing tags on assets that will be scanned wirelessly by RFID scanners. In contrast to barcodes, RFID doesn't have any requirement of line-of-sight for asset tracking.
As an illustration, whereas it takes a lot of time to scan each product one-by-one, an RFID scanner allows scanning multiple products in just a few seconds.

Why Old Methods Aren't Effective

While some companies still use such methods in order to keep track of their assets, it is a solution that might help in the initial stage only.

This approach results in:
-Human mistakes
-Misplaced assets
-Tiresome auditing process
-No real-time asset tracking capabilities
Take the case of a company with 200+ employees attempting to track their laptops through Excel. One wrong digit and you'll spend days or even weeks looking for those laptops.

How Does RFID Change Everything?

Using RFID-based tracking of assets changes everything by making it completely automated and instant.

Instant Inventory Audits Businesses will now be able to perform audits almost instantly using RFID.
Instant Tracking Assets will be easily traceable in real-time, avoiding any cases of theft and loss.
More Precise Data Using automation will help minimize mistakes in data collection and reporting.
Better Decisions With better quality data, organizations will be capable of making sound decisions on assets.

Example of How It Works

Imagine a medium-sized company managing its office equipment. Without RFID, it experienced frequent issues with equipment loss and out-of-date records. Using RFID for asset tracking, it was able to avoid losses and save time while performing audits.
Products such as AssetTrackPro provide great assistance in this process, as they use RFID technology together with an effective platform for managing assets.

Why Growth-oriented Businesses Should Pay Attention

Growth creates opportunities, but chaos occurs when processes remain unoptimized. This is where RFID comes into play, enabling companies to maintain scalability, efficiency, and proper organization. Rather than spend unnecessary resources managing their assets, businesses could concentrate on more important aspects: growing and achieving higher performance.

Conclusion

Asset management using RFID technologies is no longer an option, but an urgent necessity for growth-oriented enterprises looking to develop effectively. The benefits of automation and process optimization cannot be overstated, and RFID makes that possible.

Still using outdated methods? Maybe it's time to reconsider.

Lost Assets = Lost Money: How RFID Fixes What Spreadsheets Can't

Smrati — Mon, 27 Apr 2026 14:03:09 +0000

Missing Assets = Missing Money: Why RFID Can Fix What Spreadsheets Cannot

Many companies use spreadsheets for asset management. Initially, it looks easy - just input all the data and keep updating it. But with growth comes complexity, and missing devices, stale data, and human error start becoming a problem.
Why? Because the moment you lack the ability to manage your assets effectively, you are missing out on profits.

The Problem With Spreadsheets

They are manual. They are prone to human error.
Think about an organization with 500 laptops, scattered across various departments. With every assignment, relocation, and repair, the spreadsheet has to be updated. Just visualize the amount of work involved daily.

Problems faced:

Human mistakes while entering data
No live updates
Slow auditing process
Lack of visibility regarding asset movement

As a business develops, its managers begin to face such problems as missing equipment, purchasing duplicates, and unneeded expenditures since the system fails to work properly.

What is RFID? How Does RFID Work?

This technology is based on tags and readers that help track assets automatically.
An RFID tag is attached to each asset. When scanned, it immediately registers information in the system, without any input.

Example:
A company's warehouse implements RFID technology to track their assets. There's no need for manual asset counting - just scan everything right away.

Why RFID is Revolutionary for Your Business

RFID helps solve all those spreadsheet-based problems we talked about earlier.

Real-Time Asset Updates Any changes are registered immediately after asset scanning.
Increased Accuracy Human errors become a thing of the past.
Improved Audit Processes An audit used to take a few hours; now it can be done in minutes.

Scenario in Real Life

Consider an example of asset management in a hospital, where they monitor medical equipment.
In spreadsheet-based systems, one may spend hours looking for particular pieces or order something that they already have.

By using RFID:
-Assets are monitored in real time
-Faster location of needed items
-Lower costs

This is where modern solutions kick in. Software such as AssetTrackPro utilizes RFID combined with intelligent dashboards to streamline asset management, without increasing its complexity.

Conclusion

A spreadsheet-based method may be used only in cases when there are not many assets to manage.
But with growing business comes greater number of assets, and therefore managing them requires proper software to avoid a complete mess. RFID helps automate the process and bring precision to it.
As the saying goes, every lost asset is lost money - and no sensible business allows that.

How RFID is Quietly Replacing Manual Asset Tracking (And Why Businesses Love It)

Smrati — Mon, 27 Apr 2026 12:44:21 +0000

What's Wrong with Manual Asset Tracking?

Let's be real - manual tracking sounds simple, but it breaks down fast.
Human errors (wrong entries, missed updates)

Time-consuming audits
No real-time visibility
Assets getting "lost" but actually just misplaced

Example:
Imagine a company with 500 laptops. Every time one is moved, someone has to update it manually. Miss one entry, and suddenly… no one knows where it is.

So, What Exactly is RFID?

RFID (Radio Frequency Identification) uses small tags attached to assets. These tags send signals to scanners, which automatically update the system.
No typing. No guessing. No chasing people for updates.
You just scan - and boom, the system knows what's where.

Why Businesses Are Switching to RFID?

This isn't just a tech upgrade - it's a relief.

Real-Time Tracking You always know where your assets are. Not yesterday. Not "last updated." Right now.
Faster Audits What used to take hours (or days) can now be done in minutes. Example: A warehouse can scan hundreds of items in seconds instead of checking them one by one.
Fewer Errors Since everything is automated, there's way less chance of mistakes.
Saves Money Lost assets = lost money. RFID cuts that problem down a lot. Enter the Need for Software Solutions Such As AssetTrackPro

But here's the kicker - the problem with RFID technology is that once you have the data, how do you manage it?
This is where software solutions such as AssetTrackPro come in behind the scenes. These software solutions take the raw RFID data and convert it into a format that can be analyzed and used to make decisions.

The Big Step: From Reactive Management to Smart Management
Manual systems are reactive; issues are sorted out after they occur.
But RFID changes that.
Problems can be prevented from occurring
Usage trends can be tracked
Planning is improved
Instead of asking where it went, you simply say that you already know.

Closing Notes
RFID is not very noticeable, but it sure makes a lot of difference for business asset management. It is more convenient and actually makes life much easier.
Once you've adopted RFID systems in your company, switching back to manual tracking is like returning to the use of flip phones in 2026.

Not difficult, but why would you want to?

Why Spreadsheets Fail For Asset Management

Smrati — Sat, 25 Apr 2026 12:40:00 +0000

In many companies, using spreadsheets had been considered the primary solution to asset management for decades. Such tools are cheap, available, easy to use. It might seem that using spreadsheets could be effective and beneficial at first sight. But as businesses continue to grow and evolve, there comes a realization that spreadsheets may be far from being a viable solution to any asset tracking problems.

No Real-Time Updates

One of the major disadvantages of using spreadsheets is that they lack real-time accuracy. Asset tracking data changes regularly when items move to a new location, undergo some repairs, replacements, get assigned to different staff members. With the help of a spreadsheet system, all of these events would require human input to update information. Even the slightest delay may make asset information invalid since asset tracking data gets modified very frequently.

High Probability of Human Errors

Spreadsheet software is highly susceptible to human error due to its nature. Any mistakes, such as accidentally deleting rows, changing cells, or even misplacing files, can cause serious harm to a business. Spreadsheets lack the advanced validation features and automation tools that would make them less dependent on human intervention.

Inadequate Scalability

As businesses expand, so do their requirements for managing a greater number of assets. Spreadsheets cannot effectively accommodate large quantities of information. It becomes difficult to track numerous assets spread across various locations, especially with the growing file sizes that slow down operations. Solutions that work well for a smaller organization do not scale up to accommodate larger organizations.

Poor Collaboration and Security

While collaborative tools make it possible for multiple people to use the same file in the cloud, there is still no effective way to collaborate. There may be conflicts due to simultaneous editing, or sensitive information may get lost when different people edit the file simultaneously. Moreover, spreadsheets do not offer security measures, so there is always a risk of leaks and data loss.

Absence of Automation and Insights

Efficiency is enhanced by automation and insights. However, spreadsheet software does not offer any form of automation. It depends on the manual entry and verification of information in order to get accurate results. No alert or asset life cycle system is available. On the other hand, there are tools that automate and simplify all such tasks easily. For example, AssetTrackPro helps organizations manage their resources efficiently with automatic monitoring systems.

Ineffective Auditing and Report Generation

Spreadsheets cannot facilitate effective auditing of assets because it is a laborious process involving many errors. The task becomes complex when one needs to verify the spreadsheet information against the actual asset data. Similarly, report generation becomes an arduous job in case of such software.

Although spreadsheets could be considered an easy place to begin when it comes to asset management, they do not possess capabilities that suit the requirements of current businesses. Inaccurate, inefficient, insecure, and manual, spreadsheets cannot become a viable option in the future. For businesses to keep up with their growth and development, it is vital for them to move from spreadsheet-based asset management to more modern systems.