IoT-Based Cold Chain in Agri-Logistics Market Size, Share & Trends Analysis Distribution by Type (Hardware [Sensors, GPS Trackers, Data Loggers, RFID Devices, Controllers], Services [Installation & Integration, Consulting Services, Maintenance & Support], and Software [Cloud-Based Cold Chain Platforms, Monitoring & Analytics Platforms, Predictive Maintenance Software, Fleet Management Software]), Deployment, Technology, Application, End-user, and Segment Forecasts, 2025-2034

Report Id: 3177 Pages: 180 Last Updated: 01 September 2025 Format: PDF / PPT / Excel / Power BI
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Segmentation of IoT-Based Cold Chain in Agri-Logistics Market -

IoT-Based Cold Chain in Agri-Logistics Market by Type-

·       Hardware

o   Sensors

o   GPS Trackers

o   Data Loggers

o   RFID Devices

o   Controllers

·       Services

o   Installation & Integration

o   Consulting Services

o   Maintenance & Support

·       Software

o   Cloud-Based Cold Chain Platforms

o   Monitoring & Analytics Platforms

o   Predictive Maintenance Software

o   Fleet Management Software

IoT-Based Cold Chain in Agri-Logistics Market SEGMENT

IoT-Based Cold Chain in Agri-Logistics Market by Deployment -

·       Cloud-Based

·       On-Premise

IoT-Based Cold Chain in Agri-Logistics Market by Technology-

·       Wi-Fi

·       RFID & Sensors

·       GPS

·       Zigbee

·       Bluetooth

·       NB-loT & LoRaWAN

IoT-Based Cold Chain in Agri-Logistics Market by Application-

·       Grains & Cereals

·       Fruits & Vegetables

·       Meat & Seafood

·       Dairy Products

·       Flowers & Plants

·       Processed Foods

IoT-Based Cold Chain in Agri-Logistics Market by End-user-

·       Farmers & Growers

·       Retailers

·       Food Processors

·       Logistics Providers

·       Government & Regulatory Bodies

IoT-Based Cold Chain in Agri-Logistics Market by Region-

North America-

·       The US

·       Canada

Europe-

·       Germany

·       The UK

·       France

·       Italy

·       Spain

·       Rest of Europe

Asia-Pacific-

·       China

·       Japan

·       India

·       South Korea

·       Southeast Asia

·       Rest of Asia Pacific

Latin America-

·       Brazil

·       Argentina

·       Mexico

·       Rest of Latin America

 Middle East & Africa-

·       GCC Countries

·       South Africa

·       Rest of the Middle East and Africa

Chapter 1.    Methodology and Scope

1.1.    Research Methodology
1.2.    Research Scope & Assumptions

Chapter 2.    Executive Summary

Chapter 3.    Global IoT-Based Cold Chain in Agri-Logistics Market Snapshot

Chapter 4.    Global IoT-Based Cold Chain in Agri-Logistics Market Variables, Trends & Scope

4.1.    Market Segmentation & Scope
4.2.    Drivers
4.3.    Challenges
4.4.    Trends 
4.5.    Investment and Funding Analysis 
4.6.    Porter's Five Forces Analysis
4.7.    Incremental Opportunity Analysis (US$ MN), 2025-2034 
4.8.    Competitive Landscape & Market Share Analysis, By Key Player (2024)
4.9.    Use/impact of AI on IoT-Based Cold Chain in Agri-Logistics Market Industry Trends 
4.10.    Global IoT-Based Cold Chain in Agri-Logistics Market Penetration & Growth Prospect Mapping (US$ Mn), 2024-2034

Chapter 5.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 1: By Type, Estimates & Trend Analysis

5.1.    Market Share by Type, 2024 & 2034
5.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Type:

5.2.1.    Hardware

5.2.1.1.    Sensors
5.2.1.2.    RFID Devices
5.2.1.3.    Data Loggers
5.2.1.4.    Controllers
5.2.1.5.    GPS Trackers

5.2.2.    Software

5.2.2.1.    Monitoring & Analytics Platforms
5.2.2.2.    Fleet Management Software
5.2.2.3.    Predictive Maintenance Software
5.2.2.4.    Cloud-Based Cold Chain Platforms

5.2.3.    Services

5.2.3.1.    Installation & Integration
5.2.3.2.    Maintenance & Support
5.2.3.3.    Consulting Services

Chapter 6.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 2: By End-User, Estimates & Trend Analysis

6.1.    Market Share by End-User, 2024 & 2034
6.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following End-User:

6.2.1.    Farmers & Growers
6.2.2.    Logistics Providers
6.2.3.    Food Processors
6.2.4.    Retailers
6.2.5.    Government & Regulatory Bodies

Chapter 7.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 3: By Application, Estimates & Trend Analysis

7.1.    Market Share by Application, 2024 & 2034
7.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Application:

7.2.1.    Fruits & Vegetables
7.2.2.    Dairy Products
7.2.3.    Meat & Seafood
7.2.4.    Grains & Cereals
7.2.5.    Flowers & Plants
7.2.6.    Processed Foods

Chapter 8.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 4: By Deployment Mode, Estimates & Trend Analysis

8.1.    Market Share by Deployment Mode, 2024 & 2034

8.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Deployment Mode:

8.2.1.    On-Premise
8.2.2.    Cloud-Based

Chapter 9.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 5: By Technology, Estimates & Trend Analysis

9.1.    Market Share by Technology, 2024 & 2034
9.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Technology:

9.2.1.    RFID & Sensors
9.2.2.    GPS
9.2.3.    Wi-Fi
9.2.4.    Bluetooth
9.2.5.    Zigbee
9.2.6.    NB-IoT & LoRaWAN

Chapter 10.    IoT-Based Cold Chain in Agri-Logistics Market Segmentation 6: Regional Estimates & Trend Analysis

10.1.    Global IoT-Based Cold Chain in Agri-Logistics Market, Regional Snapshot 2024 & 2034

10.2.    North America

10.2.1.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

10.2.1.1.    US
10.2.1.2.    Canada

10.2.2.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
10.2.3.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
10.2.4.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.2.5.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
10.2.6.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
10.2.7.    North America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

10.3.    Europe

10.3.1.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

10.3.1.1.    Germany
10.3.1.2.    U.K.
10.3.1.3.    France
10.3.1.4.    Italy
10.3.1.5.    Spain
10.3.1.6.    Rest of Europe

10.3.2.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
10.3.3.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
10.3.4.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.3.5.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
10.3.6.    Europe IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

10.4.    Asia Pacific

10.4.1.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

10.4.1.1.    India 
10.4.1.2.    China
10.4.1.3.    Japan
10.4.1.4.    Australia
10.4.1.5.    South Korea
10.4.1.6.    Hong Kong
10.4.1.7.    Southeast Asia
10.4.1.8.    Rest of Asia Pacific

10.4.2.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
10.4.3.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
10.4.4.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.4.5.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
10.4.6.    Asia Pacific IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

10.5.    Latin America

10.5.1.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

10.5.1.1.    Brazil
10.5.1.2.    Mexico
10.5.1.3.    Rest of Latin America

10.5.2.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
10.5.3.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
10.5.4.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.5.5.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
10.5.6.    Latin America IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

10.6.    Middle East & Africa 

10.6.1.    Middle East & Africa Wind Turbine Rotor Blade Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034

10.6.1.1.    GCC Countries
10.6.1.2.    Israel
10.6.1.3.    South Africa
10.6.1.4.    Rest of Middle East and Africa

10.6.2.    Middle East & Africa IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
10.6.3.    Middle East & Africa IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
10.6.4.    Middle East & Africa IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.6.5.    Middle East & Africa IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
10.6.6.    Middle East & Africa IoT-Based Cold Chain in Agri-Logistics Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

Chapter 11.    Competitive Landscape

11.1.    Major Mergers and Acquisitions/Strategic Alliances
11.2.    Company Profiles

11.2.1.    TeleSense
11.2.1.1.    Business Overview
11.2.1.2.    Key Type/Service Overview
11.2.1.3.    Financial Performance
11.2.1.4.    Geographical Presence
11.2.1.5.    Recent Developments with Business Strategy
11.2.2.    ColdStream Technologies
11.2.3.    Lineage Logistics
11.2.4.    Orbcomm
11.2.5.    Sensitech
11.2.6.    Zest Labs
11.2.7.    Americold
11.2.8.    ThermoConnect
11.2.9.    Maersk
11.2.10.    Carrier Global
11.2.11.    DigiCold
11.2.12.    AgroMerchant
11.2.13.    FreshTrack
11.2.14.    Honeywell
11.2.15.    Emerson Electric
11.2.16.    SmartCold
11.2.17.    Infratab
11.2.18.    Monnit
11.2.19.    Controlant
11.2.20.    vTrack Cold Chain  

Research Design and Approach

This study employed a multi-step, mixed-method research approach that integrates:

  • Secondary research
  • Primary research
  • Data triangulation
  • Hybrid top-down and bottom-up modelling
  • Forecasting and scenario analysis

This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.

Secondary Research

Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.

Sources Consulted

Secondary data for the market study was gathered from multiple credible sources, including:

  • Government databases, regulatory bodies, and public institutions
  • International organizations (WHO, OECD, IMF, World Bank, etc.)
  • Commercial and paid databases
  • Industry associations, trade publications, and technical journals
  • Company annual reports, investor presentations, press releases, and SEC filings
  • Academic research papers, patents, and scientific literature
  • Previous market research publications and syndicated reports

These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.

Secondary Research

Primary Research

Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.

Stakeholders Interviewed

Primary interviews for this study involved:

  • Manufacturers and suppliers in the market value chain
  • Distributors, channel partners, and integrators
  • End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
  • Industry experts, technology specialists, consultants, and regulatory professionals
  • Senior executives (CEOs, CTOs, VPs, Directors) and product managers

Interview Process

Interviews were conducted via:

  • Structured and semi-structured questionnaires
  • Telephonic and video interactions
  • Email correspondences
  • Expert consultation sessions

Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.

Data Processing, Normalization, and Validation

All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.

The data validation process included:

  • Standardization of units (currency conversions, volume units, inflation adjustments)
  • Cross-verification of data points across multiple secondary sources
  • Normalization of inconsistent datasets
  • Identification and resolution of data gaps
  • Outlier detection and removal through algorithmic and manual checks
  • Plausibility and coherence checks across segments and geographies

This ensured that the dataset used for modelling was clean, robust, and reliable.

Market Size Estimation and Data Triangulation

Bottom-Up Approach

The bottom-up approach involved aggregating segment-level data, such as:

  • Company revenues
  • Product-level sales
  • Installed base/usage volumes
  • Adoption and penetration rates
  • Pricing analysis

This method was primarily used when detailed micro-level market data were available.

Bottom Up Approach

Top-Down Approach

The top-down approach used macro-level indicators:

  • Parent market benchmarks
  • Global/regional industry trends
  • Economic indicators (GDP, demographics, spending patterns)
  • Penetration and usage ratios

This approach was used for segments where granular data were limited or inconsistent.

Hybrid Triangulation Approach

To ensure accuracy, a triangulated hybrid model was used. This included:

  • Reconciling top-down and bottom-up estimates
  • Cross-checking revenues, volumes, and pricing assumptions
  • Incorporating expert insights to validate segment splits and adoption rates

This multi-angle validation yielded the final market size.

Forecasting Framework and Scenario Modelling

Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.

Forecasting Methods

  • Time-series modelling
  • S-curve and diffusion models (for emerging technologies)
  • Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
  • Price elasticity models
  • Market maturity and lifecycle-based projections

Scenario Analysis

Given inherent uncertainties, three scenarios were constructed:

  • Base-Case Scenario: Expected trajectory under current conditions
  • Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
  • Conservative Scenario: Slow adoption, regulatory delays, economic constraints

Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.

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Frequently Asked Questions

The IoT-Based Cold Chain in Agri-Logistics Market Size is valued at US$ 18.5 Bn in 2024 and is predicted to reach US$ 149.9 Bn by the year 2034 at an 23.9% CAGR over the forecast period.

The major players in the IoT-Based Cold Chain in Agri-Logistics market are ColdStream Technologies, Sensitech, TeleSense, Zest Labs, Americold, ThermoConnect, Maersk, DigiCold, SmartCold, Infratab, Honeywell, AgroMerchant, FreshTrack, Emerson Electric, Monnit, Controlant, Carrier Global, Lineage Logistics, Orbcomm, and vTrack Cold Chain.

The primary IoT-Based Cold Chain in Agri-Logistics market segments are Type, Deployment, Technology, Application, and End-user.

North America leads the market for IoT-Based Cold Chain in Agri-Logistics because of sophisticated infrastructure and stringent laws pertaining to food safety.

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