Agriculture Machine To Machine M2m Market
Agriculture Machine to Machine (M2M) Market Forecasts to 2030 - Global Analysis By Solution Type (Hardware, Software and Services), Agriculture Type, Technology, Application and By Geography
According to Stratistics MRC, the Global Agriculture Machine to Machine (M2M) Market is accounted for $3.84 billion in 2024 and is expected to reach $6.83 billion by 2030 growing at a CAGR of 10.07% during the forecast period. Enabling automated data interchange between agricultural machinery, devices, and management systems without the need for human interaction is the target of the agriculture machine-to-machine (M2M) market. Through real-time monitoring of crop health, soil conditions, irrigation, and animal management, M2M technology in agriculture increases production by leveraging IoT sensors, wireless connectivity, and data analytics.
According to a three-year plan jointly released by ten government entities in July 2021, China plans to develop 560 million 5G mobile customers by the end of 2023 and increase the penetration rate of fast wireless technology among large industrial firms to 35%. By the end of 2023, China hopes to have reached a 40 percent penetration rate of 5G among individual consumers, with 5G data making up more than half of all online traffic.
Market Dynamics:
Driver:
Growing demand for precision agriculture
Precision farming is becoming more and more popular, which is driving the agriculture machine-to-machine (M2M) market as farmers look for data-driven methods to increase output and maximize resource utilization. M2M technology supports accurate decision-making and effective farm management by enabling real-time monitoring of crop health, soil conditions, and water usage. This technology aids in waste reduction, cost reduction, and yield maximization—all of which are essential for satisfying the growing demand for food. The adoption of M2M-enabled precision agriculture systems is also encouraged by environmental advantages, such as reduced pesticide use.
Restraint:
Complexity and technical knowledge requirement
Adoption of Agriculture Machine-to-Machine (M2M) systems is severely hampered by their complexity and technical requirements, particularly for farmers with limited familiarity with technology. Without specialized training, maintaining networked sensors, data analytics, and real-time monitoring tools can be difficult in M2M systems. Higher operating expenses result from this complexity, which frequently calls for more assistance with system setup, maintenance, and data interpretation. The technological requirements and learning curve may discourage smaller farms from investing in M2M technology, which would impede the expansion of the market as a whole.
Opportunity:
Rise in IoT and sensor technology
Smarter, more effective farm operations are made possible by the growth of IoT and sensor technologies, which is a key factor driving the agriculture machine-to-machine (M2M) market. Real-time data on animals, crops, weather, and soil moisture is collected by sophisticated sensors and used by M2M systems to automate procedures and maximize resource utilization. This connection lowers the need for labour, cuts down on waste, and improves yield forecasts. Farmers are gaining more accurate insights as a result of continuous IoT improvements, which make M2M solutions more widely available, efficient, and crucial to contemporary agriculture.
Threat:
Lack of standardization
Significant difficulties arise from the agriculture machine-to-machine (M2M) market's lack of standardization, especially when it comes to data integration and device compatibility. The employment of different communication protocols by different manufacturers makes it challenging for equipment from several suppliers to function together flawlessly. Due to the possibility of requiring additional middleware or customized solutions for compatibility, this fragmentation can make system setup more difficult, raise costs, and result in inefficiencies. The entire potential of linked, data-driven farming is limited in the absence of standardized frameworks, which impede the general use of M2M technology in agriculture.
Covid-19 Impact
The COVID-19 pandemic had a major impact on the agriculture machine-to-machine (M2M) business by delaying the adoption of new technology and upsetting supply networks. Adoption of M2M solutions, which are essential for efficiency and precision farming, was difficult for many agricultural businesses due to personnel shortages and movement constraints. But the crisis also made the need for digital transformation in agriculture more urgent, leading farmers to investigate automation and remote monitoring technology. As the industry adapts to the new operating realities, this change is anticipated to propel long-term growth in the M2M sector.
The hardware segment is expected to be the largest during the forecast period
The hardware segment is estimated to be the largest, due to increasing demand for precision agriculture enables farmers to optimize crop yields and resource use through real-time data analysis. Rising labour costs push the adoption of automation technologies, reducing dependency on manual labour. Additionally, advancements in sensor technology and connectivity solutions enhance operational efficiency and facilitate remote monitoring. Government initiatives promoting smart farming practices further support this growth, making M2M solutions essential for modern agricultural practices.
The precision farming segment is expected to have the highest CAGR during the forecast period
The precision farming segment is anticipated to witness the highest CAGR during the forecast period, due to the developments in sensor technology, which offer up-to-date information on environmental variables, crop health, and soil conditions. Data-driven decision-making is further supported by the combination of artificial intelligence and machine learning, which enables prompt crop management actions. Additionally, the use of precision farming techniques that support effective agricultural operations is pushed by growing global food demand and sustainability concerns.
Region with largest share:
Asia Pacific is expected to have the largest market share during the forecast period due to rapid population expansion, increased food demand, and growing consciousness of environmentally friendly agricultural methods. M2M adoption is accelerated by the region's governments' backing of smart farming and precision agricultural efforts aimed at increasing production and resource efficiency. Furthermore, real-time monitoring in a variety of agricultural contexts is made possible by developments in IoT and communication infrastructure.
Region with highest CAGR:
North America is projected to witness the highest CAGR over the forecast period, owing to technological developments, the necessity for effective resource management in the face of growing operating expenses, and the strong demand for precision agriculture. The region's robust communication infrastructure facilitates the broad use of M2M solutions, allowing for data-driven decision-making and real-time monitoring. M2M investment is also encouraged by government programs and incentives that support water conservation and sustainable farming. The adoption of automation in North American agriculture is further fuelled by the existence of significant agricultural technology businesses and growing manpower shortages.
Key players in the market
Some of the key players profiled in the Agriculture Machine to Machine (M2M) Market include John Deere, Trimble Inc., AGCO Corporation, CNH Industrial, Yara International ASA, Kubota Corporation, Hexagon Agriculture, AG Leader Technology, Raven Industries, Digi International, Telit Communications, Orange Business Services, Vodafone Group Plc, Cisco Systems Inc., AT&T Inc., Siemens AG.
Key Developments:
In October 2024, John Deere announced an expansion to its Agriculture & Turf training center and field site near Orlando, Florida. This investment advances the company's commitment to customer success through the support of John Deere's world-class dealer channel.
In January 2023, AGCO Autonomous Tractor introduced an autonomous tractor equipped with M2M technology for precision farming applications.
In March 2021, Trimble Ag Software Update launched a cloud-based platform update that enhances data analysis and visualization for precision agriculture.
Solution Types Covered:
• Hardware
• Software
• Services
Agriculture Types Covered:
• Aquaculture
• Arable Farming
• Horticulture
• Livestock Farming
Technologies Covered:
• Cellular M2M
• Short-Range
• Satellite M2M
• Wired
• Low-Power Wide Area Networks
• Other Technologies
Applications Covered:
• Precision Farming
• Livestock Monitoring
• Fish Farming
• Smart Greenhouses
• Soil Monitoring
• Inventory and Equipment Management
• Crop Monitoring
• Remote Sensing & Imaging
• Supply Chain & Logistics
• Other Applications
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 Emerging Markets
3.9 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Agriculture Machine to Machine (M2M) Market, By Solution Type
5.1 Introduction
5.2 Hardware
5.3 Software
5.4 Services
6 Global Agriculture Machine to Machine (M2M) Market, By Agriculture Type
6.1 Introduction
6.2 Aquaculture
6.3 Arable Farming
6.4 Horticulture
6.5 Livestock Farming
7 Global Agriculture Machine to Machine (M2M) Market, By Technology
7.1 Introduction
7.2 Cellular M2M
7.3 Short-Range
7.4 Satellite M2M
7.5 Wired
7.6 Low-Power Wide Area Networks
7.7 Other Technologies
8 Global Agriculture Machine to Machine (M2M) Market, By Application
8.1 Introduction
8.2 Precision Farming
8.3 Livestock Monitoring
8.4 Fish Farming
8.5 Smart Greenhouses
8.6 Soil Monitoring
8.7 Inventory and Equipment Management
8.8 Crop Monitoring
8.9 Remote Sensing & Imaging
8.10 Supply Chain & Logistics
8.11 Other Applications
9 Global Agriculture Machine to Machine (M2M) Market, By Geography
9.1 Introduction
9.2 North America
9.2.1 US
9.2.2 Canada
9.2.3 Mexico
9.3 Europe
9.3.1 Germany
9.3.2 UK
9.3.3 Italy
9.3.4 France
9.3.5 Spain
9.3.6 Rest of Europe
9.4 Asia Pacific
9.4.1 Japan
9.4.2 China
9.4.3 India
9.4.4 Australia
9.4.5 New Zealand
9.4.6 South Korea
9.4.7 Rest of Asia Pacific
9.5 South America
9.5.1 Argentina
9.5.2 Brazil
9.5.3 Chile
9.5.4 Rest of South America
9.6 Middle East & Africa
9.6.1 Saudi Arabia
9.6.2 UAE
9.6.3 Qatar
9.6.4 South Africa
9.6.5 Rest of Middle East & Africa
10 Key Developments
10.1 Agreements, Partnerships, Collaborations and Joint Ventures
10.2 Acquisitions & Mergers
10.3 New Product Launch
10.4 Expansions
10.5 Other Key Strategies
11 Company Profiling
11.1 John Deere
11.2 Trimble Inc.
11.3 AGCO Corporation
11.4 CNH Industrial
11.5 Yara International ASA
11.6 Kubota Corporation
11.7 Hexagon Agriculture
11.8 AG Leader Technology
11.9 Raven Industries
11.10 Digi International
11.11 Telit Communications
11.12 Orange Business Services
11.13 Vodafone Group Plc
11.14 Cisco Systems Inc.
11.15 AT&T Inc.
11.16 Siemens AG
List of Tables
1 Global Agriculture Machine to Machine (M2M) Market Outlook, By Region (2022-2030) ($MN)
2 Global Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
3 Global Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
4 Global Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
5 Global Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
6 Global Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
7 Global Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
8 Global Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
9 Global Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
10 Global Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
11 Global Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
12 Global Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
13 Global Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
14 Global Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
15 Global Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
16 Global Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
17 Global Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
18 Global Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
19 Global Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
20 Global Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
21 Global Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
22 Global Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
23 Global Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
24 Global Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
25 Global Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
26 Global Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
27 Global Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
28 Global Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
29 North America Agriculture Machine to Machine (M2M) Market Outlook, By Country (2022-2030) ($MN)
30 North America Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
31 North America Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
32 North America Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
33 North America Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
34 North America Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
35 North America Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
36 North America Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
37 North America Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
38 North America Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
39 North America Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
40 North America Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
41 North America Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
42 North America Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
43 North America Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
44 North America Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
45 North America Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
46 North America Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
47 North America Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
48 North America Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
49 North America Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
50 North America Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
51 North America Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
52 North America Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
53 North America Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
54 North America Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
55 North America Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
56 North America Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
57 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Country (2022-2030) ($MN)
58 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
59 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
60 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
61 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
62 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
63 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
64 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
65 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
66 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
67 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
68 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
69 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
70 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
71 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
72 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
73 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
74 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
75 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
76 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
77 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
78 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
79 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
80 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
81 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
82 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
83 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
84 Europe Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
85 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Country (2022-2030) ($MN)
86 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
87 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
88 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
89 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
90 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
91 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
92 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
93 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
94 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
95 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
96 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
97 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
98 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
99 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
100 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
101 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
102 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
103 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
104 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
105 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
106 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
107 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
108 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
109 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
110 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
111 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
112 Asia Pacific Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
113 South America Agriculture Machine to Machine (M2M) Market Outlook, By Country (2022-2030) ($MN)
114 South America Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
115 South America Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
116 South America Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
117 South America Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
118 South America Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
119 South America Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
120 South America Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
121 South America Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
122 South America Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
123 South America Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
124 South America Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
125 South America Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
126 South America Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
127 South America Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
128 South America Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
129 South America Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
130 South America Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
131 South America Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
132 South America Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
133 South America Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
134 South America Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
135 South America Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
136 South America Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
137 South America Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
138 South America Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
139 South America Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
140 South America Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
141 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Country (2022-2030) ($MN)
142 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Solution Type (2022-2030) ($MN)
143 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Hardware (2022-2030) ($MN)
144 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Software (2022-2030) ($MN)
145 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Services (2022-2030) ($MN)
146 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Agriculture Type (2022-2030) ($MN)
147 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Aquaculture (2022-2030) ($MN)
148 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Arable Farming (2022-2030) ($MN)
149 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Horticulture (2022-2030) ($MN)
150 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Farming (2022-2030) ($MN)
151 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Technology (2022-2030) ($MN)
152 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Cellular M2M (2022-2030) ($MN)
153 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Short-Range (2022-2030) ($MN)
154 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Satellite M2M (2022-2030) ($MN)
155 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Wired (2022-2030) ($MN)
156 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Low-Power Wide Area Networks (2022-2030) ($MN)
157 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Other Technologies (2022-2030) ($MN)
158 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Application (2022-2030) ($MN)
159 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Precision Farming (2022-2030) ($MN)
160 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
161 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Fish Farming (2022-2030) ($MN)
162 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
163 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Soil Monitoring (2022-2030) ($MN)
164 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Inventory and Equipment Management (2022-2030) ($MN)
165 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Crop Monitoring (2022-2030) ($MN)
166 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Remote Sensing & Imaging (2022-2030) ($MN)
167 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Supply Chain & Logistics (2022-2030) ($MN)
168 Middle East & Africa Agriculture Machine to Machine (M2M) Market Outlook, By Other Applications (2022-2030) ($MN)
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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