Road Fleet Management: 297 million devices providing vehicle and driver monitoring by 2033

Internet of Things
IoT
Hyperconnectivity
Connected Vehicles
GPS Tracking
Telematics
Logistics
Supply Chain
Fleet Management
Sustainability
Vehicle Gateway
Fuel Management
Driver Safety
Tyre Pressure Monitoring
Driver Safety
Onboard Diagnostics
OBD II
ELD
Electronic Logging Device

Rohan Bansal
Matt Arnott
Suruchi Dhingra

This report provides Transforma Insights’ view on the Road Fleet Management market with a primary focus on Vehicle Telematics Devices. Road Fleet Management covers in-vehicle transportation logistics solutions including job allocation, vehicle tracking, vehicle and driver monitoring, maintenance planning, safety compliance, fuel management, and incident management. The segment also includes aftermarket Tire Pressure Monitoring Systems, In-cab Displays, and Electronic Logging Devices. Early examples of Road Fleet Management offered excellent return on investment, a situation that has been widely recognised within many industries resulting in widespread adoption. Fleet telematics providers frequently advertise fuel savings, lower mileage, reduced maintenance costs, and lower idle time as the main benefits of deploying these solutions. The report provides a detailed definition of the sector, analysis of market development and profiles of the key vendors in the space. It also provides a summary of the status of adoption and Transforma Insights’ ten-year forecasts for the market. The forecasts include analysis of the number of IoT connections by geography, the technologies used (including splits by 2G, 3G, 4G, 5G, LPWA, short range, satellite, and others), as well as the revenue split between module, value-added connectivity, and services. A full set of forecast data, including country-level forecasts, sector breakdowns and public/private network splits, is available through the IoT Forecast tool.

Accenture
Avanade
Daimler Trucks
Dohrn Transfer
Federal Motor Carrier Safety Administration
Fleetboard
Fleet Complete
Ford
GeoTab
GoFleet
GPS Insight
Hino
John Deere
Linfox
Microsoft
Mullen Automotive
Omnitracs
Platform Science
PT Serasi Autoraya
Samsara
Samsung
Savage
Telstra
Trimble Transportation
Tyrewatch
Verizon Communications
Volvo
Werner Enterprises
West Yorkshire Police

Internet of Things
Hyperconnectivity

Agriculture, Forestry & Fishing
Construction
Mining & Quarrying
Transportation & Storage

Smart Lockers: 6.2 million connected lockers in 2033 to ensure streamlined and secure parcel deliveries

Internet of Things
IoT
commercial lockers
delivery lockers
gym lockers
hospital lockers
last mile delivery
locker stations
locker towers
residential lockers
smart lockers
parcel delivery
post
mail

Rohan Bansal
Matt Arnott

This report provides Transforma Insights’ view on the Smart Lockers market. Parcel deliveries have grown significantly over the years, and between 2014 and 2022, the volume of deliveries quadrupled. There is an increasing demand from customers for next-day or same-day deliveries which puts businesses under extreme pressure to expedite their last-mile processes. Parcel locker stations are being introduced to tackle last-mile delivery problems, especially in remote areas where daily deliveries are difficult. The growing need for parcel lockers has led to an increase in the need to connect these lockers to monitor them remotely and manage their efficiency. Lockers are equipped with a variety of communications technologies to ease their usage. Many functions use RFID tags or biometric scanners (such as fingerprint or face recognition). Short Range technologies such as Bluetooth and NFC, and long-range technologies such as LPWA and cellular are used to connect to the cloud. Many lockers can be operated via a smartphone application using Wi-Fi or Bluetooth connectivity. The report provides a detailed definition of the sector, analysis of market development and profiles of the key vendors in the space. It also provides a summary of the current status of adoption and Transforma Insights’ ten-year forecasts for the market. The forecasts include analysis of the number of IoT connections by geography, the technologies used (including splits by 2G, 3G, 4G, 5G, LPWA, short range, satellite, and others), as well as the revenue split between module, value-added connectivity, and services. A full set of forecast data, including country-level forecasts, sector break-downs and public/private network splits, is available through the IoT Forecast tool.

Air Locker
Aituo
Blu
Click n Collect
Deutsche Post DHL
DPDGroup
Fonzel
Groundfloor Delivery
GS Parcel
InPost
KEBA
LockTec
Nærboks
Parcel Pending by Quadient
Pick Network
Posti
Posten
PostNord
Qikpod
QLOCX iBoxen Digital
Singapore Post
Sunway PopBox
SwipBox
Warehouse in a Box

Hyperconnectivity
Internet of Things

Transportation & Storage

GE Digital: Digital Transformation capabilities assessment

Internet of Things
Artificial Intelligence
Hyperconnectivity
Human Machine Interface
Data Sharing
Autonomous Robotic Systems
Distributed Ledger
Edge Computing
Robotic Process Automation
Generative AI
Connected Products

Suruchi Dhingra

This report examines the capabilities of GE Digital in Digital Transformation. It provides a comprehensive review of the products, services, and capabilities of GE Digital across 11 technology areas and dozens of functions, to determine its core strengths for meeting enterprise needs. The 11 technology families in which the vendor’s capabilities are assessed are IoT, Hyperconnectivity, Human Machine Interface, Artificial Intelligence, Distributed Ledger, Data Sharing, Product Lifecycle Management, Robotic Process Automation, Edge Computing, Autonomous Robotic Systems, and 3D Printing & Additive Manufacturing. While these might not encompass every possible technology that organisations might need in order to pursue a Digital Transformation, they certainly represent the most disruptive, and therefore the ones of which enterprises should be most aware. The report includes rating across each of the technology areas and functional capabilities (specialised hardware, general hardware, software products, integrated solutions, application development, systems integration and project management, specialist services, field & operational services) using Transforma Insight’s four-level universal rating system for vendors in Digital Transformation. Internet of Things, for instance, spans hardware, software, application development, implementation, field services and specialist services. For each of the 92 combinations of function and technology, GE Digital is rated for whether its capabilities are ‘Emerging’, ‘Significant’ or ‘Market Leading’ (or ‘None’). This rating is based on both the credibility of the solution and the position of the offering in the market (e.g. market share).

GE Digital

Electric Vehicle Charging: 449 million connections in 2033, generating USD13 billion in revenue

Wi-Fi
Bluetooth
Cellular
4G
Ethernet
Electric Vehicles
EVs
EV Charging
Charging Stations
Public Charging
Private Charging

Rohan Bansal
Matt Arnott

This report provides Transforma Insights’ view on the connected EV Charging market. This segment is comprised of public and private EV chargers, including those installed at all kinds of commercial and residential establishments. Drivers are quickly switching from traditional fuel-powered vehicles to hybrids and EVs. Governments around the globe are playing a key role in aiding this switch by providing incentives to drivers for switching to EVs. The growing demand for EVs has led to the need for sufficient charging infrastructure to be in place to charge these EVs. Chargers are also increasingly being connected. Typically, this is to provide drivers with remote functionalities to decide the time and charge amount of their vehicles in the case of private chargers and allow remote monitoring and maintenance or dynamic pricing for public chargers. The report provides a detailed definition of the sector, analysis of market development and profiles of the key vendors in the space. It also provides a summary of the status of adoption and Transforma Insights’ ten-year forecasts for the market. The forecasts include analysis of the number of IoT connections by geography, the technologies used (including splits by 2G, 3G, 4G, 5G, LPWA, short range, satellite, and others), as well as the revenue split between module, value-added connectivity, and services. A full set of forecast data, including country-level forecasts, sector breakdowns and public/private network splits, is available through the IoT Forecast tool.

ABB
Audi
BMW
ChargePoint
Co Charger
EDF
Elektromotive
EnelX
EVmatch
EV Box
EvoCharge
Gireve
Hive Home
Hubject
Lightsource Labs
Mahindra Racing
NewMotion
Opel
Plugsurfing
Sirreta
Virta
Volkswagen
Wallbox Chargers
Wave

Internet of Things
Hyperconnectivity

Electricity, Gas, Steam & A/C
Transportation & Storage
Consumer

Grid Operations: 151 million connected devices in 2033 across electricity, gas, and water

Internet of Things
IoT
Hyperconnectivity
Big Data
Electricity Grid
Energy
Gas Grid
Microgrid
Predictive Analytics
Renewable Energy
Substation
Smart Grid
Sustainability
Transmission and Distribution
T&D
Utilities
Utility Provider
Water Grid

Rohan Bansal
Matt Arnott
Nikita Singh

This report provides Transforma Insights’ view on the use of IoT in the management and operation of smart grids. This comprises electricity, gas, water, and sewage infrastructure. The transition from traditional to smart grid operations is a significant IoT initiative transforming the supply of all three utilities (water, electricity, and gas) worldwide. In 2033, there will be 151 million grid operation devices. This report examines the reasons behind the increasing adoption of smart grids, modernisation of traditional grids, and automation of distribution systems, substations, and power regulation stations. The report also assesses the management of infrastructure, use cases, and example deployments by vendors across the three utilities. Electricity smart grid monitoring is vital for the successful implementation of load balancing and microgeneration. Electricity grids will also leverage predictive analytics and big data to prevent energy losses in the system. Climate change, increasing demand for electricity, and use of alternative energy sources (such as renewables) are the key reasons driving smart electricity grid operations. In contrast, the use of IoT monitoring and management in smart water grids is less developed. However, it is crucial as it deals with multiple issues related to water scarcity, losses, droughts, floods, and reduced water security. Gas smart grids are crucial in reducing carbon emissions, improving energy independence, and detecting gas leakages and faults. These grids also promote the use of more sustainable alternatives such as biogas, biomethane, and hydrogen. The report provides a detailed definition of the sector, analysis of market development, and profiles of the key vendors in the space. It also provides a summary of the current status of adoption and Transforma Insights’ ten-year forecasts for the market. The forecasts include analysis of the number of IoT connections by geography, the technologies used (including splits by 2G, 3G, 4G, 5G, LPWA, short range, satellite and others), as well as the revenue split between module, value-added connectivity and services. A full set of forecast data, including country-level forecasts, sector break-downs and public/private network splits, is available through the IoT Forecast tool.

ABB
Aclara
American Electric Power (AEP)
Transmission Association of Southeast Asian Nations (ASEAN)
AusNet
BC Hydro
China South Power Grid (CSG)
Cisco
Croatia
Hrvatska Elektroprivreda (HEP ODS)
Dakota Valley Electric Cooperative
DTE Energy
Enedis
Etrel
General Electric
Google
Grid Investments Advisory Council
Hawaiian Electric Companies
Hitachi
Huawei
Itron
Kahramaa-Qatar Utility
Kuwait Utility
Landis+Gyr
Manitoba Hydra
Ministry of Economy
Trade and Industry (METI) Philippines
National Grid
National smart water grid (NSWG)
Power Generation Puerto Rico
Power Grid Rhebo
SEQ water grid
Shenzhen Power Supply Bureau (SPSB)
Siemens
Smart Water Grid Research Group (SWGRG)
State Grid Corporation of China (SGCC)
SunRun
Verizon
Singapore’s Public Utilities Board (PUB)

Internet of Things
Hyperconnectivity

Electricity, Gas, Steam & A/C
Government
Water Supply & Waste Management

Why VoLTE/VoNR is a critical part of an IoT connectivity provider's portfolio

Internet of Things
IoT
connectivity
Communications Service Provider
CSP
MNO
MVNO
voice
VoLTE
VoNR
IMS

Matt Hatton

The free Position Paper ‘Why VoLTE/VoNR is a critical part of an IoT connectivity provider's portfolio ’ examines the requirement for IoT applications to support voice services and the mechanisms required for IoT connectivity providers to do so. It starts by examining the key IoT applications that demand voice services, quantifies the opportunity associated with those applications, examines the technologies required to deliver voice services and identifies 11 key characteristics of an optimised voice capability that should be delivered by an IoT connectivity provider. The report is sponsored by voice solution provider ng-voice.

ng-voice

Hyperconnectivity
Internet of Things

NTT DATA: Digital Transformation capabilities assessment

Internet of Things
Artificial Intelligence
Hyperconnectivity
Human Machine Interface
Data Sharing
Autonomous Robotic Systems
Distributed Ledger
Edge Computing
Robotic Process Automation
Blockchain
Generative AI
5G
Private Networks
LPWA
NB-IoT
LTE-M
Catena-X

Suruchi Dhingra

This report examines the capabilities of NTT DATA in Digital Transformation. It provides a comprehensive review of the products, services, and capabilities of NTT DATA across 11 technology areas and dozens of functions, to determine its core strengths for meeting enterprise needs. The 11 technology families in which the vendors capabilities are assessed are IoT, Hyperconnectivity, Human Machine Interface, Artificial Intelligence, Distributed Ledger, Data Sharing, Product Lifecycle Management, Robotic Process Automation, Edge Computing, Autonomous Robotic Systems, and 3D Printing & Additive Manufacturing. While these might not encompass every possible technology that organisations might need in order to purse a Digital Transformation, they certainly represent the most disruptive, and therefore the ones of which enterprises should be most aware. The report includes rating across each of the technology areas and functional capabilities (specialised hardware, general hardware, software products, integrated solutions, application development, systems integration and project management, specialist services, field & operational services) using Transforma Insight’s four-level universal rating system for vendors in Digital Transformation. Internet of Things, for instance, spans hardware, software, application development, implementation, field services and specialist services. For each of the 92 combinations of function and technology, NTT DATA is rated for whether its capabilities are ‘Emerging’, ‘Significant’ or ‘Market Leading’ (or ‘None’). This rating is based on both the credibility of the solution and the position of the offering in the market (e.g. market share).

NTT Data
NTT Communications
NTT Docomo
NTT Group

Unmanned Non-Road Vehicles: 683,000 vehicles expected in 2033 due to a multitude of benefits including safety and operational efficiency

Internet of Things
IoT
Hyperconnectivity
Autonomous Vehicles
AVs
Autonomous Mining Trucks
Autonomous Tractors
Forklifts
Autonomous Guided Vehicles
AGVs
Unmanned Robots
Unmanned Non-road Vehicles
Civilian Unmanned Non-road Vehicles
Military Unmanned Non-road Vehicles

Paras Sharma
Matt Arnott

This report summarises the status and forecasts from the Unmanned Non-Road Vehicles Application Group found in the Transforma Insights Connected Things IoT forecast. The report provides a description of what is covered in the Application Group, as well as top-level figures from the forecast that provide detail on how many connected devices will be installed, the types of communication technology used and the total revenue opportunity. Full details are accessible through the TAM Forecast tool.

Bear Flag Robotics
Deere and Company
L3Harris Micreo
Seegrid
SSI Schaefer
Stratom
Swisslog
Toyota Material Handling

Hyperconnectivity
Internet of Things
Autonomous Robotic Systems

Administrative
Agriculture, Forestry & Fishing
Construction
Government
Mining & Quarrying
Transportation & Storage

The state of AI acquisitions 2021-2023: Big Tech leading the charge

AI
Artificial Intelligence
Acquire
Acquisitions
Deals
M&A

Nikita Singh

This report focuses on analysis of Artificial Intelligence (AI) acquisitions completed between January 2021 to December 2023. A total of 461 AI deals have been analysed during this period based on the deal count, deal value, sector, geographies of the buyer and target company, and the focus area of the acquisition.

Accenture
Accolite Digital
Airbnb
Alphabet
Alphawave IP Group
Alter
Apple
Applica
Arcion
Arq Group
Attain
Banias Lab
BD
Becton
Dickinson and Co.
Bio Pharmaceutical New Technologies (BioNTech)
Bionic.ai
Blue Yonder
BYJU’S
Capgemini
Casetext
Chorus.AI
Cloudmed
Cobwebs Technologies
Corvus Insurance Holdings
Inc.
Crowdstrike
Databricks
Datasys Group
Inc.
DiA Imaging Analysis
Digital Ocean
DoubleVerify
Francisco Partners and TPG
GamePlanner.AI
GeoPhy
Ginkgo Bioworks
Hyperconnect
InstaDeep
Light Years Beyond
LoopMe
Match Group
Maximus
Mayfair Equity Partners
Meituan
Microsoft
Mode Analytics
Mosaic ML
Motion Metrics
MTS AI (Intema)
Myst AI
Naver
NCS Group
Neeva
Neptune Wellness Solutions Inc.
Netcore Cloud
New Mountain Capital
New Relic
NextGen Healthcare
NRG Energy
Nuance Communications
PAIR Finance
Panasonic
Paperspace
Parata Systems
PenLink
Pollen Street Capital
Poshmark
R1 RCM
Royal Philips
Scholr
Scibids Technology
Siemens
Sisu Data
Snowflake
Telus International
The Travelers Companies
Inc.
Thoma Bravo
Thomson Reuters
Thoughtspot
Unbxd Inc.
Vision Labs
Vivint Smart Home
Walker and Dunlop
Weir Group
Willow Tree
ZoomInfo
ZS Associates
Zymergen

Artificial Intelligence

Growth in Artificial Intelligence forces vendors to refocus on sustainability

Artificial Intelligence
AI
Machine Learning
ML
chatbots
LLM
generative AI
sustainability
data centre
data center
AI training
AI inference
large language models
carbon emissions
nuclear energy
power purchase agreements
natural language processing
image generation
power usage effectiveness (PUE)
water usage effectiveness (WUE)
Ireland
renewable energy
net zero
graphic processing units (GPUs)
ChatGPT

Suruchi Dhingra

Artificial Intelligence (AI) is a rapidly developing technology with a widespread impact. Its implementation can be seen all around us from chatbots to autonomous vehicles. AI developments are on course to improve operational efficiency, bring labour productivity, and boost economies. However, the negative environmental impacts of AI are often hidden from public view and the technology can have socioeconomic and sustainability implications and hinder the clean energy ambitions of tech giants. Google and Microsoft, both have reported a significant surge in their carbon emissions in the last five years, largely attributed to increase in their data centre energy consumption as a consequence of infusing AI into their core products. AI has been used for decades but the question around its impact on the environment has arisen in recent years since the techniques or AI models developed now use a vast amount of data, significant computational power and are becoming far more complex and widespread. This was triggered by the generative AI boom and mass adoption of large language model-based products like ChatGPT, DALL-E, and others in the second half of 2022 . These recent AI models are fed with diverse and large data sets to bring more accuracy and robustness, and work with low latency. This requires extensive storage and powerful processing, thus escalating electricity demand and carbon emissions. Microsoft, for example, had a stable increase of carbon emissions for many years but has reported a significant increase of 29% in carbon emissions since 2020, mostly due to its data centre expansions that were designed to support AI workloads. Another tech giant, Google, has also been facing challenges due to increased electricity demand driven by AI. It saw a rise of 48% in its carbon emissions since 2019, driven by data centres and supply chain emissions. This is clearly a challenge to the ambitions of any AI company that is aiming to becoming carbon neutral. In this report, we summarise our findings on the environmental impact of AI and we highlight some of the initiatives that are being taken by AI companies and cloud providers to offset related carbon emissions.

Amazon
Amazon Web Services
Google
Meta
Microsoft
OpenAI

Artificial Intelligence
Hyperconnectivity
Internet of Things

Information & Communication

Below is a list of Transforma Insights' research reports on Digital Transformation, IoT, AI and other disruptive technologies. Our 'Essential' subscribers can access a select sub-set of the reports as 'Essential Reading'. User Group members can access exclusive 'User Group' content. Some reports (e.g. Peer Benchmarking) are only available to 'Corporate' users. For details on how to upgrade your subscriptions, check your Profile page. If you would like to speak with our analysts about the content of any report, or any other topic, please contact enquiries@transformainsights.com.