Aftermarket Micromobility Devices: A 111 million device market in 2034 impelled by fitness, convenience, and safety
- ANT+
- aftermarket
- bicycle
- bike
- bike computer
- Cadence sensors
- e-bike
- e-scooter
- fitness trackers
- Global Navigation Satellite System
- GNSS
- GPS
- helmets
- smart lock
- micromobility
- mobility
- navigation
- near field communication
- scooter
- speed sensors
- TPMS
- tyre pressure monitoring system
This report provides Transforma Insights’ view on the Aftermarket Micromobility Devices market. The report covers devices or accessories used with all types of Micromobility Vehicles including bicycles, e-bikes, scooters, and e-scooters, to enhance the safety of the vehicle and riding experience of the rider. These include connected helmets, fitness trackers, navigation devices, smart locks, lights, speed and cadence sensors, tyre pressure monitoring systems (TPMS), and stolen vehicle tracking. Micromobility vehicles are an integral component of urban transportation offering multiple benefits to both leisure users and commuters. As the use of these vehicles has increased so has the demand for accessories that improve users’ journeys. For instance, Micromobility Helmets are beneficial for riders to enhance their visibility on road with the presence of turn lights, and in some cases cameras for recording the ride. Micromobility Lights are another device type that increases riders’ visibility not only in darkness but also during the day. Stolen Micromobility Tracking devices are useful for faster theft detection and locating stolen vehicles. 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 breakdowns and public/private network splits, is available through the IoT Forecast tool.
- Abus
- AIRsistant
- Ananda
- Beeline
- Bontrager
- Bosch
- Brose
- Campagnolo
- Coros
- eTap
- Garmin
- Google
- GoPro
- Hammerhead
- I Lock it
- Insta360
- KPN
- Kurt
- Linka
- Livall
- Lumos
- Luna System
- Magene
- Mobi Lock
- National Highway Traffic Safety Administration
- Schrader
- Segway
- Sena
- Shimano
- Trek Bicycle Corporation
- Tyre Wiz
- University of Utah
- Yamaha Motor Corporation
- Artificial Intelligence
- Internet of Things
- Hyperconnectivity
- Consumer
- Transportation & Storage
A new kind of software platform for AIoT?
- AI
- AIoT
- Artificial Intelligence
- Connectivity Management Platform
- Connectivity Platform
- Device Management Platform
- Edge Computing
- Internet of Things
- IoT
- IoT Platform
Artificial Intelligence (AI) and the Internet of Things (IoT) are two of today’s most impactful technology developments. Inevitably, an increasing range of both enterprise and consumer applications and solutions leverage both technologies, so that they are enabled by both AI and IoT. A growing subset of these applications and solutions incorporate AI capabilities directly onboard an IoT device, as AIoT, unlocking benefits ranging from faster response times to more efficient use of connectivity bandwidth. This report focusses on the implications that the growth of AIoT might have on software platforms designed to support AIoT applications. Supporting software platforms for IoT are relatively well-developed, including Connectivity Management Platforms, Device Management Platforms, Application Enablement Platforms, and more. Meanwhile, supporting software platforms for AI are developing fast, and include concepts such as Application Performance Management, Software Management (often referred to as MLOps), Workload Management, and more. Since AIoT is defined as occurring when AI and IoT converge onboard devices, it is natural that platforms that are designed to support AIoT devices should include a set of capabilities that are drawn from both AI and IoT domains, alongside new AIoT-specific capabilities. This report discusses some of the key capabilities that a software platform specified to support AIoT devices should have. It focusses on the specific requirements for supporting AIoT devices, rather than more generic requirements that are well-known in either IoT or AI contexts.
- Brainchip
- Edge Impulse
- SiMa.ai
- Internet of Things
- Edge Computing
- Artificial Intelligence
Application Performance Management tools optimise AI software applications with continuous monitoring
- Artificial Intelligence
- AI
- Application Performance Management
- Application Performance Monitoring
- APM
- Observability Platform
Application Performance Management (APM) is a tool for both monitoring and managing the performance and health of software applications. APM tools automatically collect application performance data, analyse application behaviour, and identify issues in real-time, enabling businesses to ensure optimal performance, enhance user experience, and minimise downtime. In this report, we delve into the role of APM in monitoring and optimising AI software application performance, utilising data analysis and real-time issue identification to enhance user experience and minimise downtime. We discuss how APM provides a dashboard-like view of AI applications, offering deep insights into system health and efficiency, thereby significantly reducing operational disruptions and maintenance costs. Further, we explore the APM vendor landscape, categorising key players like Arize AI, Datadog, and Dynatrace, using a four-quadrant analysis that assesses their innovation and market presence. Additionally, we address the sector's evolution driven by advances in cloud infrastructure, emphasising the importance of maintaining user-friendly tools despite increasing system complexity. Lastly, we highlight the critical need for these tools to integrate seamlessly with diverse IT ecosystems and comply with strict data security regulations. Real-time analytics are the key characteristic of APM solutions because they must allow developers and IT professionals to detect and address issues promptly and before users experience problems or service degradation. This is critical in environments where AI applications must perform at high levels of reliability and speed, such as in financial trading or autonomous driving systems. AI APM also supports the continuous improvement of AI models by providing data used to refine algorithms and enhance performance.
- Arize AI
- Datadog
- Dynatrace
- Elastic
- Evidently
- Fiddler
- New Relic
- Whylabs
Honeywell: Digital Transformation capabilities assessment
- 3D Printing and Additive Manufacturing
- Internet of Things
- Artificial Intelligence
- Hyperconnectivity
- Human Machine Interface
- Data Sharing
- Autonomous Robotic Systems
- Distributed Ledger
- Edge Computing
- Robotic Process Automation
- Product Lifecycle Management
- Digital Transformation
- Generative AI
- Precision Specialist Robots
- Autonomous Robots
- Heads-up display
- Mixed reality based heads-up display
- Paras Sharma
- Suruchi Dhingra
This report examines the capabilities of Honeywell in Digital Transformation. It provides a comprehensive review of the products, services, and capabilities of Honeywell across 11 technology areas and dozens of functions, to determine its core strengths to meet 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 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, and field & operational services) using Transforma Insights’ 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, Honeywell 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).
Community Heating: A slow growing market with 85 million devices by 2034 fueled by climate resilience and energy-saving requirements
- Advanced Metering Infrastructure (AMI)
- Carbon Emissions
- District Cooling
- District Heating
- Individual Heating
- Generation Plants
- Geothermal Energy
- Grid Operations
- Load Balancing
- Renewable Energy
- Smart Energy
- Smart Grids
- Smart Heat Meters
- Smart Meters
- Sustainability
This report provides Transforma Insights’ view on the use of IoT to support Community Heating. Community Heating (CH) involves generating heat in a centralised location and then distributing the heat across businesses, residences and industry. Community heating is most common in colder countries, particularly the Nordic countries, China, Russia, and some parts of North America. Some of the prominent advantages of community heating solutions are energy saving, reduced carbon emissions, and improved load balancing when compared to traditional heating solutions. The market for community heating has been backed by several government initiatives and schemes that support its deployment not only because of the environmental benefits it provides in densely populated areas but also as a method for encouraging employment due to the need for considerable infrastructure investment. Community heating and cooling systems are gaining traction, yet their deployment is still far behind individual solutions. This is because of several disadvantages including lack of scalability in less densely populated areas, billing complexities, irregular heat distribution, lack of user control, and issues such as overheating in less sophisticated systems. To improve efficiency, CH systems are increasingly using smart heat meters to measure consumption, detect faults remotely, support load balancing, and help to reduce carbon emissions. 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.
- Avara
- Caofeidian Heat Company
- Cetetherm
- Danfoss
- Engie SA
- Ennatuurlijk
- Espoon Asunnot
- European Commission
- Landis+Gyr
- State Power Investment Corporation (SPIC)
- Vattenfall
- Veolia
- Vital Energi
- Artificial Intelligence
- Hyperconnectivity
- Internet of Things
- Electricity, Gas, Steam & A/C
AI Marketplaces bridge the gap between innovation and application
- Artificial Intelligence
- AI
- Data Sharing
- Enterprise AI
- Marketplace
- AI Marketplaces
- Regulations
This report analyses the dynamics of Artificial Intelligence (AI) Marketplaces, one of the key vendor types identified in Transforma Insights’ AI Market Framework. It includes discussion of their many stakeholders such as developers, data owners, and regulators who converge to coordinate their developments and trade AI models and services with end users. Other dynamics include ensuring the privacy and security of the data, end users who require help with technical expertise to assess model quality, ongoing maintenance requirements for products developed, and the proprietary nature of many of the solutions created. The types of marketplaces and the vendors associated with them are segmented into generalist and specialist types and reviewed for their capabilities, including infrastructure, Machine Learning (ML) models, data storage, computing resources, and others. We also draw attention to how marketplace platforms can promote standards, are challenged by regulatory complexities, and advance AI solutions across industry sectors. Marketplaces are digital spaces that connect AI vendors and adopters, including AI service developers, vendors of pre-trained AI models and enterprises and other end users, who can then coordinate the exchange of services, payments, and AI solutions. Marketplaces are platforms and can be open, single-master, or consortium-driven. Single-master and consortium-driven marketplaces are curated, in the former case by a single vendor (for example, AWS) and in the latter case, by a group in a consortium. Curated marketplaces often cater for a more specific user base (including vendors and products) and focus on hosting AI solutions that match that focus.
- AWS
- Defined AI
- Google
- Gravity AI
- Hugging Face
- Kaggle
- Microsoft
- Phygital+
- Artificial Intelligence
- Data Sharing
Digital Transformation in the Retail Industry
- Internet of Things
- Artificial Intelligence
- Hyperconnectivity
- Human Machine Interface
- Data Sharing
- Autonomous Robotic Systems
- Distributed Ledger
- Edge Computing
- Robotic Process Automation
- retail
- store
- asset tracking
- personalised shopping
- converged commerce
- augmented shopping experience
- autonomous stores
This report examines digital transformation (DX) in Retail, enabled by the key technology groups that are the focus of Transforma Insights’ research. The report focuses on digitally transformative solutions adopted in physical and online retail environments.
- 3DLOOK
- Acean
- Adidas
- AiFi
- AIREM
- Amazon
- Amazon Web Services
- Badger Technologies
- Belcorp
- Bemis Retail Solutions
- Brickhouse Security
- Coach
- Cooler Screens
- Cosium
- Digit7
- DISPL
- Eye-oo
- FFFace.me
- Flags
- Home Depot
- Instacart
- JLL Retail
- Johnson Controls
- JuiceBabe
- Kotsovolos
- L’Oréal
- Lowe's
- Maybelline
- MySize
- Nedap
- Nike
- Nivea
- Nourish + Bloom Market
- PAL Robotics
- Perfect Corp
- Pimkie
- Puente Enterprises
- PulpoAR
- Sephora
- Shopic
- Shopwise International
- Shufersal
- Sigfox
- Simbe Robotics
- Slø
- Snapchat
- Solum Global
- SpartanNash
- Target
- The Kroger Co
- Tidio
- Tokinomo
- TotalEnergies
- TouchSource
- Tutch
- UnaBiz
- Visage Technologies
- Walgreens
- Walmart
- Wiliot
- Zebra Technologies
- Zero10
- Zippin
A diverse landscape of AIoT chipset vendors is seeking to differentiate in fragmented IoT markets
- Artificial Intelligence
- AI
- Internet of Things
- IoT
- AIoT
- AnalogEdge AI
- accelerators
- compute-in-memory
- at-memory compute
- Edge AI
- neuromorphic computing
- Machine Learning System-on-a-Chip (SoC)
- unified memory architecture
- spiking neural networks.
This report discusses the leading players in the Edge AI and AIoT chipset space. The rapid growth of AIoT devices with diverse processing needs along with the proliferation of innovative chip designs is leading to the emergence of optimised edge AI and AIoT chipsets, used across various applications like natural language processing, computer vision, anomaly detection, and predictive maintenance. Such machine learning algorithms on edge devices are often required to operate at much lower levels of power consumption than equivalent algorithms running on servers or in data centres, due to limitations of availability of power. Increasingly vendors are offering edge AI chipsets with various value-added capabilities to differentiate their offerings. In light of this, several AIoT chipset providers have begun offering end-to-end solutions by providing software suites of tools. These software solutions enable businesses to build, test, and deploy customised machine learning (ML) applications by facilitating pre-silicon ML workload simulations and evaluating key performance metrics for their chips and more. Typically, such software suites consist of APIs, development tools, and prebuilt software libraries, supporting developers to deploy ML models on edge AI chips. They often incorporate features like quantisation and compression tools to optimise large language and other models to fit within the constraints of silicon with limited memory and computational capacity, aligning the models with the chip's architecture. Also, chipset providers are looking for new ways to widen and expand their revenue opportunities and increase their chipset adoption across industries by offering software tools. Thus, some companies are strengthening their software capabilities to offer a deep learning software development kit, ensuring a seamless development, deployment, and testing of edge machine learning applications.
- Andes Technology
- AON Devices
- Axelera AI
- BrainChip
- Hailo Technologies
- Himax Technologies
- IBM
- Innatera
- Mythic
- Nvidia
- Perceive
- SiMa
- Syntiant
- UntetherAI
- Artificial Intelligence
- Internet of Things
Track & Trace: An integral part of supply chain transparency
- Internet of Things
- IoT
- Hyperconnectivity
- Supply Chain Visibility
- Supply Chain
- Asset Tracking
- Supply 4.0
- Traceability
- RFID
- Barcode
- Track & Trace
- Personal Item Tracking
- Pallet Tracking
- Cage Tracking
- Logistics
- Consumer Tags
- Disposable Devices
- Suruchi Dhingra
- Paras Sharma
- Matt Arnott
The main drivers behind the adoption of Track & Trace solutions are the prevention of theft or loss, reduction of operational losses and recall incidents, and optimisation of product lifecycle management. Previously, the loss of items (such as reusable assets) was outweighed by the cost of asset tracking, but as IoT technology is becoming cheaper, and asset losses increase as businesses expand, the utilisation of tracking devices is becoming increasingly viable. The application group is also witnessing a strong regulatory push for the monitoring of goods whilst in transit, particularly in the pharmaceutical and food industry. These regulations are an effort to reduce spoilage, contamination, and falsified items in these industries. This report summarises the status and forecasts from the Track & Trace 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 IoT Forecast tool.
- Accent Systems
- Amazon
- An Post
- AT&T
- Bemis Retail
- CoreKinect
- CourierPlease
- Digital Matter
- DHL
- Emerson
- Everynet
- FedEx
- KORE
- Nippon Expree
- Life360
- NTT Docomo
- Posten
- PostNL
- Roambee
- Telia
- Thinxtra
- Tile
- T-Mobile
- UPS
- Verizon
- Vodafone
- Wiser Systems
- Internet of Things
- Hyperconnectivity
- Agriculture, Forestry & Fishing
- Mining & Quarrying
- Manufacturing
- Construction
- Retail & Wholesale
- Transportation & Storage
- Health & Social Care
Digital Transformation in Sports
- Internet of Things
- IoT
- Artificial Intelligence
- AI
- Hyperconnectivity
- Data Sharing
- Autonomous Robotic Systems
- Human Machine Interface
- Distributed Ledger
- Edge Computing
- Robotic Process Automation
- sports
This report examines digital transformation (DX) in sports, enabled by the key technology groups that are the focus of Transforma Insights’ research. It focuses on the use of DX in all aspects of sports including stadiums, homes, fans, broadcasters, advertisers, athletes, coaches, scouts, and sports organisations.
- 8i
- ADI
- ai.io
- AiSCOUT
- Alcatraz AI
- Ant International
- ARES Security
- ARound AR
- Axess
- Barcelona FC
- Bayern Munich FC
- Blackbox Infinite
- Board of Control for Cricket
- BrandXR
- Catapult
- Chelsea FC
- Columbus Crew
- Dedrone
- Diamond Scheduler
- ESPN
- EyeGuide
- FirstBeat Sports
- Formula One
- Fox Sports
- Genius Sports
- GPSport
- Grekkom
- Hawk-Eye Innovations
- Houston Dash
- Immersiv.io
- Intel
- Interact Sport
- LaLiga
- Lapz.io
- Liverpool FC
- Los Angeles FC
- Los Angeles Rams
- Major League Soccer (MLS)
- Microsoft
- MindMaze
- MindMotion Pro
- Mindway AI
- Narrativa Betting Services
- National Basketball Association (NBA)
- National Collegiate Athletics Association (NCAA)
- National Football League (NFL)
- National Hockey League (NHL)
- North Jersey Junior Basketball League (NJJBL)
- NXT Interactive
- Oakland A's
- Obvios
- Paris Saint-Germain FC
- Pittsburgh Steelers
- PlayerTek
- Playpass
- Playtech
- PMY Group
- PokerBaazi
- Premier League
- Real Madrid FC
- SailGP
- Seamless Digital
- SHIELD
- Sky Sports
- Sloan Security Group
- Sportec Solutions
- Stake
- StatSport
- Strive
- Supponor
- Telstra
- The Famous Group
- Tottenham Hotspur FC
- UEFA
- Ultimate Fighting Championship (UFC)
- uniqFEED
- Vection Technologies
- VeriDas
- Verizon
- Weezevent
- Westex Security
- Wicket
- WIN Reality VR
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.
