IoT seems like a more popular label than M2M (machine-to-machine). As such, users may conclude that M2M design approaches are perfectly satisfactory. This is a risky assumption.
M2M solutions typically apply to well-defined, vertical-industry applications. IoT solutions involve interactions across disparate connected devices and other data sources. Devices may connect via different networks and platforms. Applications may also be developed via “mash-up” strategies and across vertical application silos.
Metrics to evaluate IoT and M2M are also different. M2M tends to be valued in ‘numbers of connected devices’ and the ‘average revenue per device’. IoT is quantified by the economic value that is created by eliminating inefficiencies or exposing new value propositions.
IoT product (and service) development can learn from the M2M market. However, long term success is contingent on anticipating new service opportunities. Consider this in terms of four product development stages.
- Adding basic connectivity – this is a decision about adding fixed-network, mobile and/or short-range wireless connectivity to a device and how this is provisioned across one or more network providers.
- Integrating managed connectivity – a high quality of service relies on a service management platform to ensure that devices are working properly, that data is transferred effectively and to manage devices remotely.
- Implementing a ‘vertical’ M2M application – this may be an asset tracking or machine-health monitoring application which may also be integrated with a company’s enterprise resource planning system.
- Anticipating IoT application(s) – here, the value of a connected device is magnified by supplying its data to other applications or because its own performance is enhanced by data from external sources. An example might be an urban, transport management application that makes use of fleet movement, highway traffic and micro-climate data from a weather-services agency.
Most companies get caught up in the first few stages of product development and miss out by not planning for Stage 4 sources of value. In the connected home market, Google’s $3.2bn acquisition of NEST connected home products shows where an IoT mind-set is taking the M2M industry.
The challenge for manufacturers aiming to profit from IoT opportunities is to manage their product development road-map strategically. They have to anticipate solution “mash-ups” and data from different ‘vertical’ silos or third-party sources.
The supply-side of the IoT market faces its own challenges. Basic connectivity will be commoditised once technology choices are simplified. By then, network and platform interoperability will drive value through new business models based on shared resources and data assets.
This article was first published in m2m Journal, March 2014 (www.m2m-alliance.com)
5 March 2021
ReplyDeleteHere's an example of a cross-departmental application - waste management + use of road network monitoring cameras + policing
https://www.bbc.com/news/av/uk-56255823
13 October 2021 update
ReplyDeleteNokia envisions Airport 4.0 where ‘connectivity is no longer a commodity’
See image of progression from Airport1.0 to Airport4.0
https://enterpriseiotinsights.com/20211004/channels/news/nokia-envisions-airport-4-0-where-connectivity-is-no-longer-a-commodity
17 July 2023 update
ReplyDeleteCreating feedback loops from data and AI
How to create or strengthen feedback loops for products that can learn from customer data
The increasing availability of artificial intelligence, including machine learning algorithms, means that deliberately creating data feedback loops is now possible for most products and services. For some products, it is easy; for others, one needs to find more creative ways to engineer the data feedback loops — via integrations or minimally intrusive incentive-compatible requests for user feedback. When they are strong, these feedback loops can create a form of network effect (more users bring more data, which makes the product better, in turn attracting more users, and so on) and – provided other conditions are met – compounding competitive advantage.
https://platformchronicles.substack.com/p/creating-feedback-loops-from-data
26 April 2024 update
ReplyDeleteLeicester updates travel app to show street lighting and cameras
Leicester City Council in the UK is partnering with mobility tech firm SkedGo to enable pedestrians walking at night to see how much of their journey is covered by street lighting and CCTV.
The Lit Routing functionality forms part of the Choose How You Move app, which aims to reshape travel in the city, offering pedestrians more accessible and illuminated paths.
“Our Choose How You Move journey planning app now suggests nighttime walking routes that are well-lit and covered by CCTV, helping to reduce the perception of risk associated with being out after dark,” a Leicester City Council spokesperson told Cities Today. “We will be monitoring how people use the app to review its functionality and understand what further refinements we can make.”
https://cities-today.com/leicester-updates-travel-app-to-show-street-lighting-and-cameras/
9 August 2024 update (added value of interactivity in product planning, from the AI and gaming worlds)
ReplyDeleteMy Imaginary Friend is a Gamer: Implications of Introducing LMs to Multiplayer Games
The widespread introduction of CA-bots will open new avenues for in-game advertising. Global revenue from in-game advertising is expected to reach USD 109.60bn in 2024 (Statista, 2023) and CA-bots can be used to make this more effective for two reasons. First, CA-bots, as opposed to recommender systems like social media ads, are more trusted in general – the more human an artificial agent appears to be, the more likely humans are to trust its output (Glikson & Woolley, 2020) and, in the case of chatbots specifically, the better the advertising-effectiveness (Sun et al., 2024). Second, through their conversational abilities, CA-bots can elicit user preferences on a given topic by directly asking users about a topic or directing the conversation towards it. This allows them to work out which products are relevant to a given user at that time. After eliciting user preferences, CA-bots can make relevant advertising a natural part of the conversation and the game at large. By making the advertising a part of either the game narrative or the conversation, a higher level of transportation is achieved (Sun et al., 2024), leading to fewer negative thoughts and stronger responses to ads (Escalas, 2004).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4903925