What Might a Snapshot of a Fully Integrated IoT World Look Like 5 Years from Now?
As we’ve seen on our short journey through the IoT landscape in these posts, the ecosystem of IoT has been under development for some time. A number of factors are accelerating the deployment, and the reality of a large-scale implementation is now upon us. Since 5 years is a forward-looking time frame that is within reason, both in terms of likely technology availability and deployment capabilities, I’ve chosen that to frame the following set of examples. While the exact scenarios may not play out precisely as envisioned, the general technology will be very close to this visualization.
Since IoT will be international in scope, and will be deployed from 5th Avenue in mid-town Manhattan to the dusty farmlands of Namibia, more than one example place setting must be considered for this exercise. In order to convey as accurate and potentially realistic a snapshot as possible, I’m picking three real-world locations for our time-travel discussion.
- San Francisco, CA – USA. A dense and congested urban location, very forward thinking in terms of civic and business adoption of IT. With an upscale and sophisticated population, the cutting edge of IoT can be examined against such an environment.
- Kigali, Rwanda – Africa. An urban center in an equatorial African nation. With the entire country of Rwanda having a GDP of only 2% of San Francisco, it’s a useful comparison of how a relatively modern, urban center in Africa will implement IoT. In relative terms, the local population is literate, skilled and connected [70% literacy rate, is reputed to be one of the most IT-centric cities in Africa, and has a 26% internet connectivity rate nationally (substantially higher in Kigali)].
- Tihi, a remote farming village in the Malwa area of the the central Indian state of Madhya Pradesh. This is a small village of about 2,500 people that mostly grows soybeans, wheat, maize and so on. With an average income of $1.12 per year, this is an extremely poor region of central rural India. This little village is however ‘on the map’ due to the installation in 2002 of an ICT kiosk (named e-Choupal, taken from the term “choupal” meaning ‘village square’ or ‘gathering place’) which for the first time allowed internet connectivity to this previously disconnected town. IoT will be implemented here, and it will be instructive to see Tihi 5 years on…
Crystal ball gazing is always an inexact science, but errors can be reduced by basing the starting point on a reasonable sense of reality, and attempting to err on the side of conservatism and caution in projecting the rollout of nascent technologies – some of which deploy faster than assumed, others much more slowly. Some very respectable consulting firms in 1995 reported that cellphones would remain a fringe device and only expected 1 million cellphones to be in use by the year 2000. In the USA alone, more than 100 million subscribers were online by that year…
I personally was one of the less than 40,000 users in the entire USA in 1984 when cellphones were only a few months old. As I drove on the freeways of Los Angeles talking on a handset (the same size as a landline, connected via coilcord to a box the size of a lunch pail) other drivers would stare and mouth “WTF??” But it aided my productivity enormously, as I sat through massive traffic jams on my 1.5 hr commute each way from home to work. I was able to speak to east coast customers, understand what technical issues would greet me once I arrived at work, etc. I personally couldn’t understand why we didn’t have 100 million subscribers by 1995… this was a transformative technology.
Here are the baseline assumptions from which the following forward-looking scenarios will be developed:
- There are currently about the same number of deployed IoT devices as people on the planet: 6.8 billion. The number of deployed devices is expected to exceed that of the human population by the end of this year. Approximately 10 billion more devices are expected to be deployed each year over the next 5 years, on average.
- The overall bandwidth of the world-wide internet will grow at approximately 25% per year over the next 5 years. The current overall traffic is a bit over 1 zettabyte per year [1 zettabyte = 1 million petabytes; 1 petabyte = 1 million gigabytes]. That translates to about 3 zettabytes by 2021. From another perspective, it took 27 years to reach the 1 zettabyte level; in 5 more years the traffic will triple!
- Broadband data connectivity in general (wired + wireless) is currently available to about 46% of the world’s population, and is increasing by roughly 5% per year. The wireless connectivity is expected to increase in rate, but even being conservative about 60% of the world’s population will have internet access within 5 years.
- The cost of both computation and storage is still falling, more or less in line with Moore’s law. Hosted computation and storage is essentially available for free (or close to it) for small users (a few GB of storage, basic cloud computations). This means that a soy farmer in Tihi, once connected to the ‘net, can essentially leverage all the storage and compute resources needed to run their farm at only the cost of connectivity.
- Advertising (the second most trafficked content on the internet after porn) will keep increasing in volume, cleverness, economic productivity and reach. As much as many may be annoyed by this, the massive infrastructure must be fed… and it’s either ads or subscription services. Take your pick. And with all the new-found time, and profits, from an IoT enabled life, maybe one just has to buy something from Amazon? (Can’t wait to see how soon they can get a drone out to Tihi to deliver seeds…)
San Francisco We’ll drop in on the life of Samantha C for a few hours of her day in the spring of 2021 to see how IoT interacts with her life. Sam is a single professional who lives in the Noe Valley district in a flat. She works for a financial firm downtown that specializes in pricing and trading ‘information commodities’ – an outgrowth of online advertising now fueled by the enormous amount of data that IoT and other networks generate.
Sam’s alarm app is programmed to wake her between 4:45 – 5:15AM, based on sleep pattern info received from the wrist band she put on before retiring the night before. (The financial day starts very early, but she’s done by 3PM). As soon as the app plays the waking melody, the flat’s environment is signaled that she is waking. Lighting and temperature is adjusted and the espresso machine is turned on to preheat. A screen in the dressing area displays weather prediction to aid in clothing selection. After breakfast she simply walks out the front door, the flat environment automatically turns off lights, heat, checks perimeter and arms the security system. A status signal is sent to her smartphone. As San Francisco has one of the best public transport networks in the nation, only a few blocks walk is needed before boarding an electric bus that takes her almost to her office.
Traffic, which as late as 2018 was often a nightmare during rush hours, has markedly improved since the implementation in 2019 of a complete ban on private vehicles in the downtown and financial districts. Only autonomous vehicles, taxis/Ubers, small delivery vehicles and city vehicles are allowed. There is no longer any street parking required, so existing streets can carry more traffic. Small ‘smart cars’ quickly ferry people from local BART stations and other public transport terminals in and out of the congestion zone very efficiently. All vehicles operating in the downtown area must carry a TSD (Traffic Signalling Device), an IoT sensor and transmitter package that updates the master traffic system every 5 seconds with vehicle position, speed, etc.
As Samantha enters her office building, her phone acquires the local WiFi signal (but she’s never been out of range, SF now has blanket coverage in the entire city). As her phone logs onto the building network, her entry is noted in her office, and all of her systems are put on standby. The combination of picolocation, enabled through GPS, proximity sensors and WiFi hub triangulation – along with a ‘call and response’ security app on her phone – automatically unlocks the office door as she enters just before 6AM (traders get in before the general office staff). As she enters her area within the office environment the task lighting is adjusted and the IT systems move from standby to authentication mode. Even with the systems described above, a further authentication step of a fingerprint and a voice response to a random question (one of a small number that Sam has preprogrammed into the security algorithm) is required in order to open the trading applications.
The information pricing and trading firm for which Sam works is an economic outgrowth of the massive amount of data that IoT has created over the last 5 years. The firm aggregates raw data, curates and rates it, packages the data into various types and timeframes, etc. Almost all this ‘grunt work’ is performed by AI systems: there are no clerks, engineers, financial analysts or other support staff as would have been required even a few years ago. The bulk of Sam’s work is performed with spoken voice commands to the avatars that are the front end to the AI systems that do the crunching. Her avatars have heuristically learned over time her particular mannerisms, inflections of voice, etc. and can mostly intuit the difference between a statement and question just based on cadence and tonal value of her voice.
This firm is representative of many modern information brokerage service providers: with a staff of only 15 people they trade data based on over 5 billion distinct data sources every day, averaging a trade volume of $10 million per day. The clients range from advertising, utilities, manufacturing, traffic systems, agriculture, logistics and many more. Some of the clients are themselves other ‘info-brokers’ that further repackage the data for their own clients, others are direct consumers of the data. The data from IoT sensors is most often already aggregated to some extent by the time Sam’s firm gains access to it, but some of the data is directly fed to their harvesting networks – which often sit on top of the functional networks for the which the IoT systems were initially designed. A whole new economic model has been born where the cost of implementation of large IoT networks are partially funded by the resale of the data to firms like Samantha’s.
We’ll leave Sam in San Francisco as she walks down Bush Street for lunch, still not quite used to the absence of noise and diesel smoke of delivery trucks, congested traffic and honking taxis. The relative quiet, disturbed only by the white noise emitters of the electric vehicles (only electrics are allowed in the congestion area in SF), allows her to hear people, gulls and wind – a city achieving equilibrium through advanced technology.
Kigali This relatively modern city in Rwanda might surprise some that think of Rwanda as “The Land of a Thousand Hills” with primeval forests inhabited with chimpanzees and bush people. For this snapshot, we’ll visit Sebahive D, a senior manager working for the city of Kigali (the capital of Rwanda) in public transport. He has worked for the city his entire professional life, and is enthusiastic about the changes that are occurring as a result of the significant deployment of IoT throughout the city over the last few years. As his name means “Bringer of Good Fortune” Sebahive is well positioned to help enable an improved transport environment for the Rwandans living in Kigali.
Even though Kigali is a very modern city by African standards, with a skyline that belies a city of just over a million people in a country that has been ‘reborn’ in many ways since the horrific times of 1994, many challenges remain. One of the largest is common to much of Africa: that of reliable urban transport. Very few people own private cars (there were only 21,000 cars in the entire country as of 2012, the latest year for which accurate figures were available) so the vast majority of people depend on public transport. The minibus taxi is the most common mode of transport, accounting for over 50% of all public transport vehicles in the country. Historically, they operated in a rather haphazard manner, with no schedules and flexible routes. Typically the taxis would just drive on routes that had proved over time to offer many passengers, hooting to attract riders and stopping wherever and whenever the driver decided. Roadworthiness, the presence of a driving license and other such basic structures was often optional…
We’ll join Sebahive as he prepares his staff for a meeting with Toyota who has come to Kigali to present information on their new line of “e-Quantum” minibus taxis. These vehicles are a gas/electric hybrid powered unit, with many of the same features that fully autonomous vehicles being used currently in Japan posses. The infrastructure, roads, IT networks and other basic requirements are insufficient in Kigali (and most of the rest of Africa) to support fully autonomous vehicles at this time. However, a ‘semi-autonomous’ mode has been developed, using both sophisticated on-board computers supplemented by an array of inexpensive IoT devices on roads, bus stops, buildings, etc. This “SA” (Semi-Autonomous) mode, as differentiated from a “FA” (Fully-Autonomous) mode, acts a bit like an auto-pilot or a very clever ‘cruise control’. When activated, the vehicle will maintain the speed at which it was travelling when switched on, and will use sensors both on the exterior of the minibus as well as receive data from roadside sensors to keep the vehicle in its lane and not too close to other vehicles. The driver is still required to steer, and tapping the brake will immediately give full control back to the vehicle operator.
Rather than the oft-hazardous manner of ‘taxi-hailing’ – which basically means stepping out into traffic and waving or whistling – many small IoT sensor/actuators (that are solar powered) are mounted on light poles, bus stop structures, sides of buildings, etc. Pressing the button on the device transmits a taxi request via WiFi/WiMax to the taxi signalling network, which in turn notifies any close taxis of a passenger waiting, and the location is displayed on the dashboard mapping display. A red LED is also illuminated on the transmitter so the passenger waiting knows the request has been sent. When the taxi is close (each taxi is constantly tracked using a combo IoT sensor/transceiver device) the LED turns green to notify the passenger to look for the nearby taxi.
The relatively good IT networks in Kigali make the taxi signalling network possible. One of the fortuitous aspects of local geography (the city is essentially built on four large hills) is that a very good wireless network was easy to establish due to overlooking locations. Although he is encouraged by the possibility of a safer and more modern fleet of taxis, Sebahive is experienced enough to wonder about the many challenges that just living in Africa offers… power outages, the occasional torrential rains, vandalism of public infrastructure, etc. Although there are only about 2,500 minibus taxis in the entire country, it often seems like most of them are in the suburb of Kacyiru, Gasebo district (where the presidential palace and most of the ministries, including Sebahive’s office), is located at rush hour. An IoT solution that keeps taxis, motorcycles (the single most common conveyance in Rwanda), pedestrians and very old diesel lorries from turning a roadway with lanes into an impenetrable morass of.. everything… has yet to be invented!
Another aspect of technology, assisted by IoT, that is making life simpler, safer and more efficient is cellphone-based payment systems. With almost everyone having a smartphone today, and even the most unschooled having learned how to purchase airtime, electricity and other basic utilities and enter those credits into a phone or smart meter, the need to pay cash for transport services is fast disappearing. Variations on SnapScan, NFC technology, etc. all offer rapid and mobile payment methods in taxis or buses, speeding up transactions and reducing the opportunity for street theft. One of the many things in Sebahive’s brief is the continual push to get more and more retail establishments to offer the sale of transport coupons (just like airtime or electricity) that can be loaded into a user’s cellphone app.
IoT in Africa is a blend of modern technology with age-old customs, with a healthy dose of reality dropped in…
Tihi Ravi Sham C. is a soybean farmer in one of the poorest ares of rural India, a small village named Tihi in the central Indian state of Madhya Pradesh. However, he’s a sanchalak (lead farmer) with considerable IT experience relative to his environment, having been using a computer and online services since 2004, some 17 years now. Ravi started his involvement with the ITC’s “e-Choupal” service back then, and was able for the first time to gain knowledge of world-wide commodity prices rather than be at the mercy of the often unscrupulous middlemen that ran the “mandis” (physical marketplaces) in rural India. These traders would unfairly pay as little as possible to the farmers, who had no knowledge of the final selling price of their crops. The long-standing cultural, caste and other barriers to free trade in India also did not help the situation.
Although the first decade of internet connectivity greatly improved Ravi’s (and the other farmers in his group area) life and profitability, the last few years (from 2019 onwards) have seen a huge jump in productivity. The initial period was one of knowledge enhancement, becoming aware of the supply chain, learning pricing and distribution costs, being able to get good weather forecasting, etc. The actual farming practice however wasn’t much changed from a hundred years ago. With electricity in scare supply, almost no motorized vehicles or farm equipment, light basically supplied by the sun and so on, real advances toward modern farming were not easily feasible.
As India is making a massive investment into IoT, particularly in the manufacturing and supply chain sectors, an updated version of the “e-Choupal” was delivered to Ravi’s village. The original ‘gathering place’ was basically a computer that communicated over antiquated phone lines at very low speed and mostly supported text transmissions. The new “super-Choupal” was a small shipping container that housed several computers, a small server array with storage and a set of powerful WiFi/WiMax hubs. Connectivity is provided with a combination of the BBNL (Bharat Broadband Network Limited) service supported by the Indian national government, which provided fiber connectivity to many rural areas throughout the country, and a ‘Super WiFi’ service using Microsoft White Spaces technology (essentially identifying and taking advantage of unused portions of the RF spectrum in particular locations [so called “white spaces”] to link the super-Choupal IT container with the edge of the fiber network.
Power for the container is a combination of a large solar array on the top of the container supplemented by fuel cells. As an outgrowth of Intelligent Energy’s deal with India to provide backup power to most of the country’s rural off-grid cell towers (replacing expensive diesel generators), there has been a marked increase in availability of hydrogen as a fuel cell source. The fuel is delivered as a replaceable cartridge, minimizing transport and safety concerns. Since the super-Choupal now serves as a micro datacenter, Ravi spends more of his time running the IT hub, training other farmers and maintaining/expanding the IoT network than farming. Along with the container hub, hundreds of small soil and weather sensors have been deployed to all the surrounding village farms, giving accurate information on where and when to irrigate, etc. In addition, the local boreholes are now monitored for toxic levels of chemical and other pollutants. The power supplies that run the container also provide free electricity for locals to charge their cellphones, etc.
As each farmer harvests their crops, the soybeans, maize, etc. are bagged and then tagged with small passive IoT devices that indicate the exact type of product, amount, date packed, agreed upon selling price and tracking information. This now becomes the starting point for the supply chain, and can be monitored all the way from local distribution to eventual overseas markets. The farmers can now essentially sell online, and receive electronic payment as soon as the product arrives at the local distribution hub. The lost days of each farmer physically transporting their goods to the “mandi” – and getting ripped off by the greedy middlemen – are now in the past. A cooperative collection scheme sends trucks around to each village center, where the IoT-tagged crops are scanned and loaded, with each farmer immediately seeing a receipt for goods on their cellphone. The cost of the trucking is apportioned by weight and distance and billed against the proceeds of the sale of the crops. The distributor can see in almost real time where each truck is, and estimate with knowledge how much grain and so on can be promised per day from the hub.
The combination of improved farming techniques, knowledge, fair pay for the crops and rapid payment have more than tripled Ravi’s, and his fellow farmers’ incomes over the past two years. While this may seem like a small drop in the bucket of international wealth (an increase from $1.12 per year to $3.50 per year by first world standards is hard to appreciate), the difference on the ground is huge. There are over 1 billion Ravi’s in India…
This concludes the series on Internet of Things – a continually evolving story. The full series is available as a downloadable PDF here. Queries may be directed to firstname.lastname@example.org