Ottomate Smart Fan: Not smart enough

Last month, I was invited to the Ottomate Smart Fan launch event in New Delhi, where I sat for what felt like an entire day listening to Vishal Sehgal, Ottomate’s Co-Founder and MD, wax poetic about the company’s first product. Sehgal, who is also the Co-Founder of Lava International (yes, the Indian smartphone brand), explained to me and a few other heavy-eyed journalists that there had been absolutely no innovation in the ceiling fan industry in the past fifty years. Running us through numerous slides, he presented the Ottomate Smart Fan, an advanced ceiling fan operated using a smartphone app.

Curious enough, I got in touch with the Ottomate team and asked for one to be installed in my bedroom. No more than a week later, an Ottomate personnel turned up at my doorstep with a couple of boxes, an installation kit, and a folding step ladder. As he went about installing the fan, he told me that I would need the Ottomate app to use it. As I reached for my iPhone, he said the app was available only on Android. Fortunately, I had an Android phone too, so before long I was able to create an account with Ottomate and register the product. And a little after that, what should I see pop up on the app but a firmware update—for my ceiling fan! Imagine my surprise.

Ottomate: How the system works

Before I tell you about my experience with the fan, let me explain to you how the whole Ottomate system works. The Gurgaon-based company aims to offer a whole range of “smart” consumer durables like ceiling fans, lights, and water heaters that are operable through the Ottomate smartphone app. The idea is that once these “smart” devices are all installed and connected to a smartphone, the user can then control them from any part of the house using the connected smartphone. In an ideal scenario, the user should be able to control the operation of a connected Ottomate device that’s in the first floor from the ground floor without having to get up. What’s more, an entire mesh of Ottomate devices can be connected through Bluetooth Low Energy and controlled using the same app. The primary user can add more users and guests.

In addition to creating “smart” durables, Ottomate wants to simplify the installation process of its devices. According to the company, the user needn’t go to the trouble of calling a local electrician to have their new device installed; once the user has purchased an Ottomate product, they need only download the Ottomate app on their Android phone, open it, and request an installation. They can then expect an Ottomate installation agent to visit their home and take care of the setup. Future service requests too can be made from the Ottomate app.

From the proposed range, the company’s first product is the Ottomate Smart Fan. Designed by Bangalore-based design studio Foley Designs, it looks no different from a regular ceiling fan at first glance but has a few tricks up its sleeve. Sitting next to the motor inside the central dome is a Qualcomm CSR1020 QFN chipset, which is considered the “brain” of the fan. It features a 16-bit processor, 80 kilobytes of RAM, 60 kilobytes of internal storage space for applications, Bluetooth 4.2, Bluetooth Low Energy, and CSRmesh. The fan also has an integrated temperature and humidity sensor made by STMicroelectronics. All this is what lets the fan talk to the Ottomate app on an Android smartphone. The fan can also be operated using a proprietary Ottomate remote control, which is an optional purchase.

Ottomate service engineer at work

Ottomate Smart Fan: My experience

With the installation of the new Ottomate Smart Fan all done, I sat around under the fan playing with the controls on the app. I explored all the speed options available. Unlike a regular ceiling fan, which is typically equipped with a four- or five-speed regulator, the Ottomate Smart Fan could be set to spin at any speed between 1 and 100 with the option of a Turbo Mode, which gave it an additional ten-percent boost after its top speed. There was a Breeze Mode, which varied the speed of the fan every few seconds to create the effect of a breeze. This, I felt, was a bit of a gimmick even though the fan made use of the internal temperature and humidity sensor to work. Of course, I can understand if there are users out there who might actually like such an effect. Lastly, there was an Otto Mode (auto mode, basically), which, as you can guess, set the speed of the fan automatically depending on the temperature and humidity. The Otto Mode predicted the right speed required quite well as far as I could tell.

I have been using the Ottomate Smart Fan for the last two or so weeks now. While my experience has been mostly pleasant during this time, I came across a few unmissable issues. The first is noise. The Ottomate Smart Fan installed in my bedroom is significantly louder than my previous Havells fan at any speed. This, I’m told by my colleague Shrey, could be the result of a bad installation. At any rate, the grinding noise from the Ottomate in the middle of the night—resembling an old fan from the 70s—vexes me enough to believe the Ottomate Smart Fan wasn’t designed smartly enough to run quietly.

The second issue is overall quality of execution. The Ottomate app, which is currently limited to Android users and has no integration with Amazon Alexa or Google Assistant, needs the user’s location at all times to run, something users concerned about privacy (like me) will not want to provide. On launching, the app loads (read: communicates with the fan) for some four to five seconds before letting me control the fan. Working the speed slider in the app can, at times, be a bother while setting a precise number. On pressing the back button, the app persistently asks if I really want to quit. All these niggles give me the impression that I’d have sooner operated the fan by getting up from my bed and reaching for the regulator on the wall. The lack of a bundled remote control only adds to my annoyance because, honestly, it would have still been faster than using the Ottomate app.

Ottomate app only available on Android for now

Summary: Smart but not smart enough

I think Ottomate is bold and ambitious in its quest to build a connected household but its first product already suffers from quality issues, especially in terms of execution. After a few weeks with the Ottomate Smart Fan, I’m left with the impression that it’s a noisy fan—noisier than the thirty-year-old Khaitan table fan my grandmother owns. It doesn’t help that at times, it takes longer to operate the fan through an Android smartphone than through a traditional regulator on the wall. In summary, the Ottomate Smart Fan is an advanced ceiling fan with the potential to be truly smart, but right now, is just trying too hard.

Your next major health problem could be predicted in advance

Back in May 2018, Owkin, a medical research machine learning startup, received $5 million in Series A follow-on funds from GV, Alphabet’s venture investment arm. For the uninitiated, Alphabet is the parent company of Google that was created when the organisation went through a massive restructuring back in 2015. Cut to 2019, in February, the US Patent and Trademark Office published a Google patent about a predictive EHR system. The patent was apparently filed back in 2017 and hasn’t been granted yet.


Before we explain why this is important, it is essential to know what EHR is. Electronic health records, or EHRs, are an organised collection of patient data that can be shared across different healthcare situations. In terms of the data stored, EHR may include a wide variety of markers like demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information. Such a system allows doctors to access all of this information about a patient, new or old, as it is usually linked to identifiers such as social security numbers in the US. However, if technology based on the Google patent application came to be, their usefulness could go beyond that.

The patent

The Google patent in question intends to use EHR in multiple ways by subjecting it to machine learning. The massive amount of data in there definitely holds a lot of potential for many use cases. For instance, the first part will focus on aggregating such information from multiple sources and organisations. On the face of it, this is a huge task in itself because of how healthcare data can vary from organisation to organisation. As Google put it in a blog post dated back to May 2018, even something as basic as the temperature can have different meanings depending on where it was measured from – under the tongue, through your eardrum, or on your forehead. However, Google has defined its approach to this problem by applying a new model to track health records, built on top of the open Fast Healthcare Interoperability Resources (FHIR) standard described earlier by them.

Data in a patient’s record is represented as a timeline. For illustrative purposes, different types of clinical data (e.g. encounters, lab tests) are displayed by row. Each piece of data, indicated as a little grey dot, is stored in FHIR, an open data standard that can be used by any healthcare institution. A deep learning model analyzed a patient’s chart by reading the timeline from left to right, from the beginning of a chart to the current hospitalization, and used this data to make different types of predictions. (Source: Google)

The second part of this system would be the application of deep learning to the standardised data. A chronological reading of all the data points involved helps to highlight the factors that are most crucial for prediction purposes. This data would then be visible in the third part, a doctor facing interface that features these predictions in a format consumable to them. Another aspect of this would be to highlight pertinent medical events and data from the past, which removes the need for the physician to go through a large number of notes and records related to the patient.

While Google isn’t providing any new comments on the system, the blog post mentioned earlier goes on to show how the investigation used 46,864,534,945 retrospective EHR data points collected from 216,221 adult patients hospitalized for at least 24 hours at two US academic medical centres. Armed with this data, the deep learning models were able to successfully predict in-hospital mortality, unplanned re-admissions in a 30-day span, elongated stay durations and ultimately, diagnoses at the time of discharge with an accuracy that was not only superior to a manual analysis of the data, but also predictive systems that worked off of smaller data sets.

A deep learning model was used to render a prediction 24 hours after a patient was admitted to the hospital. The timeline (top of figure) contains months of historical data and the most recent data is shown enlarged in the middle. The model “attended” to information highlighted in red that was in the patient’s chart to “explain” its prediction. In this case study, the model highlighted pieces of information that make sense clinically. (Source: Google Research)

The potential and the competition

Before EHR, there was a lack of enough data to efficiently take actions in healthcare for the patient’s benefit. Since EHR, it can be argued that there’s an overabundance of data that can prove to be a hindrance to physicians and medical professionals. A system like the one described in the patent answers two important questions that plague physicians every day – which patient requires my attention the most, and which part of their records should I focus on.

Last year’s report by MeitY titled Adoption of Electronic Health Records: A Roadmap for India, highlights the obstacles to a centralised system like this in India. A large number of hospitals and medical facilities in our country lack the basic information and communication infrastructure that is crucial for such systems to be reliable and operational. On top of that, much of the EHR data in India is stored in privatised silos, with no exchange between private hospitals, which see 75% of outpatients and 60% of inpatients in India.

While the exact situation of the doctor-patient ratio seems to be dependent on whether you take only allopathic doctors into consideration or not, it is no secret that the healthcare system in the country could improve, especially when it comes to better patient care and efficiency. A system like this, from a company, as deeply invested in India as Google, could prove to be a significant change-maker. Unless competing offerings from Apple and Amazon break ground first. 

Amazon is also invested in this area with Amazon Comprehend Medical, last explained by the company in November 2018, working almost identically to Google’s project. Interestingly, Amazon has also filed a patent earlier for Alexa to be able to pick up on a cold or a cough from a person’s voice, detecting a deviation from the norm and maybe even suggesting possible remedies or medication. 

Apple’s ResearchKit puts the iPhone’s sensors at the disposal of researchers to carry out studies.

Apple, on the other hand, has also announced its intentions to move into the same space. With Apple Watch with a single-lead ECG, as well as the Apple Health Record, there are other things also that indicate Apple’s intentions to be a platform friendly to developers looking to build healthcare offerings off of their platform. ResearchKit and CareKit SDKs allow researchers to use the iPhone for research purposes and also to use its sensors to monitor patients. Multiple startups have used these SDKs to build their offerings, like Glow and One Drop. If Google makes something similar available to startups, especially in India, it could open up the doors to a lot of Indian startups to leverage Google’s massive data mine to build affordable healthcare software for the masses. 

OnePlus 7 Pro specs leaked in entirety ahead of May 14 launch

While the OnePlus 7 series of handsets will be officially announced on May 14, details about the upcoming phones keep leaking out. After numerous renders, reports and leaks that revealed some specs of the phone bit by bit, the full spec sheet of the OnePlus 7 Pro has now surfaced online. The information reveals what the phone might have to offer, down to its dimensions. The latest report comes via renown tipster, Roland Quandt who has also tweeted out the phone’s alleged German pricing.

OnePlus 7 Pro leaked specifications

The listing tips at a 6.67-inch ‘Fluid’ AMOLED display on the phone with a 1440×3120 pixel resolution. It’s display is said to feature 90Hz max refresh rate and 516ppi pixel density. It’s powered by the Snapdragon 855 SoC and is running on OxygenOS, on top of Android 9 Pie. It is said to come in three variants, one with 6GB RAM + 128GB storage, another with 8GB RAM + 256GB storage and the top most version with 12GB RAM + 256GB storage. In line with the latest rumours, the phone’s storage is said to be UFS 3.0 Nand flash but there’s apparently no microSD card storage support. 

Coming to optics, the OnePlus 7 Pro is confirmed to feature triple rear cameras. The listing tips at a 48MP Sony IMX586 sensor with f/1.6 aperture, and OIS support. There’s The secondary 16MP wide-angle sensor is said to be paired with a f/2.2 aperture to deliver 117 degrees FOV, and a tertiary 8MP sensor with f/2.4 aperture, 3x optical zoom and 78mm focal length could also be present. The main camera is touted to support Phase Detection Auto Focus (PDAF), along with Laser AF and Continuous AF. The phone’s main camera should be capable of recording 4K video at 30fps/60fps, 1080p videos at 30fps/60fps, 720p videos at 30fps, and super slow motion 1080p and 720p videos at 240fps and 480fps respectively.

On the front is a 16MP Sony IMX471 sensor with f/2.0 aperture, EIS, and 1080p, 720p video recording support at 30fps. The handset might come equipped with stereo speakers and might be backed by a 4000mAh battery that supports Warp Charge 30 (5V/6A). While Quandt is a fairly reliable source, we suggest you exercise some skepticism since very few details about the OnePlus 7 Pro are official..

OnePlus 7 Pro leaked pricing

If Quandt’s report is to be believed, OnePlus 7 Pro might turn out to be more expensive than one might expect. The company is said to charge EUR 699 (Rs 54,700 approx) for the 6GB RAM + 128GB storage option and EUR 749 (Rs 58,600 approx) for its 8GB RAM + 256GB storage variant. The top-most 12GB RAM + 256GB storage option could cost, wait for it, EUR 819 (Rs 64,100 approx).