The following article is my attempt at exploring a niche market of Smart IoT Door Locking Solutions and partially investigate how Big Data analytics could improve this specific sector and thus also our personal life and home security. 

Smart Door Locking IoT Solutions

The Current State

The existing Smart Door Lock solutions help homeowners to solve a very common family environment problem, that of locking and unlocking of doors. Some of the more sophisticated devices currently available for purchase are the smart door locks that are completely keyless and work by communicating with homeowner’s smartphone over the network. The present smart door lock devices are already changing the way we interact with our houses and make the regular metal keys essentially obsolete. The development in this area is also amending the way we see our smartphones. In addition to more common usages of smartphones, in which they act as cameras/camcorders or music/movie players, they will also fulfill a new function, that of a smartphone key to our own homes and businesses.

The Future IoT devices

However, let’s talk about the newest entries into the space of Smart Door Lock solutions, the devices that are adding a fresh new spin on an issue of controlling the entry access to various physical objects. The newest IoT devices come equipped with sensors such as Near Field Communication (NFC), ZigBee / Z-wave or low-power Bluetooth, that allow smart door locks to communicate with homeowner’s smartphone or smartwatch. The new IoT smart doors can unlock itself whenever the authorized user is in the proximity of the house, they allow its users to lock or unlock the door remotely, and also permit the sharing of home access right with other family members or visitors – it is all done through an app.

Grand View Research report claims that “The global smart lock market size is to reach USD 24 billion by 2024” (Research, G.V., 2017). It shows that the smart door market will grow almost exponentially, demonstrating the fact that most property holders prefer the new smart-home security, the overall easiness of use and other benefits of using digital door locks.

Smart Door Locking IoT Devices and Big Data

What are the specific benefits that could be achieved with Big Data?

It seems that this area is almost entirely unexplored, as none of my research had yielded results for using Big Data solutions with Smart Door Lock solutions. This forced me to think a bit out of the box about the potential benefits of Big Data in relation to new IoT devices. Following are just some of the ideas that I explored.

**Smart Door Locks and Big Data **

Please note that most of the ideas below imply the situation in which the data from all smart door locks are collected by a central control body, either a manufacturer or a local municipality.

- **Improvement of Traffic Control Signal Systems**

Forecasts say that “by 2050 about 64% of the developed world and 86% of the developed countries will be urbanized” (Economist, T., 2012). It means that the major cities will need to deal with increasing number of challenges and among those, the problem of urban movement will be one of the most severe.

That said, we require better ways to monitor the total numbers of cars on streets because that is one of the best indicators for forecasting when the traffic problems. Currently, most of the large cities lack the ability to know when the most cars hit the streets and thus “it is very common for someone to wait for a traffic light to become green even if there is no car in the street.” (G. Costa, and G. S. Bastos, 2012). Such problems intensify the traffic jams instead of helping signal systems to work in a role of a traffic controller.

The way I envision Big Data helping in this area is to use the data collected from all smart door locks. Ideally, they would be stored in a central municipal database, on which we can periodically run the analysis whose results we could feed directly into a centrally managed traffic system that improves the control of traffic signals. In my opinion, knowing the exact time when people are arriving or leaving home from work, for each of the city neighborhoods could improve the adaptive urban traffic control systems. Having access to smart lock information, would allow us better predict when to turn on the green lights and better resolve the traffic congestions. Figure 2 displays the typical adaptive urban traffic system that controls city lights. I imagine the data from smart door lock systems to come as one of the inputs.

Figure 2

Image © Smart Traffic Lights (2015)

- **Optimizing Police Patrol Routes with Enhanced Algorithms**

Most smart door locks are bought with an intention to ease the way in which we enter our houses and businesses, but the main purpose to invest into buying one of these devices is to prevent the crime. This is confirmed by the most recent research which claims that “The increasing crime rate globally has fueled the adoption of the smart lock devices in the enterprise segment.” (Research, G.V., 2017).

Moreover, when we talk about crime, one of the most important things is the speed of police patrol reaction to reports of a robbery. As a matter of fact, the police patrolling is still the best way to ensure public safety and battle variety of urban crimes. Unfortunately, “the specification of successful police patrol routes is by no means a trivial task to pursue, mainly when one considers large demographic areas.” (Reis, D., Melo, A., Coelho, A.L.V. and Furtado, V., 2006).

The way I envision Big Data helping in this area is to use the data collected from IoT smart door locks, more specifically that these devices would report the occupancy rates of each of the police patrolled neighborhoods. Such Big Data analysis would tell police which areas are more susceptible to crimes such as robberies and assist police in better detection of crime hotspots. Police departments could predict the areas, specific homes or businesses which would likely become targets of robberies. For example, the data analysis from smart door locks could tell which houses are unoccupied due to vacations, or due to other specific conditions, allowing police to improve coverage of those areas by the routine patrol surveillance.

As we can see, the Big Data and IoT devices could work hand in hand, paving the way for new evolutionary tools that could assist police managers, letting them plan more efficient police patrol routes and strategies. If such analysis is used effectively, the Big Data Smart Lock solution would certainly have a potential to make our neighborhoods safer.

- **Energy Companies, Smart Locks and Big Data**

When it comes to smart door locks and Big Data, many other opportunities come to mind. One of them that deserves mentioning is the use of Big Data analyses to design more intelligent power grids.

Energy companies that deliver power and other connected services could use data from smart door locks to build Big Data solutions that improve the design of the electricity grid as well as enhance the inflexible regulations. The way I envision Big Data and data collected from smart door locks helping in this area, is mainly to provide data about the current occupancy of each of the city neighborhoods. The data from smart door locks combined with those from smart meters would empower energy companies with a new source of knowledge, that could be used to build the new smart systems. New regulation devices using the power of Big Data would not need to power all areas of the power grid uniformly but instead based on the up-to-minute data automatically decide which grid requires more electricity. Such systems would not only provide the tremendous cost savings but also assist in the prevention of power outages.

IoT Smart Locks and Processing Big Data

One of the questions that arise immediately when we contemplate implementing the Big Data and Smart Door Lock solution is the issue of collecting and processing Big Data from all the IoT smart locks. Not only these devices come from multiple vendors, but data may come in a variety of different formats. In my opinion, the issue of processing data from all smart locks is to some extent a problem of security, regulation, and standards. There are numerous advantages in standardizing the format in which we collect the data, but those issues we can overcome as long as data are adequately described with metadata. Thinking about it, one way to resolve the problem is to create a standard for remote communication with IoT devices in general.

One of the biggest advantages when it comes to centralizing the input from all smart door locks is offloading the data collection as well as data processing to the cloud. Cloud would offer key advantages for big data initiatives such as centralizing data from IoT smart lock solutions. This article is not the venue to go in depth into are of cloud benefits, but some of the most important are reduction of cost, more secure data storage, scalable infrastructure, big data analytics operations in one central environment.

The best practices and criteria of NIST Big Data Interoperability Framework are the best place to start because for the general public to be willing to offload data from their IoT devices to cloud, we must first ensure the secure communication.

IoT Smart Locks and Security

One of the issues that would bother me the most is the issue of security, especially when we are suggesting to provide data from smart door locks to a central repository used by government or other agencies. Matt Reaney from BigCloud.io, provides one of the best summaries of the issues of smart door locks, he states that “At least, when you lock your door behind you, you know that there is a physical barrier to entry. If people can hack the Pentagon (it happened), then what is stopping someone from hacking your home?” (Reaney, M., 2017).

The security of IoT devices, in general, is perhaps the major issue at hand. As for me, I am counting myself among those people who are currently not considering adoption of the new IoT smart door locks. I will wait until the new technologies are proven.

In DEF CON 2016, researchers, A. Rose and B. Ramsey demonstrated that it’s in fact very easy to compromise the smart IoT door lock devices. They’ve shown that by using a cheap hardware, they could jeopardize twelve of the low energy Bluetooth smart locks currently sold on the market and hack their way into unlocking the door.

As we all know, it is not easy to hack a physical door key without having physical access to it, but that is not the case with smart door locks.

“The home is your personal space where you can escape the worries of the outside world. If you let the outside world in, where then is your psychological refuge?” (Big data will rule your home, 2016).

Conclusion

In the next 5 years, customers are expected to spend close to “$6 trillion dollars” (Greenough, 2016) on different Internet of Things (IoT) solutions entering a number of different markets, ranging from agriculture and transportation to various other connected home solutions. HIS Markit in the 2016 IoT Platforms white paper predicts there will be 75 billion installed IoT devices by 2025, a steep progression in the uptake of IoT devices from 20 billion devices currently installed (Figure 1).

Figure 1

Assuming the prediction is correct, the days of IoT are here, and we will soon need to build analytics platforms that can perform and provide enough space for the future growth.

However, to setup and analyze data from smart door lock or any other IoT devices that plan to utilize the Big Data analytics, will first require building a basic trust in the security of the data we plan on collecting. Only then will various organizations be able to create new Big Data IoT platforms that can improve many areas of our lives.

I will conclude this article with a quote from Kaushik Pal of Data Informed: “IoT and big data basically are two sides of the same coin. Managing and extracting value from IoT data is the biggest challenge that companies face.” Pal, K. (2015).

References

Reis, D., Melo, A., Coelho, A.L.V. and Furtado, V. (2006) ‘Towards optimal police patrol routes with genetic Algorithms’, in Intelligence and Security Informatics. Springer Nature, pp. 485–491. [Last accessed 21 Jan. 2017].

G. Costa, and G. S. Bastos (2012), Intelligent traffic: An application of reinforcement learning, XIX Brasileiro de Automática, ISBN:978-85-8001-069-5, Campina Grande/PB – Brazil (Accessed: 21 January 2017).

NIST.SP.1500-3 (2015). NIST Big Data Interoperability Framework: Volume 3, Use Cases and General Requirements. NIST Special Publication 1500-3. [Online] Available from http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1500-3.pdf [Last accessed 21 Jan. 2017].

Markit, I. (2017) Whitepaper: IoT platforms - enabling the Internet of things. Available at: https://www.ihs.com/Info/0416/internet-of-things.html (Accessed: 22 January 2017).

Smart Traffic Lights (2015) Towards smart traffic lights using big data to improve urban traffic II. Available at: https://www.thinkmind.org/download.php%3Farticleid%3Dsmart_2015_2_30_40061+&cd=1&hl=en&ct=clnk&gl=ca (Accessed: 22 January 2017).

Greenough (2016) Here are IoT trends that will change the way businesses, governments, and consumers interact with the world. Available at: http://www.businessinsider.com/top-internet-of-things-trends-2016-1 (Accessed: 22 January 2017).

Pal, K. (2015) The impact of the Internet of things on big data. Available at: http://data-informed.com/the-impact-of-internet-of-things-on-big-data/ (Accessed: 22 January 2017).

Research, G.V. (2017) Smart lock market projected to reach $24.20 Billion by 2024. Available at: https://www.grandviewresearch.com/press-release/global-smart-lock-market (Accessed: 22 January 2017).

The growing market for smart door locks (2016) Available at: http://futurelab.assaabloy.com/en/wp-content/uploads/sites/2/2016/10/Smart-Home-Security-Report-2016.pdf (Accessed: 22 January 2017).

Reaney, M. (2017) Big data will rule your home. Available at: http://www.kdnuggets.com/2016/03/big-data-rule-home.html (Accessed: 22 January 2017).

Economist, T. (2012) Open-air computers. Available at: http://www.economist.com/news/special-report/21564998-cities-are-turning-vast-data-factories-open-air-computers (Accessed: 22 January 2017).

Big data will rule your home (2016) Available at: http://www.bigcloud.io/big-data-will-rule-your-home/ (Accessed: 23 January 2017).