May 19, 2017 | Written by: Jayant Hardikar
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IoT technologies are already well under way to revolutionize every industry ranging from transportation and buildings to manufacturing and environment. With the explosion of sensors, sensor data, innovative ideas of how to harness all the data and vendors who are implementing solutions, there is a real danger of causing data fatigue for the organizations using these solutions, not to mention the end-user or consumer.
The case of the missing elevator
The building in which my parents live in India has an old fashioned elevator with sliding grill elevator doors on each floor. The grill door acts as a safety device. If it is not slid shut manually – completing the electromagnetic circuit – the lift won’t move. However, if after exiting the elevator a passenger neglects to shut the outer grill door, the elevator will remain on the last floor serviced – creating frustration for the next passengers who inevitably send a neighbor’s son or daughter to climb the stairs in search of the lift stranded on an upper floor with its brass grill wide open.
A poor retrofit experience: the hissing elevator
After residents persisted with numerous complaints about unsatisfactory experiences, the building operations team installed sensors to detect when the grill door was open or closed. If open, the system triggers the voice recording of woman demanding, “Please shut the door” in three languages. The recording continues to cascade through speakers on every floor until at last someone steps into the hallway and slides the grill door shut, sending the errant lift to its destination.
Not surprisingly, after the novelty of the talking woman wore off, the residents found her announcement more irritating than useful – as the recorded voice seemed to bark commands at them the from the second they entered and exited the elevator door. The presence of the angry elevator voice now made the passenger experience even worse – resulting in them hurrying to exit the elevator, ending their less than optimal experience as quickly as possible.
I can attest to the experience personally. On my last visit, as I approached the elevator, I was accosted by the voice recording of an angry woman shouting incessantly through the intercom. In defiance, rather than comply with her commands, I noticed the people on the ground floor simply ignored the message – continuing on with their business, oblivious to her demands. With no lift in sight, I bounded up the stairs instead, a pattern which repeated itself throughout my visit.
The residents had grown accustomed to the harsh vocal warning. Instead of responding to her plea, and helping other residents, they ignore it. As a result, the occupants of the building are now left with an even worse user experience – long waits, no elevator door in sight, and the nagging voice of the recording.
There are two common causes that lead to data fatigue for users of IoT solutions:
1. Bad design for human consumption
Yes, technology can be awesome; but, without carefully considering the user experience when implementing a ‘solution,’ sometimes the impact of the solution leaves individuals in an even worse situation. Thinking through to the end-user’s problem first and considering the human reaction to the user experiences can help avoid similar catastrophes. How we as humans interact with technology influences the success or failure of any solution; the value we ascribe to the technology affects how readily we adopt new technology.
2. Stove pipe solutions
Another implementation trap which can be equally detrimental to successful adoption occurs when we try to solve too many IoT problems as individual point solutions. This can potentially lead to crossing the threshold of a user’s ability to process new information. Redundancies can also cause inefficiencies in the systems themselves. Did you know hospitals reported 80 deaths and 13 severe injuries attributed to alarm hazards from January 2009 to June 2012? When it comes to the field of medicine, alarm fatigue is dangerous and, indeed, is a hot topic in the medical community.
IoT for buildings
Managing a large commercial building requires answer to questions such as:
- How bad is the plumbing leak in the basement?
- How many pounds of salad should I make for lunch in the cafeteria today?
- Which windows and doors are causing heat loss?
- How much power is the 5th floor using compared to the average number of occupants on that floor this month?
- Which parts of the elevator are close to the wearing threshold and need replacement right away?
Thousands of sensors feed data into the building’s “IoT brain” to answer these and other questions. There are hundreds of ways to design solutions to answer such valuable questions. This can easily lead to high likelihood of data fatigue for the users.
Avoiding data fatigue
To avoid IoT implementations that cause data fatigue – rendering potentially good solutions ineffective, solution developers should consider following these four constructs:
1. Put humans at the center
Ultimately it is indeed people who are the beneficiaries of data insights derived through IoT solutions. Regardless of the objective – whether it’s for comfort, safety or operational efficiency, using a human-centric design approach is one way to create better solutions.
First, understand the end-users’ persona, how they work in their environment, what they are trying to achieve; how users interact with data or insight; how much capacity they have for information; pay attention to human behavior to understand their responses when interacting with the IoT solution. Consider the user’s perspective – what frustrates them now, and what will make them happier? This recent article demonstrates that indeed “People are the point of IoT,”. In addition, explore IBM’s Design Thinking methodology – a methodology which advocates using a human-centric design point.
2. Keep the big picture in mind
Developing disconnected or individual point solutions for very targeted problems can have an inadvertent impact on something else. The same user may be responsible for watching and managing multiple systems. So, design for a comprehensive set of scenarios – as an example, ensure that the audio or visual notifications for a building security breach is clearly different than that for an electrical failure.
Also, avoid collecting and managing the same data more than once. Designing and maintaining a “Digital Twin” that is comprehensive across all systems and departments can help avoid unnecessary redundancies. Having a complete virtual representation of all systems and processes in a building allows an organization to leverage valuable data across systems to deliver higher value at a reduced cost.
3. Automate all low risk actions
Design software solutions that can make as many decisions and take as many actions as possible without human intervention. For example, in a solution that manages bathrooms in a commercial buildings, the “out of paper towels” alert triggered by a sensor should automatically place a service order for replacement, rather than simply notifying the manager who then has to place an order manually.
Automating low risk tasks will help reduce frustration for users and also result in greater cost-savings. It is important, however, to always ensure that the automated decision or action is indeed what a human would have chosen – i.e. remember to always put the human being at the center of software design!
4. Deliver higher-order information, not just data
There are many scenarios where the system cannot make a decision and take action on its own without human intervention. In this case, designing the system to provide the highest order information possible will allow humans to make better knowledge-driven decisions, in order to take subsequent actions quickly.
For example, if the system detects a plumbing leak in the basement and the automated action to shut off the appropriate valve fails, human intervention is immediately required. But rather than simply sending an alarm for the water leak and an alarm for the valve failure to a maintenance dashboard, one should design the system to provide higher order analytical information to the user.
In this scenario, rather than simply notifying the user of the failure alarms, inform the user about the extent of damage, a projected time indicating when the next major impact from the leak will occur, a headlight into any other high risk systems which could be impacted – is there electrical wiring nearby; the reason for valve shutoff failure and a list of the three next best action recommendations. Achieving this level of systems analysis requires sophisticated instrumentation and data analysis.
With sensors and a comprehensive Digital Twin of the building in place, develop Machine Learning algorithms to run prediction models based on historical data, events, and actions to make recommendations. The article entitled, “Watson IoT Platform Analytics – Covering all your IoT analytics needs,” explores the many capabilities available in the IBM Cloud to help build intelligent IoT systems.
How big is the data fatigue problem?
There is a lot at stake for human beings in this IoT revolution. The risk of data fatigue is real in every IoT implementation. The negative impact of ignoring the recording of the angry voice in a five-story residential building in India is a simple example of a pervasive issue. While it may seem insignificant to the buildings residents, perhaps even tolerable, imagine the scale of such a problem inside an office building with 75 floors.
The instrumentation throughout an urban sky scraper includes miles of plumbing, electrical and HVAC ducts, thousands of windows and doors, countless smoke detectors, multiple banks of elevators, cafeterias that serve thousands of people a day, gigantic parking garage underneath, 10s of thousands of computers/devices, network connections.
The sheer volume of data created and managed in the Digital Twin of such a building can easily cause data overload and badly designed IoT systems can quickly overwhelm and cripple building operations and safety, or frustrate the tenants.
Designing IoT solutions with humans at the center, keeping the big picture in mind before creating solutions, automating as much as possible, while delivering decision-making information, not just data are sensible constructs worthy of consideration.
The elevator saga continues
Continuing on with my encounter with the elevator in India, on one occasion, as the elevator descended with me as its single occupant, it suddenly halted in between the 2nd and the 3rd floor – where I was assaulted with the voice recording barking in my ear: “Please close the door…”over and over again. Someone had managed to open the grill door on some floor while the elevator was moving, thereby stopping the elevator immediately and the people nearby ignoring the cry wolf!
My cry for help was met by the building maintenance worker. His calm demeanor told me that this was not the first time someone had gotten stuck in between floors. His actions that followed left me amazed and amused. He took out his mobile phone and called, perhaps, his assistant and said in a monotone voice, “so… the elevator is stuck again. Bring me my Phillips-head screw driver.”
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