Healthcare and Wearables

In the context of healthcare electronics, the advent of the wearable devices  and  the Internet of Things (IoTs) are going to revolutionize the age tested hospital system. The major challenge in modern healthcare services is to provide quality medical care  at affordable prices for the large number of seekers.  The emerging field of  low power electronics and the miniaturization of devices makes the wearable devices the best choice for personalized healthcare.

The concept level model for this system is to propagate the so called "health begins at home" . In other words this means to redistribute the load of the healthcare management to a wider community of health specialists, so that an equality of health related services is rendered. According to my broad (maybe vague) perception of medical field, each individual needs to undergo the three steps of Diagnosis (Prediction), Prescription and Prevention - which is easily remembered by the 3 P's. This is very similar to the analytics which our present day data scientists are familiar with. The model henceforth develops into a stronger hierarchy of medical institution, which now translates into home medicine, primary health centers,  general hospitals, speciality hospitals and research institutions in medicine. The goal in the mind of the IoT healthcare community is to come up with wearable systems (eg: gadgets) that may equip each individual to be better informed about their health status in tandem with the best in house medical doctors to be allocated 24 x 7. 

Vehicle automation towards self driving cars

In this age of machines, humans are going automatic.

Anyone who hears this is bound to believe, something is wrong. What is really meant by automation? The term automatic refers to an activity that is performed without a person to directly control it. So,  is the action performed really independent of the person who initiated the process? To analyse the scene further, what really is unknown in the automated system is the knowledge of the controller/ initiator. This is a game changer - how can one remove the knowledge of the controller and inscribe it on the product. These threads of questioning  suggests that in automation human involvement is hidden but not completely made invisible. The debate over automation being beneficial or not is present among many communities. The importance should thus focus upon whether a middle path between human resource and automated resource can be made. In the past we have witnessed technology playing a key role in changing human values and attitudes. The current attention in this post is to establish such a compromise approach to better utilize the current resources (human as well as machines/automated) to uphold the integral human values - viz - equality, environmental consciousness and human safety.

The current attention surrounding self driving cars is motivated by several human factors which makes the roads busy and unsafe. The reliability factor in such systems is the use of vehicular communication systems and efficient sensors. However, the main human factor in the cities is solo driving. So the natural question is if the effective use of the road real estate possible with vehicle automation. This needs not just automation, but some technology that can change the human attitude. One solution for this was given through the integrated transport app (in the blog post : Travelling that .. ). This article discusses one step ahead. The intend is to make possible  a system where the user can rely on his vehicle to reach the nearest public transport station and enable the car to self drive back home. In such a situation, people would be keen on better utilizing the existing infrastructure.

Travelling that goes smart

Travelling and transportation are posing as a main challenge in the face of  developing India. At one end we have wide classes of vehicles on the road - starting from four seated motor bikes to, small cars, medium cars, luxury cars to busses and trains. Still we experience the scenario of a passenger standing on the foot board of the public transport system. With these setbacks, India has the advantage that it is well connected  by cellular mobile phones. It is the right beginning to think about a integrated app which is a solution for all personal transport requirements. In this context it has become a possibility to use the pooling system of online cabs which is well developed.

The idea here is to provide a one place integrated transport solution, ie the user can get a comfortable hassle free travel from place A to place B. The integrated solution comes in the form of a mobile app. The app requires a social login, for instance Facebook or Gmail or Twitter. On completion of the signing in the user will be enquired about the start point and the destination. The choices present would be a public transport system a pool system or a private owned car. The map shall also come up showing the social friends in nearby locations who are willing to pool. The integrated solution for the public transport is  a door to door service which will be taking the needs of the passenger from the staring point to the final destination. The door service is to be available with help of Autorikshas and taxi cabs.

The integrated transport system is automated to collect the cash in the form of mobile wallet. The public transport system option is flexible as it allows for seat reservations. The possibility of seat reservation is possible by ensuring connectivity between the vehicle and the "transport" server.

The Indian Scenario

The Indian transportation planning is quiet distinct from the ones that are addressed in the West. The major drawback is the lack of viable real estate and infrastructure to cater to the needs of the population. In many a places, the public transport exceeds its "capacity"(if there is one) and literally there is not a piece of land where one can put his/her feet. The incorporation of the integrated app is to benefit the commuters in atleast two folds. Firstly, the commuters  becomes aware that the world is a place where one has to live and let live. Public consciousness is the key attitude shift that can be brought. Since the app can make personalized suggestion on choosing the fastest, cheapest or the greenest routes - she/ he is made to think twice before using her/his own private vehicle.  Second, the system can be used for accurate and real time survey. This means that we can replace the present system where the bus conductors note down the number of passengers who covered  a certain distance,  The data set obtained from the app is a boon for the transport coorporation for the city or the state since the real data is available, while planning for additional routes or on optimizing the trips or even in efficient budgetary allotment. 

A Final Note

The number of people who owns a private car does not tell anything about the development of a country, but what matters is the productivity that is derived by the public transport network. This is the right eye opener for many of the nation planners to invest more on optimizing the available resources rather than to build expressways and fly overs.

Elements in the pedagogy for the future IoT revolution

The internet of things is going to transform the way we perceive the objective world. The world is getting more and more connected with multiple devices available.  This post is a reflection on my recent encounter with the the use cases of the Internet of Things (IoTs) in education and academia There a pressing need for us to invest on the human resources for developing the current IoT. If there is lot of potential in IoT, then the need to train our younger generations is also high.

The IoT mania is more hyped than reality. In reality, we are not trying to do something that is entirely new. But IoT is just another way of getting things done in a smarter, simplified and user friendly manner. The whole jargon blinds us of many things that we can/have fundamentally deal/dealt with. For instance, has anyone thought about the number of multimedia content that gets transferred across the internet and the cloud. Is there that theoretical "infinite" storage that is available to us to store this on the clouds? Here comes the savior in the form of Wavelet and Time-Frequency transforms. A fundamental theory that has developed more than a 50 years back, comes into action in a beautiful coincidence to solve a Big Data issue. Looking at the various layers of the communication stack in the current, IoT can back on a huge legacy network if it gets focused on the specific constraints. The IoT is going to make access to every possible sensed data at any place. In a nutshell, it becomes an all pervasive network.

The key drivers in IoT is surely the ability to handle data. Are we prepared for that ? Some key anticipations in the industry goes in the areas of low power, storage and integration of the hardware software peripherals. The answers to all these are open as of today. The 50 billion or the a trillion devices by 2020 .. how can one possibly give a network address to each of these.

If the technologists claim it to be the next biggest revolution after the industrial revolution in the early 18th century, then we better get ready. - the earlier the better. There are a variety of starter kits for students to pick up early. Specifically, there needs to be training in the following aspects : sensing, networking and actuation. An undergraduate IoT lab facility is strongly required.


Navigate to IoT Lab.

Physical Layer Security Using Energy Harvesting Models

This article has appeared in the Technical Article Board of ECE Department, SSET - June 2016

Abstract

A point to point communication with a receiver and a single transmitter is the system under study. We consider the security aspect at the physical layer of the wireless communication transmission in the presence of an eavesdropper. A combination of techniques involving the channel state information(CSI) and energy harvesting information(EHI) is used to ensure the security. The experimentation is performed using the NI USRP 2920 hardware.

Extended Abstract

ireless communication systems consists of a transmitter and many distributed receivers. The eavesdropper is an unintended node that tries to know what the wireless transmitter sends. The eavesdropper can cause security hazards to the intended receiver by causing leakage of the message and causing intentional manipulations. These manipulations can in turn, lead to wrong message being delivered. The wireless physical layer is the lowermost level of the 7 layer OSI (Open System Interconnection) model. In many existing systems the security aspects are dealt mostly at the link layer and the network layer. These schemes have their drawbacks like, complex cryptographic cyphering, power consumption, hardware cost to name a few. Physical  layer security is destined to be the future, where systems can be implemented in low battery power devices using improved simplicity. 

The physical layer security is dealt with the help of the CSI information available at the transmitter and receiver[1]. The CSI information is independent at the eavesdropper and receiver. This helps us to manipulate the order of the interleaving bits. The scheme of the interleaver requires that the channel state observed by the receiver and the eavesdropper are both independent. This prompts us to look for methods that are statistically independent with the users, but at the same time observable. In this context we try to provide a scheme that is a combination of the CSI and the proposed scheme of Energy Harvesting Information.

Courtesy : https://arxiv.org/pdf/1505.07929.pdf
Fig 1: Communication and Security Model

Harvested Energy Model 

We consider the case of a device that is capable of harvesting/collecting renewable energy from sources such as solar, wind, piezo, etc. In general as energy impinges on the photo sensors(in the case of a solar panel) some part is lost in the conversion process to electrical energy. Thus, the harvested energy at any given time is high or low, ie a Bernouli random process. Depending on the position of the device the amount of energy harvested (say in a block interval) is an independent sequence. So the interleaving pattern can be made a function of the random energy harvested.

Fig 2 : The Block diagram of the OFDM scheme using the Energy Harvesting Information (EHI)

The schematic for the physical layer security using the OFDM scheme is described. The channel is estimated and used as an input to the interleaver along with the energy harvesting input. The combined inputs fed to the interleaver will allow for an improvement in the security and decoding performance. The system has been tested under the USRP test condition with the the eavesdropper being placed in a separation. Initially channel measurements are performed using perfect channel knowledge. Later it is modified to the case where in the absence of the perfect channel state information, an estimation is performed at both the transmitter and receiver.

Reference

[1] H. Li, X. Wang and Y. Zou, "Dynamic Subcarrier Coordinate Interleaving for Eavesdropping Prevention in OFDM Systems," in IEEE Communications Letters, vol. 18, no. 6, pp. 1059-1062, June 2014

[2] Universally near-optimal online power control for energy harvesting nodes
D Shaviv, A Özgür - arXiv preprint arXiv:1511.00353, 2015

This is joint work with a M.Tech student at the Wireless Communication Lab, SSET

Going without a Jerk

This article is a republished version of the Technical Article Board at SSET

Abstract

Potholes on the road are a great threat to motorists using the highway. Currently there is very little infrastructure to locate these and repair them in a timely manner. This article presents a method to report the exact location of the portholes without any manual step. You just need to put a smartphone in your pocket.

Introduction

The article here discusses the use of the accelerometer in the phone for detecting the potholes and reporting them to the civil authorities through a database. The database can be used to locate the potholes on a map and take remedial measures quickly. The work explained here has been an extension of that developed in Nericell by Microsoft Research Bangalore. The Nericell gives a map view of the locations that and provides extension to accident detection due to abnormal braking.

Prelims of Accelerometer

The accelerometer is a device used in every smartphone and is capable of determining the acceleration along each perpendicular coordinates – X, Y and Z. The measurements are taken relative to the acceleration due to gravity, \(g (= 9.8 m/s^2).\) The directions are illustrated below. Using the X, Y components accelerometer can measure the abnormalities in the road plane. Along the Z direction, abnormalities due to level shifts can be detected- potholes or bumps for instance.

X, Y and Z directions of accelerometer

How It Works

It is possible to determine the following from the 3 reported acceleration graphs.

• Breaking Detection – accident reporting
• Pothole Detection
• Speed detection

If \(x\) is the distance, then \(\frac{dx}{dt}\) is the velocity, and \(\frac{d^2x}{dt^2}\) is the acceleration. If we look into the higher derivatives of \(x\), it is possible to detect the changes is acceleration corresponding to sudden changes in the accelerometer signal. It is possible to identify the sudden spiking of the signal along the \(x\) axis and translate it a jerk. Now the intensity of the jerk is dependent on the speed of the moving vehicle. At high speeds (ie > 25 kmph) , the jerk is prominent, while the jerk is less noticed for lower speeds (ie <25 kmph).

References

Mohan, Prashanth, Venkata N. Padmanabhan, and Ramachandran Ramjee. "Nericell: rich monitoring of road and traffic conditions using mobile smartphones." Proceedings of the 6th ACM conference on Embedded network sensor systems. ACM, 2008.

Is the Nyquist sampling rate a fundamental limiting rate in sampling ?

This post is an assessment of the key assumptions of the  conventional sampling paradigm.

The conventional sampling process applies to Bandlimited signals, or in other words, signal spreads in the time axis. The process assumes taking evenly spread samples of the signal at a spacing depending on the maximum frequency component of the signal.

We analyze the question, if localization of information is allowed , will the Nyquist rate be sub-optimal. For instance, consider the signal and its sampling method:

Dynamic Programming Decision Making

All of us set certain goals and try to achieve them. What is the best way to keep track if you have taken the right decision?  Here is a quick method to keep track of your progress. Consider that you set a goal today, and you are trying to optimize all the actions in order to reduce the total cost. The cost here can be due to time, money, effort, social costs and others.

The idea is to incorporate a method to reach the optimum in a step by step manner that uses only the local information. We query that : "If I assume that I am optimal in the future, what action needs to be taken today to ensure a global optimum". This leads us to the answer that, the best way is to determine the best that you can do today, with the assumption that from tomorrow we are going to be optimal. This seems to be very suited to our current practice also. While we drive a car we put the gear to the right speed, so that we can endure the local roads and the nearby traffic. The goal might be distant but we always have to act optimally to reach there.  While spending we ensure that the basic needs for today is met. The savings also are done accordingly. Take the simple game of tic-tac-toe, here we are trying to see the local information in the game and trying to win or in most situations stop the opponent from winning !

Courtesy : http://experimental.designforfun.com

This approach of dynamic policy is widely employed in control systems and  communication. There are two things that we consider in this optimization problem, one is the value or the cost that is incurred due to our decision (actions)  and the second is the policy that we have come up with. So remember at the beginning of each day try to see that you are going to be optimum for 'today', because tomorrow will "take care for itself".

[Topic Courtesy :  Introduction to Stochastic Optimization, IITB]

On Decisions and Learning (Part II)

In the previous post, we have seen how the space and time constraints can affect the decision  making.  In this part, we extend the model to one of practical interest. Such a model should be robust across space and time variations. In effect we cover up the space and time and replace them by agents/players who affect our decision process. To illustrate with an example we take the case of a boy in say, Brazil and a similar aged boy in India. It is more probable that the Brazilian boy latches himself to football and the Indian boy would choose cricket with higher probability.

                     

The agents here is a representation of the culture and tradition - hence depends on the space. There can be agents representing time as well. For instance the decision on taking an umbrella before leaving the home depends on whether it is the rainy season or not. Rain is the agent here and hence represents time. Thus agents are the physical representation of the time-space (real) parameters. Another aspect of agents is that, there are certain agents that aid to the decision with more weight than certain other. Now there are decisions taken in accordance with logic, past experience, and predictions. Each of them has a correspondence with time - present, past and the future.

The process of making the decision can be summed up as \( f : (A_1,A_2, \cdots, A_k) \rightarrow  \mathcal{D} \). Here \(A|_1^k\) are the agents to be considered while taking the decision and the set \(\mathcal{D}  = d_1,d_2, \cdots, d_n\) are the decision choices. This model lacks the past learning that has been accumulated over time. To explain the learning in decision making, we can take the example of the man going out while it is raining (Agent = Rain). The man does not take the umbrella, and gets wet (Decision : No Umbrella). The next time he goes out in the rain he is reminded by the fact that he has got wet (which assumes a cost). Now it is possible to assign a cost of for the decision taken over a action set. Assume that the decision maker has learnt the decision taken over a set of agents till time \(T\). Now the system is opened and the learned costs are considered while taking the decision.

On Decisions and Learning (Part I)

An inquisitive mind always seeks the answer to this question, is the thing that I decide right? Has the trained mind in me educated enough to reach the "right" decision.

Decision making is a ever happening process in the world around us. Decisions may be taken for important as well as less important topics. The rightness of a decision is always debatable and often has a subjective element. So how does one take a decision, what elements are included in the process, and how the decision affects others. The three questions here has a strong theory in statistics. Let us parse each of them and look it in detail.

How does one take a decision?

Decision is a selection of a particular choice, from the given set of available choices. A decision may be prompted by a situation, which is both depending on space and time. So, deriving cues from the situation, any decision should particularly abide by time and space. Let us see a little example. Identically aged people live in a city and a village. Both fell ill (almost in the same time), and was taken to a doctor. The doctor in the city gave medicines in the form of tablets, while the doctor in the village asked the man to collect some herbs from the garden and have them. One can tell that space is the prominent factor in this example. The doctors decision complies with the locally available medicines. One may also expect in a closer analysis, that the domain of the doctor also plays a significant role in decision making. For this discussion we can avoid this possibility.

Now consider another example where time is the decision driver. A boy injured his knee while playing in the evening . Seeing the bleeding his parents took him to the local clinic for first aid. Imagine the same situation happening in the night. At this time, the parents have no access to the clinic, so they prefer to give whatever first aid is at home and later take up to the doctor if required. Time (and to an extend space) played the crucial role in this example.

We try to introduce some modelling. Consider a situation and \(n\) possible choices. A particular choice has to be picked. If one were to derive ideas from the examples presented, the decision \(D(S,t)\) is a function of the location and the time. Generally, space and time functions are difficult to generalize. So we somehow, avoid these by introducing a probability matrix over the choice. The simplification seems good, but did we handle the reality efficiently? Not really isn't it! What we did was to look into the decisions taken by us in the past and presented a distribution over those choices. From the point of view of an analyzer, this seems to be good. While the model seems to blind the decision makers view? One way to handle this is to bring in some dependence of space-time. The model should be robust to analyze and useful for the decision maker.

I leave this at a point for the reader to ponder a little :

Image Courtesy : olivergearing.com

Most of us act more or less according to this Importance vs Urgency model (logical planner!). We have a set of priority and the decision scheduling is performed by the urgency or the time requirement. Seems to convince why certain events require, us to wait in patience.

Separation of Common and Unique Information

In the last post we were discussing about examples of common and unique information and were trying to explore its options in relay communication. Let us assume that the each relay node gets a part of the  codeword \(C\). The relay nodes if equipped to determine the common and the unique part of the information it received can use more power on the unique information part and a comparatively less power on the common information part.

For signals like images, the common and unique separation can be done using a multi-resolution filter. The low frequency(slowly varying) part forms the common information and the two orthogonal bandpass filters forms the unique information for the respective relay nodes. 

Suppose the source node performs a 2 slotted TDMA transmission, and half the relay nodes observes the first TDM symbol and the rest of the relay nodes observes the second TDM symbols what is the optimum coding that will result in achieving the decode-forward capacity? It is not very clear as to say in which domain does the separation exist. In the case of images though, we said it is the frequency domain.

Now once the separation domain becomes clear, the common information can be allotted some power level \(P_c\) and the unique part can be allotted some \(P_{u_1}\) and \(P_{u_2}\) respectively. If there exists two relay nodes then the power spent on the common part needs to be only \(\frac 12 P_c\). The other potential is that the common information can be transmitted when the channel gain is low, and an opportunistic communication can be performed for the unique information when the channel improves.

Common Informations Around Us

There is a good analogy for explaining common information. Consider the news of the Indian Cricket Team winning a test match. It does not really matter from which source you heard the news. This is because the PTI has handed over the news commonly to all the "newsmakers". Now consider news of the retirement of SRT. The decision (and of course the feelings associated) about his retirement is only known to him (and his close people) and different media reports in its unique way. The uniqueness in the reporting generates new information, and as a reader (viewer/listener) it is required to gather all these distinct pieces of information. 

SRT Retirement

 

Lords Test Win

The two news instances explains the term common information or shared information. 

Relating this to the relay communication scenario, we can observe that if the source is able to send unique information to each of the relay nodes, then the relay nodes can be used to its full efficiency. But this is a seemingly difficult task. Natural information comes as a combination of common information and certain unique information.

Information needs to be processed at the source to identify the common and unique information, and  then passed on to the relay. Each relay hence acts only as decode-forward nodes capable of only re-transmission of the information.

Device to Device Communication

In a few years to come, we will reach a point where the number of computing devices will cross the total human population. This phenomenal growth of the wireless technology brings new avenues to improve its efficiency and capacity. Days will not be far where you can turn these computing devices into sensor nodes and energy harvesters. The trend now is to make one device talk with the others.

Courtesy: www.citizenwarrior.com

The network engineers are already in the process of shifting to Ipv6  to inter-network this mammoth figure of mobile devices. A physical layer engineer is also very concerned since the modulation and coding schemes have to be modified from top to bottom. We can try to see some aspects of this upcoming scheme using a human analogy.

Alice wants to communicate some message to Bob.  Now Bob is standing in a building which is adjacent to where Alice stays. If Alice shouts at the top of her voice, Bob will be able to hear. But Alice does not prefer that mainly because the message is confidential. So Alice does the following: Alice tells her assistant Charlie the message (not the complete message)  and asks him to convey it to Bob. Alice will now call Bob from the balcony of her apartment and tell Bob the part of message not conveyed through Charlie.

Courtesy: ourcountryroad.blogspot.com

So has Alice lost her voice by shouting? If she if afraid of that, she would   call her second assistant Don and pass the remaining part of the message through him.

It is nice to see some technical aspects of this message communication where Alice and Bob are the source and destination respectively and Charlie and Don are the relay nodes. We begin with the simple model where Alice has a direct channel with Bob.

\( y_C = h_{AC} X_{AC}+Z_C \), 
\( y_D = h_{AD} X_{AD}+Z_D \),
\( y_B = h_{AB} X_{AB}+ h_{CB} X_{CB} + h_{DB} X_{DB} + Z_B \)

 The goal now is to determine a coding scheme such that the common information in \(X_{AB}\), \(X_{CB}\) and \(X_{DB}\) is zero.