IoT Assignment: Case Analysis Of Auckland Water Management Project

Question

Task:
Case study
In 2019 rainfall in New Zealand is said to have been the lowest on record. Auckland council has imposed water restrictions in different stages across the region to reduce water usage. The decision to impose the restrictions was based on the available information on average water usage in different parts of the region. Auckland Council needs more accurate ‘realtime’ data to make more accurate decisions. More information about the proposed restriction stages and the decisions council has made can be found in this link https://ourauckland.aucklandcouncil.govt.nz/articles/news/2020/05/council-to-makedecision-on-water-restrictions/

Auckland Council has approached you as an IOT expert to research and identify best realtime data gathering solution keeping in mind the Auckland ecosystem. You must present your findings in form of a report.

Your IoT assignment report must

Identify and examine two cloud computing platforms that are currently been used for similar real-world problem.
Based on your examination in part A, make a proposal for the design and application of a system based on a cloud computing platform that helps Auckland Council to make accurate decisions for water restrictions

Answer

Executive Summary
Purpose: The IoT assignment is meant to give theoretical and practical knowledge to solve both familiar and unfamiliar computing situations and come up with viable solutions using the internet of Things (IoT). (Refer Appendix for more information).

Structure: The report is separated into two parts A and B. Part A discusses two cloud computing platforms that have been used previously to solve similar problem (case study of Auckland). Part B discusses a solution for the water crisis problem in Auckland using one of the platforms listed in A.

The solution presented here identifies the best way to gather this data, by identifying the variables, a platform and system design. Off the various platform researched and available I have selected the following two platform for the analysis: AWS (Amazon Web Services)and BizIntellia.

Findings: Based on the research conducted on the two platforms, the researcher’s recommendation for the city of Auckland would the BizIntellia Platform, for the following reasons:

Strong expertise on end node technologies, which is extremely critical in the data acquisition front. Without good plumbing, no IoT platform can be effective, no matter how robust them might be.
Other reasons being scalability, cost and references.

Conclusion: The researcher recommends an IoT platform from BizIntellia for the Auckland water management project. The system is proven in the field of water management, and commercially attractive too. Having knowledge of available water and its quality, along with various consumption points along with their demand, will allow better management of water in the city of Auckland. To solve the water shortage problem in New Zealand, the cloud computing platform Bizintellia was selected given the strong expertise on end node technologies, which is extremely critical in the data acquisition front.The system architecture would follow the 3-Tier architecture of the BizIntellia platform. IoT nodes/systems generate a lot of data that needs to be managed in order for it to be useful for any analysis purposes. The techniques that could be used to management the quantum and frequency of data from the edge nodes:

Determine the frequency of data capture and transfer for each node. For non-critical nodes, less frequent polling of data is recommended
For critical applications like gas leaks or water leaks or consumption of water from an unauthorised source, logic could be embedded at the node itself, where the system would shut down if required, if a condition/rule is met. This not only reduces the load on the central system, but also speeds up the response mechanism.

2. Introduction:

Purpose of the report identified
The Industrial Internet of Things (IIoT) is gaining a lot of momentum and is said to add about 14.6 trillion dollars to the economy by 2030. As of not long ago, the water business was fundamentally relied distinctly upon Supervisory Control and Data Acquisition (SCADA) framework which couldn't screen the whole water conveyance framework because of the down to earth confinement of its establishment focuses. Shrewd, financially savvy IoT frameworks are currently empowering information to be gathered in any part of a brilliant water framework that can be estimated with sensors. Typically, the data is then stored on a “cloud” and is available for analysis on a real-time basis or on an as needed basis across multiple platforms, including smartphones, handheld devices and laptop/desktop computers.Also, water information related to AI innovations can predict the status of pumps, networks, or capacity storages. Through these kinds of arrangements, water supervisors can pick up the capacity to fix breaks inside a water framework before episodes happen, sparing capital and material expense and expanding the return of capital. There are a number of IoT platforms that are available in the market, ranging from large, well established software companies such as AWS, IBM, Siemens, Hitachi, BizIntelliaand AWS and Temboo, to start-ups who are building next-generation IoT platform for industrial and home use.
Regardless of the provider, any industrial grade IoT platform should have the following core elements (Hitachi, 2020).
- Device management software that interfaces thousands to a huge number of sensors, mechanical machines and advanced frameworks. IoT arrangements are normally intended to recognize these shortcomings and encourage recuperation from them.
- Coordination through programming advancement units, improvement instruments and APIs to help business procedures and undertaking frameworks over the business. There are noteworthy difficulties, be that as it may, given the variety of back-office applications, for example, ERP, application execution the board, endeavour resource the executives, modernized support the executives frameworks and that's only the tip of the iceberg.
- Management of volumes of data to establish control and enable monitoring, storage and quick access.
- Investigation of information from associated gadgets, the venture and outsiders to uncover examples and improvement of advantages.
- To allow the executives of uses to disentangle arranging and working associated resources and that empower advanced twins.
- Programming to permit security reviews and guarantee consistence, including measures to forestall information misfortune and to identify and follow up on access breaches.
- Provide a framework of methodologies for various different industries, such as OPC (Open Platform Communications) Unified Architecture.
- Flexibility with no-code interfaces, for example, to allow a range of users to access job-specific applications.
- The combined results from deploying cloud computing services on the premise and edge computing.
- Without good plumbing, no IoT platform can be effective, no matter how robust them might be (Kamienski et al., 2019).
Based on my analysis, my recommendation would be the BizIntellia System due to is architecture, out of box solutions, ease of use, and proven in the water management industry. +
Background information of the problem
The assessment is meant to give theoretical and practical knowledge to solve both familiar and unfamiliar computing situations and come up with viable solutions using the internet of Things (IoT). The report is separated into two parts A and B. Part A discusses two cloud computing platforms that have been used previously to solve similar problem (case study of Auckland). Part B discusses a solution for the water crisis problem in Auckland using one of the platforms listed in A.
The case study, to summarise states the water shortage problem that New Zealand is facing due to extremely low rainfalls in 2019. To combat this, the Auckland Council imposed various restrictions in parts of the region based available information. However, in order to make better decisions on water management and policy implementation, the Council would require real time data. The solution presented here identifies the best way to gather this data, by identifying the variables, a platform and system design.
Brief description of cloud computing platform selected and the solution
The Industrial Internet of Things (IIoT) is gaining a lot of momentum and is said to add about 14.6 trillion dollars to the economy by 2030 (Desk, 2020). The advantages of IIot that make it so attractive include the capability for companies to predict when an equipment may fail giving it time to fix the problem and avoid this hiccup in the very first place. Another major advantage is asset management allowing manufacturers to optimize asset performance and production. Finally, it increases revenues and IoT can help formulate better solutions and innovate the business for higher returns. There are a number of IoT platforms that are available in the market, ranging from large, well established software companies such as AWS, IBM, Siemens, Hitachi, BizIntellia and AWS and Temboo, to start-ups who are building next-generation IoT platform for industrial and home use.
To solve the water shortage problem in New Zealand, the cloud computing platform Bizintellia was selected given the strong expertise on end node technologies, which is extremely critical in the data acquisition front. Without good plumbing, no IoT platform can be effective, no matter how robust them might be. The other reasons were relating to the ease of scaling, cost effectiveness and references. The methodology proposed is a ten-step process beginning from planning the requirements with stakeholders, then drawing out the solution design, budgeting and deadlines, together this would take 7 weeks. After getting the approvals, development and feedback phase begins, post which the testing is done, and bugs are fixed. The client is trained, and the plan goes live along with the supporting staff. The systems that would be monitored include water levels of various sources, water quality at these sources, Models from Metrological department on rainfall , consumption points. The functions that need to be monitored are also stated. The system architecture would follow the 3-Tier architecture of the BizIntellia platform. IoT nodes/systems generate a lot of data that needs to be managed in order for it to be useful for any analysis purposes. The techniques that could be used to management the quantum and frequency of data from the edge nodes:
1. Determine the frequency of data capture and transfer for each node. For non-critical nodes, less frequent polling of data is recommended
2. For critical applications like gas leaks or water leaks or consumption of water from an unauthorised source, logic could be embedded at the node itself, where the system would shut down if required, if a condition/rule is met. This not only reduces the load on the central system, but also speeds up the response mechanism.
3. For applications where local logic/control cannot be provided, then the data needs to be brought into the central system for analysis and actions.

3. Discussion: (A) Identify and examine two platforms

Platform identified
Off the various platform researched and available I have selected Amazon Web Services (AWS) and BizIntellia as the two platform for the analysis:
1. AWS IOT(Amazon, 2020)
2. BizIntellia("Best IoT Water Management Solution for a Sustainable Future", 2020)
BizIntellia
Examination of identified platform includes
- Identification of sub-system used
  - Bizintellia uses a typical 3-layer architecture for its IoT Platform.
  - The first layer is the sensor management layer.
  - The layer in between/ middle layer is the data receiving and management layer
  - The top layer is the business logic and application layer("Best IoT Water Management Solution for a Sustainable Future", 2020)
- Internet services used
  - The IoT sensors that are fitted on to the end nodes use LoRaWAN is essentially used to buil IoT networks and are a long range, low power wireless protocol (MAC protocol). LoRaWAN is a remote innovation where a low fueled sender for example end hubs transmits little information bundles (0.3 kbps to 5.5 kbps) as payloads to a recipient over a significant distance.
  - The IoT sensors communicate to a central controller using LoRaWAN technology. The central controller, typically 3 to 5 miles away from the nodes, communicate with the cloud software using TCPIP protocols.
- How the solution will be implemented
  - According to the company, a typical implementation is around 4 to 6 weeks (for about 1 dozen sensors and for configuring the application software for the specific business needs.
  - Field service engineers are required to install the end-node IoT sensors and the central gateway solutions and for testing the range, interference, safety, etc.
  - Application software engineers focus on the configuration of the platform on the cloud infrastructure.
- Benefits of using this platform
  - Quick implementation through several out of the box features
  - Very low cost (pricing begins at $2/month per node), which includes the cost of the node IoT sensor
  - Cloud based deployment, which means there is no IT costs
  - Reports and dashboards are available over smartphones and desktop
  - Good customer support
AWS IoT
Examination of identified platform includes
- Identification of sub-system used
  - AWS IoT architecture is based on web services (API).
  - Every application is an independent solution by itself, which can be then integrated with other services using API/Web services.
- FreeRTOS: Microcontroller software. FreeRTOS is an open source, constant working framework for microcontrollers that makes little, low-energy edge gadgets simple to program, convey, secure, interface, and oversee. Appropriated unreservedly under the MIT open source permit, FreeRTOS incorporates a piece and a developing arrangement of programming libraries reasonable for use across industry segments and applications. This incorporates safely interfacing your little, low-energy gadgets to AWS cloud administrations like AWS IoT Core or to all the more remarkable edge gadgets running AWS IoT Greengrass. FreeRTOS is worked with an accentuation on dependability and usability. A microcontroller contains a straightforward, asset obliged mechanism that can be found in numerous gadgets, including machines, nodes/sensors, wellness trackers, modern mechanization, and autos.
- AWS IOT Greengrass: Edge computing and decision making. This sits on the gateway and can be programmed remotely. This allows actions and decisions to be made locally based on local/node level information and events. With AWS IoT Greengrass, you can make use offamiliarlanguages and programming software/ packages to create and check your gadget programming in the cloud, and thereafter convey it to the used gadgets. AWS IoT Greengrass can be modified to allow information to flow from the gadget, deal with the life cycle of that information on the gadget, and just transfer fundamental information back to the IoT platform (here, AWS). You can likewise interface with outsider applications, on the location programming, and AWS benefits out-of-the-container with AWS IoT Greengrass Connectors. Connectors likewise kick off gadget onboarding with pre-constructed convention connector incorporations and permit you to smooth out confirmation through combination with AWS Secrets Manager.
- AWS IoT Core: This is the core data aggregator solution. This connects with the gateways in the field and aggregates information coming from the various nodes (IOT sensors). AWS IoT Core is acloud-based service for administration that lets similar gadgets effectively and cautiously cooperate with the cloud- based operations and dissimilar gadgets. AWS IoT Core can bolster billions of gadgets and high quantum of messages, with the ability to analyse and decode and then send these messages to the IoT platform (AWS) endpoints and to various gadgets with assured confidence/accuracy and security. With AWS IoT Core, the designed applications can oversee and communicate with each of the other one of your gadgets, constantly, in any event, when they aren't networked together. AWS IoT Core additionally makes it extremely easy to make use of AWS and Amazon administrations like AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service to fabricate IoT services and applications that assemble, process, examine and follow up on information created by associated gadgets, so as not to deal with any framework.
- AWS IoT Device Management: This application allows the user to manage the various IoT sensors in the field. WS IoT Device Management makes it very easy to safely enlist, sort out, check, and oversee IoT gadgets at scale from different locations. Using the AWS IoT Device Management, you can make a list ofthesimilar gadgets separately or in bulk, and monitor the functioning of the gadgets to check for accuracy and security. The many other functions and benefits range from being able to sort through the gizmos and check and analyse their usage. You can also send alerts to check the asset condition and call for any repair requirements over-the-air (OTA). AWS IoT Device Management is so sophisticated that it can help manage/ micro-manage the operations of various gadget types with different operating systems. AWS IoT Device Management allows for the scaling of the business/ model and helps to cut down on the expenditures and asserting themonitoring of seeing huge and differing IoT gadget organizations.
- AWS IoT Device Defender: this is the antivirus solution for each IoT sensor in the field.
- AWS IoT 1-Click: out of box solution for AWS IoT 1-Click compliant devices for managing events and actions, such as notifications, alerts, etc.AWS IoT 1-Click is an assistance that empowers basic gadgets to call for AWS Lambda works that can perform a said activity. AWS IoT 1-Click bolstered gadgets empowersthe user to effectively execute activities, for example, telling specialized help, following resources, and recharging merchandise or administrations. AWS IoT 1-Click bolstered gadgets are prepared for utilize directly out of the utility and bring out the requirement for composing your own equipment or modifying them for safe network. AWS IoT 1-Click bolstered gadgets can be handily overseen. The user is able to without much of a stretch make gadget gatherings and partner them with a Lambda work that executes your ideal activity when activated.
- AWS IoT Analytics: This module does the data analytics, and reporting function.
- AWS IoT Events: Manages events from various sensors and integrates with other services with AWS
- AWS IoT SiteWise: Similar to IoT Core, this module helps collect and manage data from various sensors at scale.
- AWS Things Graph: This is the graphical output module of AWS. Internet of things services have an array of utilities, are being constructed today utilizing an assortment of gadgets and web administrations to computerize undertakings for a various utilization cases, for example, savvy houses, mechanical robotization, and vitality the board. Since there exists no broadly embraced measures, it's troublesome today for engineers to get gadgets from various producers to associate with one another just as with web administrations. This powers engineers to compose loads of code in order to join all of the gizmos and web administrations they requirement for their IoT product. Amazon Web Services (AWS) IoT Things Graph gives a visual intuitive user interface for associating and organizing connections among gadgets and web administrations, so you can fabricate IoT applications rapidly. For instance, in a case for business farming application, you can characterize associations between moistness, the weather, and sprinkler sensors with climate information benefits in the cloud to mechanize irrigation. You speak to gadgets and administrations utilizing pre-manufactured parts that can be used again, called models, that conceal low-level subtleties, for example, conventions and interfaces, and are anything but difficult to coordinate to make modern work processes.
Internet services used
- MQTT protocol for communicating with the various field sensors.
- Standard Json protocols for API communications
- TCPIP protocol to communicate with the field controllers
Benefits of using this platform
- Scalable and elastic, as it is built over AWS platform
- API based access to several modules
- Interoperable with multiple end node device types
- Cloud based deployment, which means there is no IT costs
- Reports and dashboards are available over smartphones and desktop
How the solution will be implemented
- Since there are no out of box applications on AWS IoT for water management, the entire system needs to be configured per the business logic of the client. This typically takes 8 to 12 weeks depending on the complexity of the project and the skills of the developers.
- A detailed system architecture of the solution needs be developed first and the appropriate web services (APIs) need to deploy
- The APIs are then configured per the business logic to form the final solution.

4. Discussion: (B) Select and apply

Selecting platform based on examination in (a) with justification
Based on the above two platform, my recommendation for the city of Auckland would the BizIntellia Platform, for the following reasons:
1. Out of box solution for water management which reduces cost, complexity and risk
2. No need for trained programmers on AWS as they are expensive and in short supply
3. Easy to maintain as the system is configuration based, as opposed to programming based.
4. Strong expertise on end node IoT sensors, which is extremely critical in the data acquisition front.
5. Other reasons being scalability, cost and references
Development methodology
- Following is the methodology I would recommend for this project:
  1. Detailed requirements gathering phase with all stakeholders – 4 weeks
  2. Development of requirements document along with solution design, options, costs and implantation timelines – 3 weeks
  3. Sign off on the requirements and final plans – 1 week
  4. Development and go live in a phased manner – 1st go live of 1 to 5 nodes
  5. Feedback and changes as needed – 2 to 3 weeks
  6. Subsequent implementation – 4 weeks intervals
  7. Final User Acceptance testing – 3 weeks
  8. Bug fixes and enhancements – 2 to 4 weeks
  9. Training and system handover
  10. Go Live and support
Platform design
- Systems that would be monitored
  - Following are the systems that need to be monitored as part of the overall IoT plan
    - Water levels in the various sources (dams, ponds, lakes, etc)
    - Water quality in the sources
    - Models from Metrological department on rainfall
    - Various consumption points
      - Industries, sporting arenas, hotels and spas, commercial buildings, etc
    - Farming and irrigation systems
  - Following are the functions that need to be monitored
    - On/off state
    - Flow
    - Leakages
    - Volume
    - Overflow
    - Equipment uptime
    - Corrosion
- System architecture
  The system architecture would follow the 3-Tier architecture of the BizIntellia platform as shown below
- Signal flow diagrams
  The diagram below shows the flow of data/signals across the various components of the platform.
- Description of real-time data gathering and how analysis is done
  IoT nodes/systems generate a lot of data that needs to be managed in order for it to be useful for any analysis purposes. Following are the techniques that could be used to management the quantum and frequency of data from the edge nodes:
  1. Determine the frequency of data capture and transfer for each node. For non-critical nodes, less frequent polling of data is recommended
  2. For critical applications like gas leaks or water leaks or consumption of water from an unauthorised source, logic could be embedded at the node itself, where the system would shut down if required, if a condition/rule is met. This not only reduces the load on the central system, but also speeds up the response mechanism.
  3. For applications where local logic/control cannot be provided, then the data needs to be brought into the central system for analysis and actions.

5. Conclusions
In conclusion, I recommend an IoT platform from BizIntellia for the Auckland water management project. The system is proven in the field of water management, and commercially attractive too. Having knowledge of available water and its quality, along with various consumption points along with their demand, will allow better management of water in the city of Auckland. To solve the water shortage problem in New Zealand, the cloud computing platform Bizintellia was selected given the strong expertise on end node technologies, which is extremely critical in the data acquisition front.The system architecture would follow the 3-Tier architecture of the BizIntellia platform. IoT nodes/systems generate a lot of data that needs to be managed in order for it to be useful for any analysis purposes. The techniques that could be used to management the quantum and frequency of data from the edge nodes:

Determine the frequency of data capture and transfer for each node. For non-critical nodes, less frequent polling of data is recommended
For critical applications like gas leaks or water leaks or consumption of water from an unauthorised source, logic could be embedded at the node itself, where the system would shut down if required, if a condition/rule is met. This not only reduces the load on the central system, but also speeds up the response mechanism.
For applications where local logic/control cannot be provided, then the data needs to be brought into the central system for analysis and actions.

6. Recommendations
The Industrial Internet of Things (IIoT) is gaining a lot of momentum and is said to add about 14.6 trillion dollars to the economy by 2030. Managing supply and demand of water is of the utmost importance for any country, not just for New Zealand, given the growth in population, industrialization, and reduction in water supply from natural resources. As of not long ago, the water business was fundamentally relied distinctly upon Supervisory Control and Data Acquisition (SCADA) framework which couldn't screen the whole water conveyance framework because of the down to earth confinement of its establishment focuses.Based on the research conducted on the two platforms, the researcher’s recommendation for the city of Auckland would the BizIntellia Platform, for the following reasons: Strong expertise on end node technologies, which is extremely critical in the data acquisition front. Without good plumbing, no IoT platform can be effective, no matter how robust them might be. Other reasons being scalability, cost and references.

My recommendation is to start with a small pilot with two vendors to evaluate the system and the IoT sensors. After that, a decision could be made to go with one of them for scale out purposes.

7. Appendix
The Industrial Internet of Things (IIoT) is gaining a lot of momentum and is said to add about 14.6 trillion dollars to the economy by 2030. Managing supply and demand of water is of the utmost importance for any country, not just for New Zealand, given the growth in population, industrialization, and reduction in water supply from natural resources. As of not long ago, the water business was fundamentally relied distinctly upon Supervisory Control and Data Acquisition (SCADA) framework which couldn't screen the whole water conveyance framework because of the down to earth confinement of its establishment focuses. Shrewd, financially savvy IoT frameworks are currently empowering information to be gathered in any part of a brilliant water framework that can be estimated with sensors.

For applications where local logic/control cannot be provided, then the data needs to be brought into the central system for analysis and actions.

The system is proven in the field of water management, and commercially attractive too. Having knowledge of available water and its quality, along with various consumption points along with their demand, will allow better management of water in the city of Auckland. To solve the water shortage problem in New Zealand, the cloud computing platform Bizintellia was selected given the strong expertise on end node technologies, which is extremely critical in the data acquisition front. Without good plumbing, no IoT platform can be effective, no matter how robust them might be. The other reasons were relating to the ease of scaling, cost effectiveness and references. The methodology proposed is a ten-step process beginning from planning the requirements with stakeholders, then drawing out the solution design, budgeting and deadlines, together this would take 7 weeks. After getting the approvals, development and feedback phase begins, post which the testing is done, and bugs are fixed. The client is trained, and the plan goes live along with the supporting staff. The systems that would be monitored include water levels of various sources, water quality at these sources, Models from Metrological department on rainfall , consumption points. The functions that need to be monitored are also stated. The system architecture would follow the 3-Tier architecture of the BizIntellia platform. The techniques that could be used to management the quantum and frequency of data from the edge nodes:

Determine the frequency of data capture and transfer for each node. For non-critical nodes, less frequent polling of data is recommended
For critical applications like gas leaks or water leaks or consumption of water from an unauthorised source, logic could be embedded at the node itself, where the system would shut down if required, if a condition/rule is met. This not only reduces the load on the central system, but also speeds up the response mechanism.

8. Reference list
Amazon. (2020). AWS IoT - Amazon Web Services. Amazon Web Services, Inc. Retrieved 7 June 2020, from https://aws.amazon.com/iot/?nc=sn&loc=0.

Best IoT Water Management Solution for a Sustainable Future. Biz4intellia.com. (2020). Retrieved 6 June 2020, from https://www.biz4intellia.com/iot-in-water/.

Best IoT Water Management Solution for a Sustainable Future. IoT assignment Biz4intellia.com. (2020). Retrieved 6 June 2020, from https://www.biz4intellia.com/iot-in-water/.

Desk, W. (2020). Industrial Internet Of Things #Infographics. Visualistan.com. Retrieved 6 June 2020, from https://www.visualistan.com/2019/02/industrial-internet-of-things.html.

Hitachi, L. (2020). Monitoring and Control Systems for the IoT in the Water Supply and Sewerage Utilities : Hitachi Review. Hitachi Review. Retrieved 6 June 2020, from https://www.hitachi.com/rev/archive/2017/r2017_07/r7-03/index.html.

Kamienski, C., Soininen, J., Taumberger, M., Dantas, R., Toscano, A., & Salmon Cinotti, T. et al. (2019). Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture. Sensors, 19(2), 276. https://doi.org/10.3390/s19020276

Tags: it management critical analysis new zealand information technology

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