A typical-one left open 'in the wild', after maintenance...
Ideology(..in brief) for this Design Challenge.
1) Predicting the Next deadly Manhole EXPLOSION...
The random hazards associated to smoking, flaming and exploding manholes are a result from decrepit wiring of underground transmission lines, which can lead to sparks and further in contact with underground toxic-gases, result to 'next big-bang'(mostly). Still, the system lacks a clean method of knowing where or when the next outburst would occur; repairs are commenced only after a manhole-growls(ironically).
2) Effect of Temperature & Humidity changes on sewage-bionic life & Infrastructure
Temperature plays an important role in processes that affect the infrastructure and operation of wastewater works. Based on data obtained from wet weather conditions and cold periods, It was determined that a decrease of one degree Celsius in the liquid leads to a 10% reduction of the maximum specific net growth rate of nitrifying microorganisms. In sewer systems, high temperature accelerates processes involved in the sulfur cycle affecting the long term corrosion of pipes as well as the production of unpleasant odors and flammable gases. A study revealed that a change of 5 ℃ (from 20 to 25 ℃) increased the sulfide oxidation by 15%.
3) 'I see manholes, but no Lids'; this Theft is on the RISE
Reason for the theft of manholes and copper-cable theft, is usually motivated by the price of the scrap on the market. Based on current commodity prices for iron, a stolen manhole cover might fetch more than $60. But it costs about $200 to replace each one, not counting the additional labor involved. Chinese officials have taken an unusual step in the fight against scrap metal thieves by starting to fit their manholes with GPS tracking devices. Besides the cost and hassle of replacing the missing covers, there exists a much bigger concern about the hazards that gaping holes in city streets could pose to pedestrians and drivers.
4) Impact of high mechanical stresses on manhole-covers
Stresses resulting from vehicle traffic loading should not exceed the ultimate strength of the cover’s thickness at the diameter. The structure of the manhole, including the integrity of the cover is usually the responsibility of the utility served by the manhole. Most jurisdictions inspect roadway surfaces annually.
Pertaining to above problems, 'which we have faced throughout our entire PoC run, can be eliminated theoretically, but we have to go through long routes of field deployment'
Individual features of RSL10-SENSE-GEVK, which have been exploited in the final build for colloquially addressing a solution to the above problems;
- ON board Light level sensing.
- ON board Temperature sensing.
- ON board Humidity sensing.
- ON board Gyroscope sensing.
- ON board Accelerometer sensing.
- ON board Magnetometer sensing.
- ON board Pressure sensing (optional..in our case).
Things utilized for shaping it out:
- RSL10-SENSE-GEVK module
- 1x CR2032 Coin cell
- Sense & Control App by ON Semiconductor (playstore/appstore)
- IBM Watson IoT Cloud Account
- AWS Cloud Account(optional)
- 3D Printer
Fabricating it out...
An enclosure for RSL10Sense Board has been designed through Fusion360 and 3DPrinted. Quick references were obtained from the Board Resources (3DPDF) document for the RSL10Board, provided by the ONSemi but still conditions were tough to export the concerned 3D PCB file, even after utilizing Tetra4D converter. Hence, I went on to 'scratch' the enclosure from datum. [I'm Feeling Lucky]; OnSemi provided the necessary gerber for RSL10Sense, which was further imported into Altium Designer-19, and hence I was able to export the 3D PCB (top-mask and dimension layer)into the CAD program.
Using the 'force'(Vernier Calipers), and compensating it for the tolerances of ABS material, I was able to build an enclosure for RSL10Sense in one shot.
Interacting with the Sensor for Smart Cover
To receive and visualize the multi-sensor data collected through BLE peripheral, I have utilized ON Semiconductor's Sense and Control Android App. The features of App can be divided into three phases:
- BLE Connection,
- Sensor Data Display RT(value, Graph), and
- Sensor Data Cloud integration through MQTT protocol
After a successful connection has been made between the RSL10Sense and Android App, the IMU based motion data along with ambience-sensors is received and visualized in real-time.
Each sensor plays it's own game ON RSL10-SENSE-GEVK
The non-debugger version of hardware has been used for completing the design challenge, still one can try to go with the DB version to expand the capabilities of the hardware and on-board firmware (while I wasn't able to utilize the PDM microphone and VOC gas sensor, which would definitely add more value-proposition to the the final product), still the features & concepts from my original application-note for Think ON Design Challenge have been addressed in this project. While we will be geo-tagging our sense-hub, for efficient sensor-management (cluster-scenario).
- Ambient light sensor (NOA1305) has been utilized for reporting light intensity inside the manhole; the preset trigger thresholds on cloud-application will report for the routine-maintenance, as well as become an 'eye' for underground spark and flames, even before the deadly explosion has occurred. This feature has been tested, and reports to work efficiently.
- Measurement of ambient environment parameters (BME680) like Temperature and humidity helps in reporting the indirect sulphide oxidation levels, thus reporting the presence of harmful-odors and internal thermal levels associated with the manhole, which will be further used to notify the municipal authority for early maintenance.
- The magnetic sensor (BMM150), although a 3 axis digital compass which provides accurate readings of orientation data, has been used wisely for detection of sense-hub's proximity to the cover. In my final tests, I have used a small neodymium magnet which will be placed behind the circular case and in-between the mounting backplate. It is used to recognize and report the sense-hub status for local vandalism with the sensor-mountings.
- The gyroscope sensor (BHI160) plays an important role in reporting the theft/vandalism of manhole-covers, as well as report the same for accidental 'lid-open' status after post-maintenance along with geo-tagged data.
- The accelerometer unit reports for threshold defined surface activity, in form of mechanical vibrations induced on the cover, which helps in predicting the structural integrity of cover and report the same for early maintenance.
The provided low-power firmware and CR2032 battery alone provides enough juice for sensor to work for greater-than-a-year duration, since the required data-packets are usually pair or three per day intended for our job. But, I would like to replace battery holder for coin cell (5x former's capacity), which would further reduce the maintenance costs.
I have also observed, the RSL10Sense keeps on going to 'sleep-mode' quite frequently(low-power firmware), and needs a proper RESET for wake-up. Hence, integrating with our existing product, I was able to utilize the hardware in it's original(factory-state) form for building the sensor-hub for Smart Cover.
(referenced from individual research & Journals(ResearchGate) ...still need a continuum amount of reading-time, for exploring the limits of this DreamHardware)
Cloud Integration(..Mostly Watson)
Getting started guide : RSL10Sense Cloud Connectivity
Got few shots from AWS, during the early trials(the .json export feature is quite helpful, though the acquisition rate for dashboard update is at 'snail's pace' vs. IBM's IoT Cloud)
Similar, to AWS one can create custom boards under IBM Watson IoT Cloud "Boards Manager", and create custom Gauge, Time-stamped data insights, plotting on graph, etc.
You can also export the RSL10Sense data into spreadsheet, using Google Tesseract OCR Project, for performing post-analytics in MatLab. (Kylo Ren's Method!)
Finally publishing the data on IBM Watson IoT Cloud
(Manual labeling on trigger events has been performed, still need a large data-set for training a Classifier for ML based approach.)
The above pictures are obtained from IBM Watson IoT Cloud, which show the sense-hub;
The first dashboard image was captured under normal sensor working condition, with every other parameter like internal temperature, humidity and lux-levels. [Refer: dash#1]
Light-intensity data from 0 - 10lx under low light condition, and value 72lx(has been simulated for low intensity flame-condition). Moreover, values upto 400lx have been observed during the tests done with LPG burners. Also the geomagnetic sensor data has been depicted through gauge and pre-defined threshold status, weak lodestone disks report for values (179-300), while tests with neodymium reached peak value of (850); though it disrupts the calibration routine of sensor(resulting in high inacuuracies in orientation values), still works for our job. [Refer: dash#2 & dash#4]
The accelerometer & gyroscope values are time-stamped and recorded for post-processing application. Combining the IMU data through Classifier Learner App (Matlab) and Tesseract, one can predict the structural integrity of cover, by using the transfer-learning approach, even low dataset produces accurate results. [Refer: dash#3]
Would be sharing the actual deployment data in coming months, under PoC(Phase:2)